RN-1 Changing the classic technological perspective
RN-1.1 Contents
🚚 RN-1.1.1 Looking forward - paths by seeing directions
A reference frame in mediation innovation
When the image link fails, 🔰 click here for the most logical higher fractal in a shifting frame.
Contexts: ◎ r-steer the business ↖ r-shape mediation change ↗ r-serve split origin ↙ technical details ↘ functional details
There is a counterpart 💠 click here for the impracticable diagonal shift to shaping change.
The quest for methodologies and practices, dialectical closure
This page is about a mindset framework for understanding and managing complex systems.
The type of complex systems that is focussed on are the ones were humans are part of the systems and build the systems they are part of.
The phase shift from classic linear and binary thinking into non-linear dialectal is brought to completion in aliging the counterpart of this page.
A key concept is "dialectal closure", words that are not understandable without a simple explanation. 👁️
Dialectical closure means:
You have looked at something from all the necessary sides, and
nothing essential is missing anymore.
When closure is reached:
tensions are recognized, opposites are connected, action - meaning make sense together
It does not mean:
agreement, perfection, the end of change
It means the picture is whole enough to act responsibly.
Dialectical closure is when all three views are taken together before deciding the next move.
✅ Steering Closure
❌ Skipped to binary
Look ahead ➡ where am I going?
only looking ahead ➡ fantasy
Look around ➡ what is happening now?
only looking around ➡ drifting
Look back ➡ did my last move work?
only looking back ➡ paralysis
This is a simple list of 3 tensions, for awareness.
🎭
Using the 3*3 matrix the cycle as the flow around "execution".
✅ in 3*3 terms
❌ any is missing:
Problem is seen (Context * Sense)
no real learning occurs
Execution happens (Process * Act)
decisions feel arbitrary
Purpose is reflected (Outcome * Reflect)
people get confused or resist
This is a simple list of 3 tensions, in activities.
Without closure: frameworks feel abstract, discussions go in circles, people talk past each other
With closure: disagreements become productive, roles become clear, action becomes legitimate.
Dialectical closure is reached when context, action, and consequences are considered together, allowing meaningful action without ignoring tensions.
Although there are only 7 items mentioned by a tension in two axis it is about 3*3 items.
The quest for methodlogies and practices, seacch to STEM
👉🏾 This is far from a technology-tools mindset but it is very well possible to treat it as technology-relationship mindset.
Seeing it is relationship there are approaches in Science, technology, engineering, and mathematics (STEM) that enable to handle those.
In mathematics, a dynamical system is a system in which a function describes the time dependence of a point in an ambient space, such as in a parametric curve.
In probability theory and statistics, a Markov chains Markov chain or Markov process is a stochastic process describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event.
System dynamics (SD) is an approach to understanding the nonlinear behaviour of complex systems over time using stocks, flows, internal feedback loops, table functions and time delays.
A problem arises when to evaluate things that are not having a scale loike worth in value ethics Te
🚚 RN-1.1.2 Local content
Reference
Squad
Abbrevation
RN-1 Changing the classic technological perspective
The foundation is a fractal model used to organize thought and action. It maps two dimensions:
Horizontal (Relational Scales) : Sense ➡ Act ➡ Reflect.
Vertical (Contextual Scales): Context ➡ Process ➡ Outcome.
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By intersecting these, the framework identifies specific "cells" for organizational health (e.g., "Problem" is the intersection of Context and Sense; "Execution" is Process and Act).
In situations where a 3*3 approach is not rich enough extending it to 6*6 approach is solving that.
In complex environments (where humans are part of the system), traditional management fails because it ignores uncertainty and human bias.
Th change proposal is using a rigorous "grammar" of distinctions to ensure that governance is recursive, fractal, and responsive to reality rather than just "fantasy" plans.
An approach to understanding complex problems:
Actor Perspective: The narrative of the person closest to the problem.
Human Factors: Forces shaping behavior (incentives, power, norms).
Ecosystem View: How other actors experience the same situation.
Restated Problem: A synthesis that includes the history of failed prior attempts.
Feasible Influence: Determining what capabilities are actually needed to effect
Moving away from just asking for AI results (appeasing) and toward requiring AI reasoning.
Transitioning EA from a static descriptive role into an active participant in "integrated governance."
Diagnosing "broken systems" by looking at where the "sense-act-reflect" loop is interrupted (e.g., "drifting" happens if you only look around but never back). 🎭
The distinction between State Points (referred to as "Semantic Stable Cells") and Halfway Points is about the difference between being somewhere and transitioning between stages of understanding.
State Points are where we are competent and consistent.
Halfway Points are where we are stretching and pretending. 🔰
A goal among others is to help in seeing when you are "stuck" in a halfway point so you can move toward a new stable state.
It requires to see: using the language of progress to hide a lack of actual change.
Losing control in following a linear order
For acquiring knowledge, learning, a linear path is the old classic approach.
That assumed linear path is not the real natural approach it is broken because knowledge, effects, results are to be foreseen when they have not been experienced.
This kind of contradiction is bypassed in assuming the knowledge is there, Gestalt so the basics are able to build in better constructions.
Stable Points and halfway points a recursive problem in understanding
The first chapters are technological, deal with the "Serve" mindset.
Technology is not just about computers; it is the "Grammar" of the system.
The focus is on Ontology (how we define things), Taxonomies (how we categorize things), and Data Topology (where things are).
The Goal: It aims to build the "Reference Frame." Before you can think about complex "Halfway Points," you need a stable technological language. 🔰
If the "Stable Points" aren't defined correctly here, the transitions later will be pure chaos.
Technology is "Semantic Blind": Technology alone cannot "close" a system.
You can have the best technology structure in the world, but it is "incomplete" until a human applies Sense-Making to it.
Focus on the "How," not the "What": The geometry of information (how it flows) but leaves the specific technical "dimensions" empty.
Every organization has different tools (AI, SQL, SAP, etc.) and they change in time.
The chapter is a "blank map" meant to be filled with your specific technical reality at a moment.
Invoke Harold Leavitt and Talcott Parsons: Bridging the gap between "Management Science" (the technical engine) and "Sociology" (the social system).
In an overlay these two diamonds""one horizontal and one vertical""you are creating a 3D Navigation System for a value stream.
Leavitt's Diamond (Technology, Tasks, Structure, People) is the Engine.
Perspective: It focuses on Efficiency.
The Dashboard: This measures how fast we are moving and how much force we are applying. It is the "Horizontal" axis of execution.
Parsons' AGIL (Adaptation, Goal Attainment, Integration, Latency) the Compass.
Perspective: It focuses on Effectiveness and survival within an environment.
The Dashboard: This tells us where we are in the landscape and why we are going there. It is the "Vertical" axis of ideology and purpose.
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You can have all the "Power and Speed" (Leavitt) in the world, but if your "Location and Directions" (Parsons) are wrong, you are just accelerating toward a cliff.
When set Leavitt horizontally and Parsons vertically, the area where they overlap creates a third emergent diamond at the center, this is the Value Stream Nexus.
By reaching back to the 1950s and 60s, it is saying that our modern "DevOps" or "Digital Transformation" problems aren't actually new.
They are the same friction points between social systems and technical systems that Parsons and Leavitt identified decades ago.
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The problem in this the theory doesn't unfold linear so practices supported by theory are problematic until theory gets closed.
Starting these dashboards but it leaves them "incomplete" because the intersection hasn't happened yet.
We can see the Leavitt components, bt the "New Diamond" only appears when you move into the later chapters and drop the Parsons framework on top of it.
This is itself a halfwaypoint for the human dialectic that is required to make the technology meaningful.
🚚 RN-1.1.4 Progress
done and currently working on:
2012 week:44
Moved the legal references list to the new inventory page.
Added possible mismatches in the value stream with a BISL reference demand supply.
2019 week:48
Page converted, added with all lean and value stream idea´s.
Aside the values stream and EDWH 3.0 approach links are added tot the building block patterns SDLC and Meta.
The technical improvements external on the market are the options for internal improvements.
2025 week 49
Start to rebuild these pages as a split off of the Serve devops.
There was too much content not able to consider what should come resulting in leaving it open at the serve devops page.
When the split-off happened at the shape design the door opened to sess how to connect fractals.
Old content to categorize evaluate and relocate choosing three pages inherited at the this location, other pages to archive
2025 week 50,51, ...
Extensive reflections in using DTF by using chatgpt, surprising answers to reflect.
A different perspective in using DTF than for persons, using text artifacts.
Two visions in the the connections one of DTF and the other of Zarf Jabes Cynefin.
2026 week 1,2,3, ...
Chapters RN-2.1 to RN-2.6 draft finished a full range from solution from cognitive grammar to boundary governance.
The first tree are setting the methods for observation.
The next tree are details for governance, the issues of failing EA and the structural split between operations and administration.
No idea how to proceed in the chapters RN-1.2 to RN-1.6 it is old content not connecting to any part.
The question is what is the best next step to replace it.
Chapters RN-3.1 to RN-3.6 trying to put content in but aside some deepening in theory the structure is missing.
The deepening in theory gave however the options to replacement starting in RN-1.5 and than downwards (reverse order).
2026 week 10,11,12, ...
Slowly working on chapters RN-1.1 to RN-1.6 replacing it ot a complete new perspective.
RN-1.5 got the why of dashboards.
RN-1.4 the processing of information.
RN-1.3 The how of transformations in solving conflicts.
RN-1.2 The goal of processes as a whole not by parts.
RN-1.5 and RN-1.4 in draft finished goint into the frist ones. Going back to the question of why 6-7 categories? That I gat an answer for in RN-2.
👓 Highly related to this is information processing mindset, Jabes Jabsa Zarf how it started:
I-Jabes The technological idea of knowledge management that is bothering me.
Topics that are unique on this page - executing methodologies
It is focussing on the technology. serve, related thoughts but started from what is experienced in trying to understand the soft communication and mediation thoughts, shape.
In the shape counterpart requirements for a knowledge management system are set to the level of grouping what can become technical records.
👉🏾❶ The challenge in ICT for using useful practices in ontologies taxonomies.
A vocabulary and taxonomy for understanding between parts is in place
A standard reference in naming conventions and knowledges is in place
The standard naming convention for elements supports:
a wide possibility in change (velocity)
a wide possibility in variety (volume)
easy exchange in technology (vitality)
When this was the only interesting for trying to see different perspectives, there was no emergent thinking.
An other dimension for perspectives in contexts is:
What is the primary duality-dichotomy for contexts?
Organizing, leading: From the first wave there is the anarchy vs hierarchy.
Decision making for a goal: for the now based on the past near or far future?
Decision making evaluating worth with the goal: deterministic or probabilistic?
What is the second duality-dichotomy within contexts?
Organizing, leading: Are the detailed actions initiated top-down or bottom-up?
Decision making for a goal: Are the made pro-active or reactive
Decision making vision in worth: setting boundaries, scope in autononmy vs guiding.
What is the third duality-dichotomy?
Organizing, leading: Are the detailed actions grounded in well set proven competence?
Decision making for a goal: Are the made pro-active or reactive
Decision making vision in worth: setting boundaries, scope in autononmy vs guiding.
👉🏾❷ The maturity difference for OIT, AIT and IIT in safety.
The bold claim is to achieve "security by design" embedded in the system, a generalised view how information flows.
The reasoning:
OIT Operational IT: "Security by design" is included in OT, operational technology for physical solutions from design to implementation.
Security measures are taken beforehand.
Of course, things sometimes go wrong, and actions are taken to address them.
The mindset is preventing fires
AIT Administrative IT: "Security by design" is an illusion in administration it's not a standard part of the design.
Attempts are made to make things presentable afterward with tools, caught up in the buzz and hypes of published new threats.
Penetration tests are the guiding principle for the implementation result.
What prevails is doing security after the fact to achieve a point of something that's considered workable.
The mindset: putting out fires.
IIT Informational IT: "Security by design" is a fantasy because security measures are not part in the mindsets in presenting what is going on.
👉🏾❸ In the different dualities-dichotomies & variety of information types acting as a whole.
In the intangible setting of information the biggest challenge is in the understanding what knowledge processing means.
That property of knowledge being intangible is the root cause of a lot confusion:
The eDIKWv: Events Data Information Knowledge Wisdom Vision getting combined to the intelligence cycle (IC).
For the soft skills the categories of Bloom (learning) and Dilts (social fitness) are aligned to eDIKWv and IC.
Defining layers we could see where something goes wrong: "operational gap", "cognitive gap" and "strategic gap".
👉🏾❹The question for optimizing the functioning - functionality aligned to the worth.
There are in the intangible setting of information flows different ones for a product/service and the descriptions knowledge of enabling that product/service.
The property of intangibility is a cause of a lot confusion.:
Leavitt's diamond: Technology, Tasks, Structure, People, focuses on Efficiency.
Parsons' diamond: Adaptation, Goal Attainment, Integration, Latency, on Effectiveness
Goal: Worth not only financial but more important ethics, purpose sets reflections in both.
The interacting relations by RKGg: Resources, Knowledge, Governance.
The two competing perspectivhgfs must be aligned coordinated they are a duality and dichotomy. They cannot exist without each other but they are easily getting into conflicts.
It is the art in control how the conflicts are managed.
Topics that are unique on this page - triggering methodologies
This are the core topics that are related to the diagonal counterpart that is deepening the social neural aspects and what is needed for a Stem mindset.
👉🏾 ❺ The workshop proposal is designed to solve the problems seen by observation in a social intervention: the Workshop.
Seen: a timeless structural conflict between social goals and technical tasks as problems.
Goal: move from a "flat" process view to "thick" understanding of why things are stuck.
Once the workshop has surfaced the friction, you need a place to put it in.
There must be a way to get in translated into requirements for realisations.
👉🏾 ❻ The Problem State proposal is about a structure way for categorizing problems.
It provides the Reference Points (R) for the "Broken" states. If the workshop is the "X-ray," the Problem State is the "Diagnosis
The Workshop provides the raw data of human frustration and technical lag, and the Problem State Proposal provides the semantic structure to categorize that data.
Topics that are unique on this page - understanding methodologies
It is focussing more at complex relationships.
Introducing the use of a full dialectical framework that can be use in evaluating frameworks and situations.
The DTF, dialectical thought forms are by 4 main categories each in seven sub-categories.
The 4 main DTF categories: Relationship(R), Process(P), Context(C), transformation(T).
Alignment of DTF to others: Zachman VSM Cynefin extended to many more.
The reasoning of about 7 categories for becoming dialectical closed.
O.Laske educated at the frankfurter school created DTF and more using that transitional language for change in time (learning)
The 6-7 categories are somehow different in when it is evaluating the past, building up a vision for the future or preparing a resalsion for the now.
👉🏾 ❼ using a time dimension transformation in knowledge learning growing.
The learning paths are having a dimension of time, that is explicit or hidden
Adding time the knowledge itself is changing knowledge from the paste is not the same of that in the now or the future.
Knowledge evolves by options, choices and events.
👓 When only looking back in the paste it answers the "why".
🚧 Change to future it becomes "which?"
🕳 It is left open for the now.
Components are building blocks.
🚧 are given from the paste needing adapations
🕳 left open in the future
👓 but needed in the realisations for the now.
Worth in several meanings like wealth morality purpose,
🕳 can be evaluated for the past using the than not existing knowledge
👓 is guessed in what is knowing at the moment for the future and
🚧 is set and experienced in the now.
The result will be by at least two knowledge lines supporting for changes in time. Often we are only able to see only one.
The first is for what is known how the work is done, The Second is the becoming of work being done in the future.
🤔 There are two possible unique sets of this 3*3 variations for the three attributes 🚧,🕳,👓
👉🏾 ❽ The perspective in changing the flow or change in managing the flow.
Just looking at how work is done is measuring power and speed
Evaluating how work is done is measuring the direction and the progress between where we are to where we want to be.
The Worth is driving both but is by itself hardly measurable.
RN-1.2 The quest in understanding the path going to somewhere
The classification for management, executive, information was based on technical approaches for:
Assuming disciplines involved in a system are having defined agreed boundaries within them for outcomes with worth.
Each discipline should have a shared language, taxonomy, set at boundaries (standardized).
There should be no siloes between disciplines. The system acting as a whole including safety.
🚧 Breaking the assumptions of shared languages are in place, safety is in place.
🛠️ RN-1.2.1 Understanding systems by Concepts - Ontology - taxonomies
Understanding Concepts - Ontology - taxonomie
The anatomy of an ontology (W.H.Inmon J.Talisman 2026)
People can say or write anything they want. There simply is no rhythm to creating and collection of text.
Text can come in many forms, voice, print, spreadsheets, email and so forth.
In a word, reading text and extracting meaningful data from text was and is a daunting task.
There is a technology/discipline that greatly abets the challenges of extracting meaningful data from text. That technology/discipline is called an ontology. ⏳
What in the world is an ontology?
Note that the word text is use for any form of communication.
An ontology characterized simplified:
carefully vetted vocabulary designed to unravel and classify a body of raw text.
containing what can be called a series or collections of taxonomies.
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What exactly is a taxonomy?
A taxonomy is a vocabulary of related words designed to classify something:
a tangible object, a car, an airplane,
an intangible object, a concept, a discipline,
a football team, a method of teaching swimming and so forth
The only requirement is that classifications are sensible in the intended context.
A taxonomy has boundaries to the ontology it resides in.
contain only taxonomies that relate to the ontology focus.
ontology focus has an influence on the contents of the taxonomies it hosts.
A taxonomy has multiple levels of classification:
They have some one unifying category to draw the elements together.
They may have multiple levels of categories contained inside the taxonomy.
The taxonomy can show relationships between classifications and words:
Each classified word has a similar relationship to words that are being classified as all of the other words contained for the same classification.
Taxonomies inside a ontology may or may not have relationships to each other.
A taxonomy can be generic by a generic discipline or settled branches.
A generic taxonomy is a taxonomy that can be used in many places.
From generic disciplines they can exist independently. Examples:
For settled branches there are common reusable taxonomies. Examples:
banking (credit card, savings and loans ), insurance, airlines,
railways, oil/gas electricity energy,
restaurants, supermarkts, shops
Defining and maintaining the ontology and taxonomies.
The biggest challenge in building and using a taxonomy lies in the first iteration of the building of the taxonomy.
Ontology, taxonomies will change over time as the enterprise, organisation, change.
The "good" is that most enterprises, organisations only change marginally over time.
Some taxonomies are generic across multiple ontologies, these are generic disciplines.
👉🏾 Note security safety, morality ethics, is assumed to be a generic discipline.
⚠️🚧 Security safety, morality ethics, should be a generic discipline using information technology but that is a failing situation.
Using the word conceptual or ontology taxonomy business model
Using different words. conceptual model, ontology taxonomy can be confusing.
Conceptual -ontology (LI: R.Ross 2025).
In 1993, Gruber originally defined the notion of an ontology as an "explicit specification of a conceptualization". In 1997, Borst
defined an ontology as a "formal specification of a shared conceptualization". ⏳
Asking an analsyes for ontology to concepts gave the following.
In the methodology of Ronald Ross, an ontology (primarily expressed as a concept model) is a strategic framework designed to ensure shared understanding and business clarity across an organization.
Core Concepts & Functioning : Concept Model as Ontology: Ross defines an ontology as a "shared conceptualization".
For him, the core component of a Business Knowledge Blueprint is a concept model, which identifies the essential "things" (nouns) and their relationships (verbs) that matter to a specific community.
Business Rules Integration: Ross is widely known as the "Father of Business Rules".
In his framework, an ontology provides the structural foundation (vocabulary) upon which business rules (behavioral and definitional) are built.
You cannot have clear rules without precisely defined concepts.
Eliminating Semantic Silos: Organizations often suffer from functional silos where different departments use the same terms to mean different things.
Ross's strategy replaces these "semantic silos" with a "Knowledge Commons" a unified business vocabulary that serves as a common ground for all stakeholders.
Application-Centric vs. Knowledge-Centric: A key part of his development strategy is moving away from application-centric development (where data is designed for a single system) toward a knowledge-centric approach.
This ensures that data is "potent," reusable, and manageable across different domains.
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The work behind and achieving acceptance for its usage is development strategy.
Define Terms Precisely: Use the Business Knowledge Blueprint to establish unambiguous definitions based on business logic, not IT requirements.
Map Relationships: Structure concepts according to their inherent business relations to create a Concept Model.
Bridge the Gap: Use these blueprints as a "front end" for technical system design, ensuring that IT implementations (databases, AI, etc.) speak the "language of the business".
The hard work for an ontology and taxonomies and business model
Continuation of analysing "The anatomy of an ontology (W.H.Inmon J.Talisman 2026)".
Just defining what it is about is not enough it should be usable in practice.
The work behind the words for an ontology :
represents decisions, thousands of small, careful decisions about how concepts relate to one another, where boundaries should be drawn, and what matters enough to include.
is a human activity, not a mechanical one. The ontology builder must understand the words of a domain AND the conceptual architecture underneath those words, the way practitioners in that domain actually think about their work.
The work behind Scope and granularity:
The most effective ontologies are purpose-built. They serve a specific need within a specific context.
The ontology builder must resist the temptation to capture everything and instead focus on capturing what matters for the task at hand.
Determining the scope or coverage of a taxonomy and ontology are both decisions that must be analyzed and decided upon by humans, as ultimately, these decisions construct the profile of the organization, workflows and the things human workers care about and need, to be successful.
If the need is to route documents to the correct department, broad categories may suffice.
If you need to identify patterns in outcomes, fine-grained distinctions become essential.
The work behind relationships beyond hierarchy:
Associative relationships allow the ontology to represent the rich web of connections that characterize any complex domain.
These are not taxonomy relationships.
An ontology is never truly finished, language evolves, domains change, new concepts emerge while old ones fade from use.
The ontology must have a steward, someone responsible for keeping it aligned with the reality it represents.
The ontologist is not a technician cataloging words.
The ontology builder is making choices about what matters: choices that will ripple through every analysis that depends on the ontology upstream, downstream and in between.
🤔 To be short: it is a never-ending story of activity for continuous improvement.
🛠️ RN-1.2.2 Information security taxonomy and ontology relationship
The state of the taxonomy for information security
When assuming security would be part of ontologies by a discipline having a generic taxonomy, there should be references for those.
Howevers what is found and seen are practices of doing without any relationship to ontologies. ⏳
It is a signal of a fundamental gap causing a lot of issues. Information security (infosec) is the practice of protecting information by mitigating information risks. It is part of information risk management.
There are many specialist roles - tasks - in Information Security including:
securing networks and allied infrastructure,
securing applications and databases,
security testing,
business continuity planning,
electronic record discovery, and digital forensics.
information systems auditing,
To standardize this discipline, academics and professionals collaborate to offer guidance, policies, and industry standards on passwords, antivirus software, firewalls, encryption software, legal liability, security awareness and training, and so forth.
This standardization may be further driven by a wide variety of laws and regulations that affect how data is accessed, processed, stored, transferred, and destroyed. ⌛ That is a siloed technological approach nor really a systemic structural one, worse just reacting after the fact. Information Security Attributes: or qualities, i.e.,
Confidentiality, Integrity and Availability (CIA).
Information Systems are composed in three main portions,
hardware, software and communications
with the purpose to help identify and apply information security industry standards, as mechanisms of protection and prevention, at three levels or layers:
physical, personal and organizational.
Essentially, procedures or policies are implemented to tell administrators, users and operators how to use products to ensure information security within the organizations
The quest for aligning security to the ontology generic.
Seen the gap what would be need to change for closing the gap in secure information processing?
Building an ontology and taxonomy is requiring seeing the relevant layers. ⏳
The question for relevant layers, a proposal using 6 levels:
Abstraction
classification level
System integration level
context
ontology-taxonomy
System as Whole
concept
organisational
Procedures
logical
personal
People, processes
physical
physical (segmentation)
hardware, software, communication
component
applications (business)
Identity & access - CIA, BIA
instance
tools, middleware
Encryption, defending software
An important difference for procedures and processes.
👉🏾 procedures are activities to overcome issues.
👉🏾 processes are standards that hopefully prevent issues.
No single point of failure. ⇄ Distribute dependencies (cloud, identity, backup).
Data is owned, the application is replaceable. ⇄ Separate data from the software layer.
Data must always be exportable. ⇄ Open formats. Complete. Instantly available.
Recover outside the primary provider. ⇄ Backups & recovery are configured independently.
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Separated processes for what should be one.
The Life cycle of continuity planning is identical to that of the business process flow.
It is unexplainable they don't go together.
Business continuity planning (BCM) is a relationship part of the safety taxonomy.
It is to be defined as "the capability of an organization to continue the delivery of products or services at pre-defined acceptable levels following a disruptive incident"
An organization's resistance to failure is "the ability ... to withstand changes in its environment and still function".
Often called resilience, it is a capability that enables organizations to either endure environmental changes without having to permanently adapt, or the organization is forced to adapt a new way of working that better suits the new environmental conditions.
The basic extremes for processes including safety by design
Looking strictly at the Hierarchical (Order/Control) versus Anarchical (Freedom/Chaos) duality, we are looking at the tension between Strict Governance and Operational Autonomy.
In this view, the hierarchy prioritizes the integrity of the system, while Anarchy, in the functional sense, prioritizes the speed and needs of the individual user or project. ⏳
Hierarchical (Centralized Order):
Access 🤔 Gatekeeper Model: Access is denied by default.
Every permission requires formal alignment with a rigid Identity & Access Management (IAM) hierarchy.
Time LCM 🤔 The Master Calendar: Lifecycle is dictated by contract dates (central procurement system).
Termination and deletion happen by fixed schedules.
Change Risk 🤔 The Change (Ethic) Advisory Board (CAB, EAB): Nothing is allowed without a formal assessment and documented "Go/No-Go" decision from the top.
Process & Security 🤔 Standard Operating Procedures (SOP): Strict adherence to a framework (e.g., Itil, ISO 27001, DPRR-DPIA GDPR) are a a set of non-negotiable rules.
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Anarchical (Distributed Autonomy):
Access 🤔 Open-by-Default / Peer Trust: Access is fluid.
Users grant each other permissions or use shared credentials/API keys to "get the job done" without central approval.
Time LCM 🤔 The Natural Cycle: The lifecycle is determined by the "pulse" of the work.
Data stays long, only deleted when the team runs out of storage or interest is lost.
Change Risk 🤔 Organic Evolution: Scope "creeps" or evolves naturally based new features or the user's changing needs.
Risks are accepted implicitly by the person doing the work.
Process & Security 🤔 Ad-hoc Workarounds: Security is "situational." Teams invent their own processes, bypass security protocols, if they perceive them as "friction".
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The Core Tensions:
The Hierarchical Risk A: The system becomes that complex, the (Hierarchical) centre it is changed into rigid bureaucracy. "Hierarchical Reactive"
The Hierarchical Risk B: The system becomes so rigid (Bureaucracy) that the organisation can no longer compete or adapt to time-sensitive scope changes.
The Anarchical Risk: The system becomes so fragmented (Shadow IT) that a single scope creates a safety "black hole" the central office doesn't even know to exist.
A Tragic mismatch: failing to adapt worth in the system
Organisations are stuck in "Hierarchical Reactive" because it feels safe for auditors.
The switch to "Population Proactive" is terrifying to a traditional CISO because it requires trusting the user.
Standard frameworks (like SOC2 or ISO) are designed for defensibility, not necessarily agility.
When get hacked:
"Hierarchical Reactive": you can say, "We followed the checklist."
"Population Proactive": to explain why "untrained users" were part of your security logic.
⚠️
The industry is currently failing because it refuses to make this switch.
I believe the "Population Proactive" set is the future of the majority for Cyber Security.
Access should be "Guided" by the centre but "Triggered" by the user.
Risk Change should be identified by the ones acting, not an audit visit.
❶
Access Control & Connectivity
Reactive vs Proactive: Implementing Zero Trust and Just-In-Time (JIT) provisioning.
Proactive: You grant access before the task starts, but it expires automatically.
Reactive: Revoking access after an audit find or a breach occurs.
Guided vs. Population: adapt to suddenly needs e.g. access to a new tool to stay productive
Guided: Central IT defines the "Golden Rules" for access based on roles (RBAC).
Population: "Peer-based" access requests. The system adapts in alignment to boundaries.
❷
Time LCM Life Cycle Management
Reactive vs Proactive: Follow planned dates for data, follow planned boudaries
Proactive: Setting "Hard Stops" and data deletion triggers at the start of the contract.
Reactive: Scrambling to delete data, renew contracts at events e.g. expiration, GDPR.
Guided vs. Population, actors signal when information is actually finished
Guided: Corporate policy for categorised information be purged expired by x or y years.
Population: Signals are triggering LCM stages not an "official" corporate calendar.
❸
Change Risk Evolution & Impact
Reactive vs Proactive: Business Impact Analysis (BIA) are guiding choices
Proactive: BIA usage before changes covering CIA (Confidentiality Integrity Availability).
Reactive: Patching vulnerabilities after experienced events breaking business or by signals.
Guided vs. Population: Using feedback from employees to find where scope has changed.
Guided: Central offices sets the risk appetite (e.g., "We never accept high-risk changes").
Population: "Shadow IT" discovery because staff found "better ways" to use tools.
❹
Process & Security The Framework
Reactive vs Proactive: Bug Bounty style
Proactive: Continuous monitoring & automated "Health Checks" at assumed boundaries.
Reactive: Relying on static spreadsheet/questionnaire that are outdated by day-one.
Guided vs. Population: Encouraging employees to report "weird" behavior or UI changes
Guided: Standardized ISO/NIST frameworks dictated by the Compliance department.
Population: Crowdsourced security, rather than just following the manual.
🛠️ RN-1.2.3 A worth taxonomy approach to organising sub-disciplines
An awarenes for alternatives in information strategy -safety
Similar ones to define for other aspects of worth but a focus for safety is the first one to understand.
The goal is chosen an appropriate one out of all six that is the best fittest for a situation.
The four by four combinations in a more detailed table:
Access
Time LCM
Change Risk
Process & Security
2 central proactive
✅ Zero Trust Architecture: Pre-defined roles and Just-In-Time (JIT) access that grant permissions only when needed.
⏳ Automated Expiry: Policy-driven triggers that automatically archive data and terminate credentials on contract end-dates.
🛡️ Predictive Modeling: Centralized risk assessments performed before any vendor scope change is authorized.
🤖 Continuous Monitoring: Real-time automated scans and "Golden Image" configurations enforced by HQ.
3 central reactive
🔐Emergency Lockdown: Centralized "Kill-Switch" to revoke all vendor access immediately upon detection of a global breach.
📅 Audit-Driven Cleanup: Manual data purging and contract termination initiated only after a compliance failure or audit.
⚠️ Incident Patching: Risk mitigation steps taken by the central team only after a scope change causes a system failure.
📑 Static Reporting: HQ requesting manual security questionnaires (SIG/CAIQ) only after a vendor's security score drops.
5 population proactive
👥 Peer-to-Peer Validation: Teams identify necessary access levels early based on actual project workflow needs.
📢 Early Sunset Alerts: Project leads signaling that a vendor's work is finishing ahead of schedule to trigger early offboarding.
💡 Innovation Feedback: Employees suggesting safer ways to integrate vendor tools based on their daily hands-on experience.
🛡️ Security Champions: Departmental "power users" who voluntarily promote best practices before IT intervenes.
6 population reactive
🔑 Ad-hoc Requests: Users requesting access "on the fly" because they cannot perform a task under current scope.
🕒 Extension Requests: Teams asking for more time/retention because the central LCM didn't account for project delays.
🔍 Shadow IT Detection: Identifying risks only after employees have already started using a vendor's "new"
🚩 Whistleblowing: Users reporting "weird" vendor behavior or UI changes that seem insecure during their daily use.
The search for a balance in information strategy
To find a "Balance," we must treat the four dualities as a Strategic Menu.
Depending on the situation (e.g., a low-risk SaaS tool vs. a high-risk core banking system), what is the best fist to choose. ⌛
The Devil's Advocate: the "Hierarchical Fortress" is not an obsolete relic, but a biological necessity for survival in high-stakes environments. ⏳
The Switch: Hierarchy is the only way to ensure a Minimum Viable Competence before a single "bottom-up" idea is allowed to touch the system.
The "Hierarchy" shouldn't give orders; it should give parameters.
The center defines the "Security Intent," but the population executes the "Technical Scope."
Security should be a "Platform Service."
The center provides the "Cyber-Fortress" as a service that the autonomous teams must use, rather than building their own weak fences.
The switch hasn't been made because we haven't solved the "Competence Gap".
The speed of Haier is admired, but we are terrified that our "working force" isn't as trained as Marquet's nuclear submariners.
Until we automate competence (via AI guardrails), the "Hierarchical Fortress" remains the only way to stay out of court.
The Tragic mismatch in data strategy
By ovelaying the models: eDIKWc (Ackoff, Carpenter, Bellinger, Cleveland ), Dilts (Psychology), Bloom (Cognitive) and the IC (Intelligence Cycle), shows you can see that effective decision-making (Intelligence) only arises when the Vision (Dilts' 'why' and Bloom's 'creation') directs which Events we perceive in the first place.
In the context of cybersecurity, the connection between the six layers of EDIKWV, Dilts' Logical Levels, and the Intelligence Cycle clearly illustrates why many organizations remain vulnerable despite millions of investments. ⏳
Case Study: The Cybersecurity Pyramid in Action:
eDIKWv
Cybersecurity Context
IC
Focus - Noise
Events
Raw log files, network traffic, firewall pings.
1
Selecting Planning & Direction
Environment: Is our "sensor environment" complete, or do we have blind spots?
Data
The billions of individual rules in a SIEM system.
2
Collection
Behavior: Do we only record what happens, or also what doesn't?
Information
An aggregated dashboard showing a "brute force" attack.
3
Processing
Capabilities: Do our analysts have the tools/skills to see patterns in the noise?
Knowledge
The understanding that this attack is specifically targeting our IP rights.
4
Analysis
Beliefs: Do we think we are "too small to be hacked" (Bias)?
Wisdom
The decision not to just close the gate, but to inform the entire chain.
5
Dissemination
Identity: Are we acting as a "victim" or as a "resilient supply chain partner"?
Vision
Strategy: "We are the safest haven for customer data in our sector."
6
Evaluation / Feedback
Mission: Does our vision drive the procurement of tools, or do the tools drive our vision?
A move from "what do we see?" to "what does this mean for who we want to be?". ⌛
Where things often go wrong: The "Operational Trap".
Many companies are stuck at levels 2 and 3 (Data & Information).
They have beautiful dashboards (Information), but lack the Vision (Level 6) to determine which data, information, is truly relevant.
This leads to:
Alert Fatigue: Analysts are drowning in information without the knowledge of the broader context.
Tool Mismatch: People purchase an EDR solution (Capacity/Level 3) while the biggest threat lies at the Beliefs/Culture level (Level 4) (e.g., phishing vulnerability).
Lack of Context: Without Wisdom (Level 5), a SOC analyst cannot determine whether a suspicious action by an administrator is a legitimate emergency fix or a hostile takeover.
⚠️
The problem often lies in an upside-down approach: people purchase tools (data/information) without a clear vision or identity "who do we want to be?" and "what to protect and why?"
🛠️ RN-1.2.4 Continuations for what is known for new system improvements
Hardening is indispensible but always tailored
Without practical details it is hard to see what to do.
A hardening checklist for safety:
Proactive limits in execution: accountability for the proces owner.
Ensure knowledge in what can be normally done, normally expected to be done.
Safety: use what is normal knowledge behaviour and sets limits according those.
Identities & licensing: accountability for the process owner.
Use dedicated Integration Users (service accounts). Licenses should be aligned to this.
Safety: Restricted Tools to API-only access by default preventing from using a UI.
Integration dedicated accounts: auditability & limiting impact when compromised.
Safety: Never reuse a single "generic" integration account for multiple systems.
Use segmentation for different tasks for different classes in sensitivity and risks.
Safety: Use multiple accounts by a person maybe different domains defined to his tasks.
Access Control & Network Security: accountability for & at the process owner.
Ensures service accounts can only be accessed from your known middleware or server.
Safety: Restrict Login source locations limiting usage by service accounts.
Safety: Doing this for natural users is limiting it to known locations (e.g. VPN).
Enforce MFA for Logins by accounts during the initial handshake or login flow.
Safety: MFA for API logins service accounts (non personal) without a manual action.
Safety: MFA is standard for natural personal users, an additional manual action.
Least privilege: Well defined roles aligned to functions setting limited scopes.
Safety e.g.: Only grant "API Enabled" permission to users require it in their function.
Authorization (Least Privilege): accountability for the process owner.
Use the appropiated security model: hierarchical layers (files) vs object based.
Safety: Permission Set-Led layers for specific permissions using Permission Sets.
Quickly and at low cost installing & configuring tools conflicts to safety & morality.
Safety: Never use "System Administrator" at integrations or usual work.
Object & Field Level Security (FLS): Explicitly grant Read or Edit only when needed.
When managing many records is needed, use Sharing & stacked Rules.
Safety, Audit: Avoid "Modify All" (network shares) permission at all costs.
Connected Tools Governance: accountability for the proces owner.
Limit the vulnerability surface by denying all uninstalled/unwanted connected tools.
Safety: Block "Uninstalled" "unwanted" tools" unless they are explicitly allowed.
Limit scopes to the bare minimum, e.g. goal of prevention code injections.
Safety: Scope Limitation in accordance to the work that is expected to be done.
Refresh tokens are used minimizing the impact of overlaoding in MFA requests.
Safety: Shorten Refresh Token Lifespans to balance impact in too short/long.
Reactive limits evaluation: accountability for the proces owner.
Ensure your safety settings haven't drifted from what the intention was.
Safety: Run Security Health Check regular, im for a score of 90% or higher.
Note the difference in the roles at 1,6 as governance activity vs 2,3,4,5 categories.
Understanding systems, the floor practices
Why Do Manufacturing Systems Fail? (LI: K.Kohls 2026)
Most manufacturing systems don't fail because people are careless, they fail because they were designed using averages: balanced lines, one-piece flow everywhere, high OEE (Overall Equipment Effectiveness) at every station. ⏳
On paper, these designs look flawless, on the floor they create:
growing queues, longer lead times
chronic firefighting and "mystery" bottlenecks that seem to move every week
To understand why, we don't need another framework or philosophy we need a dice game.
A simple simulation, used for decades, where each station rolls dice to determine output.
When variability is introduced, something uncomfortable becomes obvious very quickly: systems designed to be
balanced, fully utilized, locally efficient
become unstable by design as a whole.
There is fit for what (the problem state), how, where, who when which.
The question where ToC belongs to, is a duality between the how and who for perspectives in different levels of abstraction. ⌛
In the following article series, I'll use that dice game and basic simulation logic to show:
why balanced lines collapse under variability
how buffers reveal the true bottleneck
why OEE often damages throughput
how lead time is mostly an inventory decision
why capable systems design bottlenecks instead of discovering them
and why manufacturing, uniquely, resists simulation despite its success everywhere else
This isn't a critique of Lean, TOC, or any method.
👉🏾 It's a critique of intuition-driven design in a variable world.
If your system feels like it's constantly fighting itself, there's a good chance it's doing exactly what it was designed to do.
Does Toyota Principle #3 Improve Focus? (LI: K.Kohls 2026)
Instead of pushing work into the system, downstream processes signal when they are ready for more material.
When systems become predictable, problems become easier to see.
RN-1.3 The location setting for the path going to somewhere
The classification for management, executive, information is based on historical first wave habits for:
Assuming the type of structure and way of communication at the system is fixed hierarchical for predictable outcomes in worth.
Decisions should be based on how the organisations is lead in well structured way. There are multiple structures as options.
There should be no ambiguity's in the chosen structure of decision making and no ambiguities in shared taxonomies.
🚧 Breaking the assumption of a stable lead system, stable taxonomies.
📐 RN-1.3.1 Changing vocabulary taxonomies in adapting by leading styles
Types of Leadership and paralyses by leading
Leading an organisation has options in styles.
Looking for a model that combines high clarity with high trust, that balance is often described as providing "freedom within a framework.".
Intent-Based Leadership provides "the what and the why" and the necessary "Guardrails" (safety and competence checks).
Subordinates do not ask for permission, the use autonomy by statin, "I intend to..." and get confirmation if it aligns with the framework. (D.Marquet)
Autonomous Leadership or "Empowering Leadership," is active, not passive.
Unlike a servant leader who might be seen as "submissive," an autonomous leader provides basic instructions and clear expectations but then steps back to let the team take full ownership of the "how".
An Architectural leader focuses on designing the system, rules, and environment (the "house") rather than the daily activities of the people inside it.
The leader ise "in charge" of the structural boundaries, but the team has full autonomy over how they operate within those walls.
Originating from military strategy, Mission Command or "Visionary Leadership" is the ultimate "boundaries + autonomy" model.
The leader defines the Commander's Intent (the objective and the constraints).
The subordinates are given the freedom to innovate and change tactics on the fly as long as they stay within those boundaries.
Often linked to servant leadership the Steward Leader emphasizes accountability and responsibility for a mission.
A steward doesn't just "serving" individuals, they are protecting the organization's goals by setting firm guardrails that ensure the team stays on track
Situational Leadership is a "Selling" or "Coaching" style.
It is Directive on the "What" for defining the goals, deadlines, and core values.
Facilitative on the "How" in providing resources and remove obstacles without micromanaging the process.
The shift for seeing tensions:
2,3 Servant Leader: Asks how the team can help in what is wanted.
5,6 Architect/Autonomous: Tells where it is going and why, sets rules then lets it go.
The dictator, the classic hierarchy to overcome the problems by anarchy (first wave 1).
An autonomous symbiotic system without hierarchy - anarchy the ultimate by ideology (7).
There are more options to organize a double diamond system becomes visisble.
Term
Tone
Core Action
2
Intent-Based
Empowering
Moves authority to where the information is.
3
Enabling
Systems-oriented
Fixes the "greenhouse" so the plants can grow.
4
Strict rule based knowledge in disciplines.
5
Orchestrator
Collaborative
Synchronizes experts without micromanaging.
6
Facilitator
Guidance-focused
Sets the goal and provides the tools to get there.
Using a manager's time-span of discretion as a measure of role complexity, Jaques developed a system for measuring executive roles.
He postulates that the boundaries in a managerial hierarchy increase logarithmically.
Symbolic verbal, thoughts used as symbols:
declarative 1 day to 3 months (Level 1), - unconnected arguments
cumulative 3 months to 1 year (Level 2), - linked arguments
serial 1 year to 2 years (Level 3), - cause/effect sequences
declarative 2 years to 5 years (Level 4), - cause/effect sequences linked & interwoven
Abstract conceptual, thoughts refer to other thoughts:
declarative 5 years to 10 years (Level 5), - unconnected arguments
cumulative 10 years to 20 years (Level 6), - linked arguments
serial 20 years to 50 years (Level 7), - cause/effect sequences
In addition to time-span of discretion, Jaques observed that at each managerial level there
is a "progression of complexity" from one level to the next higher. (Jaques 1996).
Potential Capability and Organizational Transition (Researchgate pdf: S.W. King, G.T. Solomon, K. Cason - 1998 )
Concepts that define or constrain aspects of the organisation
In the "business rules" there is a vocabulary and taxonomy that is used for the organisation.
These are essentially creating the "source code" for the organization.
The leader philosophy determines who writes these rules, how prescriptive they are, and where the decision-making power lies.
Under a Dictator hierarchy (1), the language is suppressed by a forced corporate lexicon, there can be no drift.
An anarchy (7) leads to systemic collapse because parts can no longer communicate or align (total drift).
When the discipline is unique the used language will drift by the way of leadership. That is causing unnoticed drift in boundaries.
When a discipline's language drifts, it creates a "Semantic Moat." The team becomes untouchable because no one else understands their rules.
When a specialized discipline operates with high autonomy, it naturally develops its own "patois" or technical shorthand. ❷
Intent-Based uses Language as Control, it is the primary tool for shifting power.
Drift is dangerous because if we don't mean the same thing by "Ready," the "I intend to" bridge collapses.
The vocabulary and taxonomy is treated as a Certification of Competence.
It is about proof of clarity.
Language - competence Checks ensure the boundary hasn't moved.
🔏 No autonomy claim for a process until the agreed "Business Rules/Vocabulary" is mastered.
"Shared language" is a prerequisite for "freedom," ensuring the team stays tethered to the concepts.
Drift is stopped at the source because "incorrect" language results to danger.
Pro-active decentral: the vocabulary is used as gatekeeper for prevention. ❸
Using an Enabling approach then "concept drift" is seen as Technical Debt.
If the language drifts, the "Greenhouse" walls become blurry, and the system loses efficiency.
Taxonomy is treated as tooling. Just as a broken tool is fixed, vocabulary is "refactored".
🔏 "Business rules/vocabulary" must be audited regulary ensuring it still matches reality.
Constantly updating the taxonomy by "Systems Architects" ensuring boundaries remain sharp and usable for all.
It is about system Infrastructure maintenance (Refactoring).
Pro-active because rules are continuously refactored to remain crystal clear and easy to navigate ❺
An Orchestrator treats the vocabulary as APIs, accepting that different "sections of the orchestra" (disciplines) have their own internal language.
Strictly enforces the "Sheet Music", the shared taxonomy.
Not trying to stop the team from using their own jargon internally, but set rules for Interfaces.
🔏 "When communicating outside a discipline (at the boundary), internal terms must be mapped back to the Global Taxonomy."
The Translator-in-chief, ensures that the "unique disciplines" doesn't become "isolated siloes."
Reactive because rules are enforced as checkpoints. It is about a Standard - Interfacing. ❻
The Facilitator believes that if language drifts it's because the business reality has changed.
Drift is not controlled not fought against, the drift is socialized.
🔏 New concepts are proposed and integrated into the shared glossary."
Unnoticed drift is prevented by making it explicit. It is about a Social Contract: Alignment - Consensus.
"Taxonomy Workshops" where the unique discipline explains its new terms to the others, re-drawing boundaries together.
Reactive because rules are updated after the team's internal vocabulary has evolved.
If we follow Elliott Jaques' logic, human capacity for "Time Span of Discretion" in categories it caps out at around 7 or 8 levels for global CEOs of massive nations/corporations.
When there is an connection to another layer when seeing six there are 7.
A personal Management philosophy, six categories covering the entire spectrum of Structural Control:
Level 2: Control via Power (Dictator).
Level 4: Control via Competence & Language (Intent/Enabling).
Level 5-6: Control via Harmony & Culture (Orchestrator/Facilitator).
🤔 To be short: it is a never-ending story of activities for continuous improvement.
Understanding leader paralyses by role choices
The reason "Servant Leader" is failing is that it is often a Level 6 style (Facilitator) applied to a Level 2 environment.
Without the "Architectural" or "Intent-based" foundations, servant leadership quickly collapses into Anarchy because boundaries haven't been semantically locked.
🤔 Using the words "Servant Leader" for any of the four 2,3,4,5 is just a semantic approach.
📐 RN-1.3.2 Evolving taxonomies and ontologies purpose into organising
The Philosophy and Practicality of Lean: Jit - Jidoka
Lean has a long history with a lot of misunderstandings.
There is however a duality dichotomy in the fundaments, you cannot have one without the other.
Only looking at a detailed aspect like JIT is missing what really brings value: Jidoka.
It is not just about cost-saving but it is about managing fluctuations. Fundamental Ways to Decouple Fluctuations:
The Philosophy and Practicality of Jidoka 👁️
Diving deep into the Toyota philosophy, you could see this as JIT telling you to let the material flow, and jidoka telling you when to stop the flow.
This is a bit like the Chinese philosophical concept of Ying and Yang, where seemingly opposite or contrary forces may actually be complementary.
The same applies here.
JIT encourages flow, and Jidoka encourages stops.
This seems contrary, however both help to produce more and better parts at a lower cost.
Unfortunately, JIT gets much, much more attention as it is the glamorous and positive side, whereas jidoka is often seen as all about problems and stops and other negative aspects.
Yet, both are necessary for a good production system. ⚖️
Ignoring the holistic view of the higher goal can make things worse not better.
There are several approaches in lean to focus on using JIT - Jidoka:
Focus for on the jobs by humans or machines needed for to work be done
Focus on the objects in the flow lines that are needed or a result of work
Focus on the objects that are done only once e.g. the change of flow lines
Using shared langauge in understanding the floor
Gemba walks the most honest mirror of your share (LI : Alper Ozel jamuarie 2026)
We spend hours discussing performance in meeting rooms, but the real story is written on the shopfloor.
If we're honest, most of the problems we "discover" in reviews were visible days ago at the Gemba where value is actually created. 👁️
That's why Gemba walks are not an 'Operational Ritual'; they are mirrors of 'Leadership Behaviour'.
Done right, they transform:
The way we see problems
The way teams see leadership
The speed at which we turn issues into improvements
When we walk the Gemba, we should try to look beyond "Is everything OK?".
It's also about how we lead. Thats why we should also use a parallel set of leadership lenses to guide the conversation.
Lens beyond is it OK
👐
conversation guidance
What is the process?
-A
How can we improve the process?
What is normal vs abnormal?
a2
How can we eliminate the abnormal?
What is working well?
a3
How can we move good to great?
What is not working well?
a5
Why is standard not being followed?
What is broken?
a6
How can we prevent broken things?
What is not understood?
-C
Why is it not understood?
What is creating waste?
c2
Why is it creating waste?
What is creating strain?
c3
How can we prevent strain?
What is creating unevenness?
c5
How can we smooth unevenness?
What is not visible enough?
c6
How can we make it visible?
The vocabulary taxonomy is important for persons to be able to act as a whole changing a system sensible.
👉🏾 Activities (A) to improve for better efficiency.
👉🏾 Conditions (C) to adjust for better effectiveness.
👉🏾 The worth is a key factor and needed to be not too volatile uncertain complex ambiguous.
👁️
A good Gemba walk has at least six rules:
Go with curiosity, not a checklist
Listen more than you speak
Ask "What makes your job difficult today?" and really wait for the answer
Instead of asking why we are off-target : ask 'what stops us from hitting it'
Always leave a trace of action
Connect what you see to your leadership
Nothing destroys Gemba faster than leaders who walk, nod, take photos and change nothing.
Convert at least one observation into a clear action, owner, and date and follow up visibly.
Gemba Walk isn't about walking around with a clipboard.
It's about building a culture where problems are seen, spoken about, and solved together: At the place where they happen.
Explaining The number of 6 categories in leadership approaches
I did find and see many structures mostly showing about 6-7 categories others are using a 3*3 lay-out.
For those structures never an explanations was seen how it did evolve.
For 3 dualities/dichotomies 2**3 = 8 categories are expected, one additional for coordination.
For leadership types ordering and categorisation was done, with a lot of help, by myself. ⚖️
There is simple duality to start with: hierarchy vs anarchy.
Anarchy (6) serves where no identity or filter is needed, only adaption to events is sufficient.
Hierarchy (1) serves internal identity and as a filter for wat is coming from external.
It is the simple beginning when there is a need to behave as group solving internal conflicts and acting on external threats when doing activities.
The disadvantage: this introduces, adds complexity.
Two additional dualities dichotomies: 1/ proactive vs reactive and 2/ set by a leader vs originated from the population, are adding more options at the cost of increasing complexity. ⚖️
Resulting to 4 additional approaches:
Decisions making: ideas and boundaries are set by the leaders pro-active and reactive.
Intent-Based & Enabling are proactive
Orchestrator & Facilitator are reactive
Decisions making: setting boundaries of the leader and by adapting ideas from the population.
Intent-Based & Orchestrator are by boundaries of the leader
Enabling & Facilitator adapting ideas of the subordinates subsystem
💠 There is no linear order or growth, the challenge: what is the most fittest in a situation.
Each component in a system can have a different choice for this, by that we see appearing: autonomous vs consciousness and reactive vs pro-active.
Reactive ⇆ Autonomous: It's "self-moving" logic, but lacks "self-direction."
Proactive ⇆ Conscious: mimics through prediction, but can still be "soulless".
"All models are wrong, but some are useful." (LI: Mohammad Mirkarimi 2026)
The RKG lens: Resources, Knowledge, Governance. Not a replacement for PPT, but a reframing for the world we're actually operating in.
RKG that is another one aside PPTs (Harold Leavitt) and AGIL (Talcott Parsons), they match by pattern but are in different domains.
PPTs is about (P) processes people technology. Once a diamond with structure -governance
RKGg is about (C) concepts adding purpose - goal (G). Sensible by an ontology lens
AGIL is about (R) relationships. Latency, maintaining culture & values, maps to governance
Adding the terrible complex time dimension is the last part needed for good outcomes.
PNFv is about Transformations (T). 💡 (P) past (N) now and future (F) needing vision (V)
💡 Together these four are a new one: PCRT for Process, Context, Relations, Transformations.
Combining 7s-mc-Kinsey, north-star into 9s using Siar
Reviewing the McKinsey 7s model that I modified to 9s for alignment to the SIAR model.
The structure is in 4 quadrants and 9 areas, an orthogonal and diagonal domain.
Resistance to change is imminent, adjusting a good old model into new ones difficult getting acceptance.
💸👁️
The 9s model has four edges seen as diagonals in dualities/dichotomies (dialectal):
The number of connections reduced to 3 but adaption interaction is assumed, totals 4 for each.
The coordination centre: 2 sets of 4 connections. Reducing load by what promoting autonomy.
Horizontal (middle) the operational flow. Power & Speed in the W-E line
Vertical (middle) the organisational change Location, direction progress S-N line.
In the centre Strategy, Servant leader, Shared values, includes: finance, morality/ethics purpose.
I used Style and Social intelligence because it is mainly about humans/people the connections that make processes.
Idea: not a static mindset but seeing it is a map chart helping in understanding & directing changes.
There is no absolute control predictability assumed but dynamics. 🚧
This encapsulates the activity of both a person in a designated management 'role' and also any person who brings people together to create an outcome that is necessary for the organisation.
The people 'convened' can be either or both those who have the role or skill required or, and I see this as a crucial distinction, the Emergent Task-based Relationship Network (ETRN).
ETRNs are emergent patterns that cut across all levels.
They form when formal systems cannot respond to immediate needs in whatever contexts by people.
The question is what conditions allow coherence to emerge without exhausting everyone.
Insight isn't linear progression but contextual fit: different conditions call for different approaches.
What matters is whether the architecture serves living systems, or living systems serve the architecture.
💡 👁️ A often use word: "the north-star"
It is only a navigation aid, never able to reach it as a position.
The The north star framework (LI: Timothy Timur Tiryaki 2026) is a promotion for a book.
The used graphic is interesting to review further.
Using the Past now/purpose/supply/deliver Future (horizontal) vs Doing purpose/design/values/strengths thinking (vertical) gives a perfect alignment to the SIAR and 9s model.
The four: Habits, Mindset, Vision, Goals alignment to four stable categories similar to PCRT.
Horizontal (middle) the operational flow. Power & Speed in the W-E line
Vertical (middle) the organisational change Location, direction progress S-N line.
📐 RN-1.3.3 A worth taxonomy approach to some organising sub-disciplines
What is lean realy about, 7 stages
How can we support lean systems? (M.Balle Nicolas Chartier 2025 planet lean)
Basic skills are in and of themselves not so obvious to pinpoint.
From our work on the shop floor, this is what we look for in our people: ❶Technical skills: Knowing the job and understanding how their tools interact with their materials to produce customer satisfaction (or dissatisfaction) and at what cost, also understanding that getting the job done means improving safety, quality, timing and cost of the work. ❷Seeing and listening skills: Being able to look at a situation and hear what people say about it and build a picture of the problem in their minds, beyond what they originally thought.
This sounds obvious, but it turns out that seeing and listening skills are quite rare and can always be worked on (particularly in terms of seeing safety, quality, lead-time or cost issues, as well as recognizing enthusiasm or distress in people). ❸Problem-solving skills: Being able to recognize and pinpoint a problem, then draw a functional analysis (how things are supposed to work) in order to spot where things are not working, knowing who to talk to about it and how to start looking for countermeasures is also a basic skill, although when you look at it it's not that basic and needs constant learning. ❹Teamwork skills: Some people are easy to get along with, others less so.
Keeping a team task-oriented while being aware and open to members' individual moods and personal difficulties is a skill that involves both emotional empathy (being attuned to others) and cognitive empathy (seeing what they're trying to achieve) and how to switch from one to the other, as well as knowing when to follow, when to organize, and when to lead. ❺Communication skills: Getting one's point across by expressing ideas clearly and concisely, as well as attentive listening to staff's concerns and suggestions, conveying to them the importance of their job and making sure to share changes that will affect them.
Simple conflict resolution skills, such as making sure people feel heard and checking facts before jumping to conclusions, are critical as well. ❻Looking ahead skills: This again sounds simple enough, but it is yet another basic skill people need to develop in order both to understand how things work and evaluate possible countermeasures according to impact.
The ability to anticipate problems - both on tasks and on people's reactions - is an essential part of problem awareness and managerial potential. ❼Leadership skills: Discovering opportunities, taking initiative and negotiating the support needed to get things moving is another basic-yet-difficult skill required to function within a lean framework and use its tools.
Without this skill, tools can turn into formal activities with very little value. 🎭
Of course, one can think of many more "basic" skills than this set of seven. Yet, without minimal proficiency in these skills, problem-solving and kaizen initiatives can easily turn out to be misguided or fraught with interpersonal friction.
Once the basic skills are in place, however, we can then turn to building the tool with the person - explaining how the tool works to do what - and have them practice, until we can use the tool on real-life, complex problems.
Activity for doing something paralyses, two error types
Not only "What went wrong?", but also "What didn't we do and why?" (LI: Dirk Fischer 2026)
Traditional accounting only records what happened, not what could have happened,
these errors remain invisible and invisibility shapes culture.
Over time, organisations learn an implicit lesson:
Doing nothing is safer than doing something.
Initiative becomes risky.
Caution becomes rational.
Inaction becomes the default, not because people don't care, but because the system quietly rewards it. ⏳
Ackoff distinguished between two types of errors:
Errors of commission: doing something that should not have been done
Errors of omission: failing to do something that should have been done
What's striking is how organisations react to them.
Errors of commission are visible.
They show up in reports, audits, incident logs, and post-mortems.
They are easier to point at, easier to blame, and therefore easier to punish.
Errors of omission are different.
They leave no invoice, no variance, no accounting entry.
Nothing happens and that's exactly the problem.
⌛
Ackoff argued that omission errors are often more critical than commission errors:
not investing when capacity is constrained
not addressing an obvious systemic risk
not stopping a failing policy early
not acting when weak signals were already there
The irony?
Many of the biggest failures in organisations are not caused by bold mistakes, but by missed opportunities and delayed decisions that were never tracked, reviewed, or learned from.
Ackoff's insight is uncomfortable because it shifts the question.
Using multiple frameworks that all using 6 categories
Overlaying models: eDIKWv (Ackoff, Carpenter, Bellinger, Cleveland), Dilts (Psychology), Bloom (Cognitive) and the IC (Intelligence Cycle), shows you can see that effective decision-making (Intelligence) only arises for events we perceive in the first place. ⏳
eDIKWv
Dilts
Bloom
IC
Focus - Noise
Events
Environment
Remembering
Planning & Direction
1
Context noise: Are we looking at the right sources or 'noise' from the environment?
Data
Behavior
Understanding
Collection
2
Observation noise: Are we objectively recording what is happening (behavior) without judgment?
Information
Capacities
Applying
Processing
3
System noise: Do we have the skills and tools to convert data into useful information?
Knowledge
Beliefs
Analyzing
Analysis
4
Bias noise: Is our analysis colored by (unconscious) beliefs and values?
Wisdom
Identity
Evaluating
Dissemination
5
Judgment noise: Does the advice align with who we are as an organization and our ethics?
Vision
Mission / Spiritual
Creating
Evaluation / Feedback
6
Strategic noise: Does the intelligence contribute to the "purpose" - "Why are we doing this?"
⌛
The origin of "Noise".
Combining these models reveals three critical points where information provision often goes wrong:
"Operational Gap" (Layers 1-3):
The noise often lies in technology or perception.
According to Dilts' Logical Levels, the problem is at the level of Environment or Behavior.
In the Intelligence Cycle, this means: faulty sensors or inadequate data transformations.
"Cognitive Gap" (Layer 4):
This is the level of Beliefs (Dilts) and Analysis (Bloom).
This is where the most dangerous noise arises: Confirmation Bias.
We interpret information to fit our existing beliefs, thus contaminating 'Knowledge'.
"Strategic Gap" (Layers 5-6):
Without Vision or Mission (Dilts), intelligence is meaningless.
If the top layer is missing, the IC will produce reports (Knowledge), but not result to change.
The reason: there is no connection to Identity or a higher purpose of the organization.
📐 RN-1.3.4 A tragic knowledge mismatch for real new system improvements
The Tragic mismatch in data strategy
Refering to a topic of buzz and investments: "Organizations do not need a Big Data strategy; they need a business strategy that incorporates Big Data"
Data Strategy:
Tragic Mismatch (LI: Bill Schmarzo 2020)in Data Acquisition versus Monetization Strategies. (LI: Bill Schmarzo 2020)
💸👁️
Organizations spend 100"s of millions of dollars in acquiring data as they deploy operational systems such as ERP, CRM, SCM, SFA, BFA, eCommerce, social media, mobile and now IoT.
The hype now in 2026 is AI, but essennially nothing has changed.
Then they spend even more outrageous sums of money to maintain all of the data whose most immediate benefit is regulatory, compliance and management reporting.
To exploit the unique economic value of data, organization"s need a Business Strategy that uses advanced analytics to interrogate/torture the data to uncover detailed customer, product, service and operational insights that can be used to optimize key operational processes, mitigate compliance and cyber-security risks, uncover new revenue opportunities and create a more compelling, more differentiated customer experience.
But exactly how does one accomplish this?
By focusing on becoming value-driven, not data-driven.
A topic full of confusion and frustration:
Missing the PDCA by looking for the North.
Somehow, the western world is equaling Hoshin kanri with the X-Matrix, when in reality the X-Matrix is not much more than a weird format for the same content as in the tables.
💡 👁️
Hoshin Kanri - X-matrix: a perspective to see frictions strategy vs operations.
It is well known practice used in management consultancy but a good understandable theory behind is missing.
Comments are mostly about the missing PDCA: H review cadence.
The hardest part of strategy is turning it into action. (LI: Sergio D'Amico, 2026 )
See right side.
The story is that doing this in practice is a hard challenge, many tried to use it, but the frustration by its many failures is creating frictions by themself.
Looking to the visual it is a 9 plane.
SIAR model similarity, orthogonals & diagonals, is remarkable.
Using a compass orientation: the SE edge is left empty, but is should not be empty.
This edge is the closing part where the promise meets fulfilment, vision meets realisation.
The Categories are each 4 but the cross over by duality/dichotomy adds the needed interaction.
Orthogonal lens - states
👐
diagonal lens - dynamics
Where are we and where want we to be?
duality switch
1
What is the power we want and what speed we want?
Long-term goals
A
context
2
E
KPI's for purpose
Annual objectives
B
relations
3
C
Alignment for goals
Top Priorities
D
process
4
F
Actors - Responsibilities
Accountabilities - who
G
transformations
5
H
Review cadence - PDCA closure
What is our position and are we progressing?
duality switch
6
What power do we have and what speed is made?
An adjustment to make is changing "metrics to improve" into "Actors - responsibilities" ⇆ Transformations.
From the PCRT we have "Long-term objectives" ⇆ Context, "Annual Objectives" ⇆ Relations, "Top level priorities" ⇆ Processess.
The SE corner is the one that is in fact overloaded for content, not only "metrics to improve" but also severl time gaps (cycle and vision), interdependencies, resources.
Horizontal (middle) the operational flow. Power & Speed in the W-E line
Vertical (middle) the organisational change Location, direction progress S-N line.
The critique emphasizes that the Japanese tradition requires the X-matrix to reflect individual responsibility and dynamic action rather than simply being a checklist of delegated tasks.
RN-1.4 Harsh conditions inclusiveness for going to somewhere
The classification for management, executive, information was based on technical approaches for:
Creating complex dashboards with a lot of technology details in the assumption they would result in better decisions
The experience for what is known at operational execution being ignored assuming the dashboards are the truth.
The assumption that a top down C&C command & control is the ultimate only valid target operation model.
🚧 Breaking with the far too complex dashboards.
🏢 RN-1.4.1 Redefining the how in getting decision knowledge for changes
The threat of failure and loss of an eco-system - IIT OIT ICT
For a long time the "data-driven" dogma is made similar to building to what is labelled as Datawarehouse (DWH), data lake.
Nobody is daring to challenge that there is a huge profitable market and a feeling of safety in best practices.
The similarity to a physcial warehouse should open up questions.
Is knowledge found in a storage location full of some materials?
Is what is possible changing or needed got known by looking around in a storage location?
❌ 💰
The answer is simple understandable negative, no one would make those kind of claims in the physical world.
Those with better approaches will very fast replace those.
➡ For knowledge you are going to a library that has access to scientific sources.
Details in what a warehouse, storage location could be:
👉🏾 Self-service sounds very friendly, it is a euphemism for no service.
Collecting your data, processing your data, yourself.
Get it from a location someone stored a lot you possible can use.
👉🏾 The limitation: Very likely not what you are needing .... unless
👉🏾 it is about getting measurement tooling helping in understanding.
💡 Really doing measurements is new information for IT IIT.
It can become very messy when there is no agreement on what should get measured.
Different accountabilities have their own opinion.
❓ How conflicts should get solved?
The easy way is outsourcing issues to external parties.
New viewpoints perspectives and most likely increasing tensions.
🤔 The expectation: outsourcing is cheaper and better quality is a promise without warrants.
🤔 Having no alignment between the silo's there is a growing problem easily breaking the system as a whole.
❌ These are the classic ICT battles for technology (no progress).
Have it prepared transported for you so it can processed for you.
The advantages are a well controlled environment that also is capable of handling more sensitive stuff (confidential secres).
💡 Seeing operational flow is information for IT OIT.
Breaking the classic DataWareHousing: EDWH, Data Lake - IIT OIT ICT
Process
Data lakes are where context goes to die. (LI: Adam Walls 2026)
Data model harmonisation projects that never finish.
Master data management that assumes there's one canonical truth.
ETL pipelines are built on the assumption that you know what questions you'll ask before you ask them.
You take data from a system that understands it. You strip it of its local meaning.
You transform it into some canonical schema. You dump it in a lake.
Then you spend months building pipelines to make it useful again.
By the time you've done all that, reality has moved on. The schema is already out of date. The data is already stale.
⏳ Breaking what has always been done.
The real problem is deeper than technology.
When you centralise data you're making an assumption that variation is error, different business units having different definitions is a problem to be solved.
It's not, it's information.
Different parts of your organisation define things differently for good reasons.
Regional variations reflect local markets.
Operational differences reflect how work actually gets done.
When you force everything into one schema you don't eliminate that variation.
You just push it underground where you can't see it.
So what's the alternative? ⌛ Refactoring into an experience plane.
Stop trying to unify, start federating, send the question to the systems that own the data.
Let each system answer in its own terms.
Translate the responses into a shared vocabulary and then read what the differences between those answers actually mean.
The delta between what your CMDB says and what your network traffic shows isn't an error, it's your attack surface.
The delta between what your documentation claims and what your audit logs reveal isn't a governance failure, it's your compliance reality, the gap is the information.
Pathologies by wrong expectations for data driven - dashboards
Many organizations believe they're data-driven (dashboards, KPIs, and reporting), but too often, real conversations in the boardroom are neglected.
It's undeniable that complexity is increasing both within and outside organizations.
Technology is developing faster than people can keep up. And yet, we still overinvest in systems while the organization's most important asset isn't on the balance sheet: its people.
Data-driven work doesn't start with dashboards, but with behavior and with leaders who dare to say: we use data to learn, not to settle accounts, and to empower our people.
Combining and adjusting the text from a A high level goal for what is data-driven and what the relationships are (LI: Feb. 2026 R.van den Wijngaard) and for what is usually done but doesn't help for improvements. (LI: Jan. 2026 R.Borkes )
Many organizations invest heavily in data management: data governance, data platforms, data quality, definitions, and tools.
And yet, the same problems keep recurring: delays, frustration, unreliable management information, Low adoption.
The reason is Data management doesn't fix process failures, at most, it masks them. ⚒️
The question for what is going on in the flow.
Errors and Defects: "Data - reports that gets it right first time"
Many information products fail to meet customer needs, not because the data is bad, but because the process is failing.
Process errors, interpretation errors, and operational errors
reports, dashboards, analyses that are technically correct but functionally deficient.
Data management can standardize data, it can't fix a wrong question.
Re-editing and Correction "Export the report - results to a spreadsheet"
When information is no longer usable, it is re-edited, corrected, or "touched up," often multiple times.
This is hidden waste:
Extra analysis time, Extra fine-tuning, Extra validation steps
Efficiently you fix bad products rather than prevent those bad ones.
Data management can help in reporting on processes, it can't fix wrong processes.
Control "The convincing single truth to others by a report"
There is a direct relationship between:
Low process reliability, High control pressure
More controls: reviews, checks, reconciliations, and shadow administration.
Data management facilitates control, but it is not a substitute for robust process design.
Waiting "waiting for: the right data."
Decision-making and implementation are waiting not because data is lacking, but because:
Definitions are ambiguous, ownership is unclear, processes are not synchronized
Waiting time for decisions is pure waste, and often administratively invisible.
Eis systems can help in decision making, but are no substitute for resilent descision making.
⚙️
The question for what about to achieve defined states.
Inventory The more inventory, the lower the agility.
In service and administrative processes, inventory isn't a physical pile, but rather:
data still in progress, Backlogs, open files, unfinished analyses.
Getting better insight into what are inventory items.
Data management provides insight, but it doesn't automatically optimize it.
Moving data Following blindly "best practices" external consultancy advisories
Storing data, information from operational systems into:
data lakes, data warehouses, integration layers
Seems rational, but is fragile, time-consuming, and expensive, but every transfer introduces:
delay, interpretation risk, maintenance burden
The assumption: more centralized data ⇄ less complexity.
Data duplication followed by manipulations is not a replacement for sensors.
Overprocessing Not because the organization needs it, but because it can.
Spending more time on data than strictly necessary:
extra analyses, extra dashboards, extra levels of detail
Data management sometimes encourages precision where simplicity suffices.
"Underutilizing Data"
Perhaps the most costly mistake: Data with high intrinsic value that:
is not linked, is not interpreted, is not used in decision-making
Not due to a lack of technology, but due to a lack of context, ownership, and direction.
The inconvenient truth is that Data Management optimizes what already exists, it doesn't transform anything.
True value only arises when data management becomes subordinate to:
The question shouldn't be "Is our data management system right?" , but: ⚖️"What waste are we perpetuating with perfect data management?"
When seeing "waiting for: the right data." and "Underutilizing Data" as the same that is a connection point than we have the first three (1,2,3) a describing negative in what could be "power" and the last three (5,6,7) as negative ones for "speed".
🏢 RN-1.4.2 Searching for the how in getting knowledge for improvements
Connecting ICT - administration to agile lean, information flow.
Having the flow lines approach for what is similar to work in mass the same kind (OIT), the work of changing flow lines is more similart to one-off projects. 🎭 When a project shop is better in place, why not copy this approach for ICT?
This perspective to administration work moving the papers around is Operational IT (OIT) supported by Administrative IT (AIT) and managed using informational IT (IIT). Flow lines (👓)
are often the best and most organized approach to establish a value stream.
The "easiest" one is an unstructured approach.
The processes are still arranged in sequence; however, there is no fixed signal when to start processing at those.
During the process the errors in them to be corrected in the flow.
💡 The reinvention of common flow patterns using the information flow (OIT) similar as a physicial assembly line.
Aside the the standard operational activities there are administrative processes associated to them.
The difference between OIT and AIT is difficult to see the used technology is indenticial, but when reviewing the goal of the activity should make the difference clear. ⚠️ Information processes are different to physical ones that use physical objects.
Information is easily duplicated Creating copies gives some feeling of independency from others.
That feeling has disadvantages costs: losing awareness in what the value chain is.
Technology ICT buzz hide the real issues, ignore problem signal in the value chain.
Information object components are often not complete in the needed OIT value assembly chain.
Missing the physical and administrative verification (AIT) it can go easily into chaotic confusing working practices.
Failures mistakes to blame to the machine (computer says no") where the value process chain is the real problem", but not noticed (IIT).
DataWareHousing, Information flow based - EDWH 4.0.
Repositioning the Datawarehouse as part of an operational flow makes more sense than the solely puprose in informing some management.
This shift has a big impact because it forces to see all information as a whole and not by isolated compoents or silos.
A compliancy gap getting a solution: 💡
The are two important phase shifts to be made for a very different approach in building up this enterprise information data ware house.
👉🏾 All consumers and providers valid for: Archive, Operations, ML operations
👉🏾 Every information container must have a clear ownership.
All information having a shared understanding in the area of its usage.
A generic data model for relations between all information elements - information containers.
Safety accountablity is an inseparatable property of the system.
In a figure: 🔏 Getting A phase shift into integration and safety is hard.
🏢 RN-1.4.3 The interaction of four forces to improvements by knowledge
First contact in abstractions to enterprise engineering
My first contact to abstract thinking was to:
Understanding and Modelling Business Processes with DEMO (Researchgate: J.Dietz 1999)
It didn't get into something practical when first seen long ago but it did trigger the opening for many abstracted perspectives.
DEMO (Dynamic Essential Modelling of Organizations) is a methodology for modelling, (re)designing and (re)engineering organizations.
A way of thinking about organization and technology that has originated from a deep dissatisfaction with current ways of thinking about information systems and business processes.
These current ways of thinking fail to explain coherently and precisely how organization and ICT (Information and Communication Technology) are interrelated.
Its theoretical basis draws on three scientific sources of inspiration:
Habermas' Communicative Action Theory, Stamper's Semiotic Ladder and Bunge's Ontology.
The core notion is the OER-transaction, which is a recurrent pattern of communication and action.
The per-forma of a piece of information is the effect on the relationship between the communicating subjects, caused by communicating the thought.
It is determined by both the illocution and the proposition of the communicative action, and is further dependent on the current norms and values in the shared culture of the communicating subjects.
Every piece of information has a forma, meaning that it has some perceivable structure carried in some physical substance.
This structure must be recognizable as being an expression in some 'language', which is the case if the forma con-forms to the syntactical rules of that language
The in-forma is the meaning of the forma, the reference to some Universe of Discourse, as defined by the semantics of the language.
The aspect in-forma also includes the pragmatic rules of the language, like the choice of the right or best forma to express some in-forma in specific circumstances
The distinction between the three aspects per-forma, in-forma, and forma, gives rise to the distinction of three corresponding levels at which information in an organization has to be managed: the essential level, the informational level, and the documental level respectively. ❶ The three layers in components OIT AIT IIT
Alle attention in Demo went to the flow of the primary operational activities, it is neglecting the glossary taxonomy and other parts.
In Demo it is shown as the smallest part at the top of an triangle.
Keeping the colours similar I reverted the shape.
forma: AIT primary administrative support processes (green)
in-forma IIT: the measurements and information for activities and administration (blue).
There is far more in Demo e.g. the Request-Result cycle, a cycle in 4 stages.
Thew position of where to start I change to the bottom-right so the material flow is left to right.
❷Positioning of 4 of them around a centre.
⚖️ It are these ideas that bought me into the SIAR model.
That model is that far abstracted it can get different meanings depending on the used context.
🤔 Having understandable information for involved parties is what should be learned from although different perspectives are possible.
The change to achieve this is one of cultural attitudes. That is a top down strategical influence and bottom for changing activities.
🤔 Aside these three/four for the primary processes there are similar ones for other processes.
❸In a halfway line - braking point - boundary
⚖️ It are these between each layer, in between segments, where the most important information to measure can be found.
When these issues are seen, discussed and accepted as problem states for requirements to work on there is start for shared goals and collaboration.
Using data collectors is an indication of designing useful sensors.
Real questions for the real problems to solve:
Alignment frictions in primary operational processes.
Alignment frictions in primary and other processes.
Strategy and identity frictions requiring repositioning.
The resistance for change in information processing
Changing a background in promoting agile to the narrowed setting of reporting analytics as the data management paradigm.
A presentation for
skills for business analysts (Scott Ambler feb 2026) Classic IIT only Collecting and processing for management (BI).
See figure right side.
EIS/MIS systems:
➡ Goal informing managers to decisions (IIT)
➡ Shadow usage solving broking value stream processes (OIT, AIT)
Chaotic complexity No sensors but data duplications into what is felt as sensors.
See figure right side.
Data profiling:
➡ Acting on operational data
➡ seeing files interactions
➡ Understanding data streams
It is ambiguous to see references to Agile e.g. "The Agile data Warehouse design" based on answering: Who, What, When, Where, How many, Why, How, the use of Obeya and scrum but all being used in practices as it has always been done.
Still the long chaotic chain of extracts, data lineage, on duplicated data and no usage of sensors for metrics. 🔏 Getting into a real fundamental change is hard.
🏢 RN-1.4.4 Alignment by three domain types to four time perspectives
Change data - Transformations
the modern data stack (Xebia blog feb 2026 )
Before the rise of the "Modern Data Stack," the landscape was dominated by Relational Databases, primarily designed to provide key figures and trends.
Think: customer counts, product sales, and margin evolution.
A central IT team was responsible for this Relational Database product, typically procured from an relational database vendor and deployed on-premise.
This was the (enterprise) Data Warehouse, the primary source for reporting and dashboarding.
This setup had its limitations, data users faced:
Storage limitations resulting into discarding vast amounts of information due to datawarehouse capacity constraints.
Limited data type support: no support for images, video, audio (NoSql buzz). The use of e.g. CSV, JSON is missing the semantics of the information.
Slow innovation: Difficulties in using other technologies, other data sources or APIs usage.
Painful upgrades: Changing the technology and information stack are never ending projects.
But this approach also offered significant benefits:
Clearly defined schemas: Target tables are well-defined and structured, based on logical and physical data models.
Source-to-target mapping: Collaboration enforced with source system engineers and domain experts to agree on data usage, quality expectations, and delivery schedules.
ETL tooling: Tools provided features like data lineage, data validation, business logic libraries, and data cataloging.
This contributes directly to the issues many data teams face today: data trustworthiness concerns, lack of data ownership, a heavy data-ops burden, and difficulty in understanding data meaning and origin.
👐 There are two sets of 3 that are complementary.
The upper three are activities for realisations, the bottom three is about abstractions in enabling realisations.
In that perspective the flow that is searched for is horizontal left to right.
(Re)instate Data Management Practices, it's time to redefine Data Management for this new data reality.
To overcome these challenges, we need to strategically incorporate Data Management practices into our current way of working and technology stacks.
Data Management is a broad topic with dozens of sub-categories.
However, you should select subcategories based on your main challenges and the opportunities to gain the most benefit.
These subcategories can be organizational (data strategy, processes, operating model), technical (metadata store, data quality engine, data lineage, automated governance workflows) or knowledge management focused (capturing knowledge, documenting output, creating data models).
Metadata is the foundation: rich and accurate metadata is critical explainability, bias detection, and ensuring responsibilities.
Semantic metadata includes definitions and explanations.
Security metadata classifies data and indicates sensitivity.
Using Organizational Model: Accountability for data assets should be on the business side.
A data contract is an agreement between data producers and consumers.
A well-organized Data Portfolio Management prioritized based on business value, is crucial to bring focus and maximize impact.
👐 There are two interacting sets of 4 that are complementary.
Data quality capabilities allow you to continuously monitor data and receive early warnings.
Adapting to circumstances for data modelling practices is focussing on the data entities that are most crucial to your business model and context.
Providing data lineage across the entire chain will give you explainability, about the origin of data, the source of data issues, the impact of changes etc
Managing reference data reduces variety and increases recognizability.
When seeing "Data Portfolio Management" and "reference data" as the same that is a connection point than we have the first three (1,2,3) a describing negative in what could be "power" and the last three (5,6,7) as negative ones for "speed".
Evaluation of the slow evolving Data warehouse
The evlving approach for a DWH, data lake experience plane.
Looking back for seein the future.
A tale of two architectures - Kimball vs Inmon
At the mid 80's came Bill Inmon's best selling book: "Building The Data Warehouse".
The industry accepted definition of a data warehouse: "a subject oriented, integrated, non volatile, time variant collection of data for management's decision making".
But there was another related architecture that arose in roughly the same time frame.
That architecture is the one that can be called the "Kimball" architecture, it is the Kimball architecture that is associated with Red Brick Systems. 👁️ The Current state: DWH 2.0
The DW 2.0 architecture represents the evolving architecture for data warehouse.
It contains the best features of the Inmon architecture and the Kimball architecture can be combined very adroitly.
DW 2.0 represents a long term architectural blueprint to meet the needs of modern corporations and modern organizations.
A figure See right side.
Remarkable, those 4 levels:
very current
current
less than current
older
are a reflection of what happens in organisations processing the flows.
Three perspectives, this is the operational one:
The now
Technology, near future
Vision far future
🔏
Two important phase shifts are needed for a move of DWH 2.0 into DWH 4.0
RN-1.5 Good conditions enjoying for going to somewhere
Changing the classification in information for management, executives, into an approach that is based on:
Accepting a level of uncertainty unpredictability avoiding the technology details. Only showing basics to navigation.
Back to an alignment for what is known at operational execution as important information source for decisions.
Allowing for a diversity in approaches for the different levels by autonomous authority by a polyarchy.
🚧 creating a culture of sharing purpose by effective communication.
The geographical structure and type of competing dashboards
The categories C3,R4,C4,R4 in the centre are from the DTF framework. 🕦
The details of the DTF have to be explained, but we are needing these parts now before we can explain those.
When going to describe the who what and how of dashboard context is needed for what is seen, how to expect interactions and why by who should act. Sensory organs act as biological sensors that detect environmental stimuli and convert them into neural signals for the brain.
The confusing with using the word sense is it has two meanings.
🔰Sensory organs: eyes, ears, nose, tongue (taste), skin (touch) and
⏲ It could be also: "feel" "good judgement", "awareness"
The meaning of "good judgement" "awareness" is what the intention to solve for the usage with a dashboard is.
Before that and that is the context to start with for a dashboard is when it is about collecting the data, information.
The standard layout of dashboards by using two circulation rings and a centre.
For the centre it is the connections to the driver, coordinator, manager, executive.
The meaning of C3,R4,C4,R4 is:
It lives between the S3 ⇄ S4 ⇄ S5 hinge.
VSM meta-regulation core is the place where identity, intelligence, and control are continuously reconciled.
S.Beer sometimes calls this the "algedonic loop nexus". ⚠️
The usual (wrong) claim about dashboards is that organisations say:
"This is an operational dashboard." (S1 / P)
"This is a management dashboard." (S3 / R-P)
"This is a strategic dashboard." (S4 / C-T)
So they try to place a dashboard on a node, owned by a role, owned by a layer, owned by a function.
This implies a Dashboard = position in the structure, that's a myth.
The conceptual breakpoint
Dashboards are sensors that are not logical parts components of systems but solely added for observation.
This gives a complete other aspect in separation for OT (operational information processing) and IT (informational information processing).
Pair
👐
Meaning
R3 - C3
present-time judge of the system
R4 - C4
future-oriented judge of the system
R3 - C4
Authority that organises meaning
C3 - R4
Meaning that regulates authority
The change, dashboards are not on:
C, not on R, not on P, not on T,
not on edges, not on halfways,
not owned by any vertex.
◎
In VSM language: Dashboards belong to the algedonic + intelligence channels, not to S1, S2, S3, S4, or S5 individually.
They are part of the nervous system.
👁️
Dashboards sit inside the circulation rings, intersect vertical and horizontal flows, are influenced by all, but governed only by the centre (C3/C4/R3/R4).
They are organs of sensing, seeing, not organs of doing, they behave as:
Observation surfaces, not action points.
The geograpical structure and type of competing dashboards
The generic lay-out of a functional dashboard for a system as a whole
What is confusing in a system is there a multiple dashboards with a different goal that interact.
Operational Judgment / Legitimacy-in-Action
Strategic Judgment / Legitimacy-of-Becoming
👐👁️ Sensor for the operations, to see: Power - Speed
See visual at the right.
Measurements for:
⚒ Power What is put into the systems (left side)
⚙ SpeedThe results of the systems (right side)
👐👁️ Sensor for tactical goals , to see: Location- Direction:
See visual at the left, measurements for all:
⚒ Location Asked to change of existing systems (bottom) with their history.
⚙ Direction Desired results of changed systems (top) in assumed expectations.
Ignoring the near and far future time horizon for a dashboard is reducing it to a simple structure.
Only the almost now and a little bit history.
Looking ahead for the direction &
using mirrors are sufficient
When controlling something it is necessary to:
👓 Knowing were it is heading to.
⚙ Able to adjust speed and direction.
✅ Verifying all is working correctly.
🎭 Discuss destinations, goals.
🎯 Verify achieved destinations, goals.
It is basically similar like using a car.
The orientation is made vertical because it is sharing the same centre of the operational.
There are two different dashboards at the same time but for a different time horizon and for different perspectives.
👐👁️ Sensor for strategic goals , to see: Worth: values, ethics, purpose
These are unspoken or assumed.
Note: there are no❗additional instruments for observations needed in a simple situation.
🧪 RN-1.5.2 Using sensory for novice knowledge improvement of the whole
The geograpical location and type of the several dashboards
I introduced four categories: Service Desk, Functional management, Portfolio, Board to get a response for understanding in the meaning of dashboards.
The result is understandable, explainable, usable but it is breaking a lot of assumptioms.
Centres are always places of: legitimacy, arbitration, framing, sensemaking, they are the S3/S5 hinge zones (VSM).
These dashboards are reflexive instruments of the system, not managerial artefacts.
The centre is where vertical, ideology change, and horizontal, execution change, intersect without time-shift.
It is:
Judgment in the present about structure and authority.
Not action, not vision, but meta-regulation.
They do not belong to anyone but to the meta-layer that observes all of them.
That's why they sit in "ghost positions", they are not inside the system, they are how the system becomes aware of itself.
The common classification: Operations, tactics, strategy assumes it would be simple, it is not.
Seeing observing from the outside is different than the experiencing from the inside.
"The now" perspective
Technology oriented
Future perspective
Service Desk (S1),
Floor, Operations (S1)
Floor, Operations (S1)
Functional management (S3)
Portfolio, Tactics (S4)
Engineering (S3)
Portfolio, Tactics (S3)
Architects (S4)
Board, Strategy(S5)
Board, Strategy (S5)
Board-architect concepts(S4)
Board context (S5)
The perspective from the outside is in conflict with the inside.
Every dashboard has a split for inside perspectives.
Most organisations put dashboards in:
IT, in PMO, in operations, in Finance,
which forces: C ➡ P shortcuts, role capture, political metrics, local optimisation.
The proposed model for dashboards although there are likely 9 not 3 enforces a huge conceptual correction:
✅ Observation ➡ Judgment ➡ Commitment ➡ Action,
❌ not:Action ➡ Reporting ➡ Excuses.
How did this emerge and how is it emerging?
See figure right side
A diamond in fractals
Combining two double diamonds:
One that is dominated by Context, the operational perspective.
The relational aspects are present to correct (C3-R3) horizontal early.
One that is dominated by Relations, the change perspective.
The context aspects are present to correct (R4-C4) vertical early.
There is another diamond in this for worth (R5/C5) in a third dimension.
Changing is having a history, past, now and future for a fourth dimension.
The geograpical location and type of the several dashboards
The generic lay-out of a functional dashboard for a system as a whole
What is confusing in a system is there a multiple dashboards with a different goal that interact.
Operational Judgment / Legitimacy-in-Action ⚒ the now (horizontal).
Strategic Judgment / Legitimacy-of-Becoming ⚙ near future (vertical)
👐👁️ The Combined double dashboard: Power - Speed and Location- Direction:
See visual at the left.
Measurements for:
⚒ Power What is put into the systems (left side)
⚙ SpeedThe results of the systems (right side)
See visual at the right that adds measurements for:
⚒ Location Asked to change of existing systems (bottom) with their history.
⚙ Direction Desired results of changed systems (top) in assumed expectations.
➡complicated situations, instruments:
location awareness &
setting a direction &
planning the route,
are becoming indispensable.
When controlling something it is necessary to:
👓 Knowing were it is heading to.
⚙ Able to adjust speed and direction.
✅ Verifying all is working correctly.
🎭 Discuss destinations, goals.
🎯 Verify achieved destinations, goals.
Commbining the two competing ones to a whole.
The near future cannot be ignored anymore.
The far future is an indispensable part of this but left out in the operational usage views.
Trying to answer everything, manyfold views:
💰 more effort (costly)
👉🏾 new questions
❓ No real endsituation
🚧 continious evolvement
👐👁️ Sensor for strategic goals , to see: Worth: values, ethics, purpose:
These are unspoken or assumed.
Note: there are additional instruments ❗ for observations needed in a complicated situation.
The simple easy car dashboard could endup in an airplane cockpit and still mising the core business goals to improve
🧪 RN-1.5.3 Observed pathologies caused by wrong dashboard usage
The different types of centres
In the four categories: Service Desk, Functional management, Portfolio, Board there are understandable roles responsibilities accountabilities.
These however are flattened removing for any worth.
A provocative approach for worth where none of these are in commonly in place (ViSM fractal included).
Service desk Instance: the worth is enabling the operations at the floor.
Activities for this first line could be:
(S1) Having needed technology equipment available for usage.
(S2) Having the needed people available to act in operation.
(S3) Available people are educated and trained according to needed activities.
(S4) The culture of involved people is in support of a shared goal.
Functional - component: the worth is delivering the product/service externally.
Activities for Functional management could be:
(S1) An understandable effective planning for operational activities.
(S3) Having the knowledge of how the product-service is to be created.
(S4) The qualities for the product-service are effectively validated.
(S5) A product/service delivery culture in satisfying known external customer needs.
Engineering - physical: The "how" Knowledge for product/service internally is the worth.
Activities for this could be:
(S1) Continuous evolvement for effective & efficient instructions to operations.
(S3) Adapting external knowledge relevant to the product-service in the portfolio.
(S4) Changing the product-service by changed external knowledge portfolio adjustments.
(S5) A product/service delivery culture in satisfying assumed external customer needs.
Architect - Logic: Boundaries knowledge in "what" for the product/service is the worth.
Activities for this could be:
(S1) Coordination into alignment for activities to physical, component and instance.
(S3) Knowledge of how all interactions are cooperating into the goals around the whole.
(S4) Coordination into alignment for changes to physical, component and instance.
(S5) A product/service change culture in satisfying yet unknown external customer needs.
Board - concepts: Knowledge worth of the "why" internally culture for product/service.
Activities for this could be:
(S1) Maintaining an understandable shared language in the whole usable for alignment.
(S3) Setting boundaries for the shared language allowing specialisations in components.
(S4) New vocabularies taxonomies for innovation in the portfolio (product/service).
(S5) A product/service portfolio culture in adapating external customer needs.
Board - context: Knowledge worth of the "why" externally identity for product/service.
Actvities for this could be:
(S1) Setting boundaries for what the organisation internally is able to do.
(S3) Promoting paths of changes in divarication of components to innovated portfolios.
(S4) Reward alignment for the whole to what is seen as worth by anybody's contribution.
(S5) A product/service portfolio mindset in innovating choices for external customer needs.
✅
Financial aspects are setting boundaries and are the enablers in this.
They are not the worth that is intended here, that is including ethics and purpose
Common pathologies by short-cuts bypasses
Board, Functional, Portfolio, and Service Desk fail today because they connect to execution paths directly and bypass the C3-R3 / C4-R4 judgment core that alone can turn data into legitimate action.
Summary of common mismatches:
Domain
Should anchor in
Usually plugs into
Structural error
Board
C4-R4 ➡ C3-R3
R4 ➡ P 4/3
Authority without meaning
Functional Mgmt
C3-R3 ➡ P3
P3 ➡ T3
Optimisation without legitimacy
Portfolio Mgmt
C4-R4 ➡ T4
T4 ➡ P4
Logistics without identity
Service Desk
P1 ➡ C3-R3 ➡ T1
P1 ➡ T1
Reaction without judgment
Details of common mismatches:
Board plugs into R4 without C4
becomes a command organ instead of judgment.
The Board should live at: C4 ➡ R4 ➡ C3 ➡ R3
Meaning:
absorb meaning (C4), judge direction (R4),
translate to present policy (C3), legitimise execution (R3).
So the Board is primarily C4-R4 dominant, with a bridge to C3-R3.
💣⚠️
What happens today is that boards usually plug into:
bypass: R4 ➡ P4 (authority straight to plans)
or worse: R4 ➡ P3 (authority straight into operations).
They skip C4 sensemaking and C3 coherence, so they act as: "Decide ➡ impose ➡ monitor."
Instead of: "Understand ➡ judge ➡ legitimise."
Failure mode:
Strategy becomes slogans. Dashboards become compliance theatre.
Risk is misread as performance. Identity fractures from execution.
❌🎭
VSM: System-5 collapses into System-3 control. DTF: R4 bypasses C4 and C3.
FM plugs into P3 without R3
becomes technocratic instead of legitimate
Functional management (FM) should live at: C3 ➡ R3 ➡ P3 ➡ T3.
Meaning:
understand policy (C3), gain legitimacy (R3),
coordinate practice (P3), transform flow (T3).
Functional Management is anchored in C3-R3.
💣⚠️
What happens today is they usually plug into:
P3 ➡ T3 directly.
They manage: resources, capacity, KPIs, processes, without passing through:
judgment ➡ legitimacy ➡ meaning.
Functional management becomes: "Optimise what exists." not: "Judge what should exist."
Failure mode
Local optimisation. Metric gaming.
Political prioritisation. Shadow hierarchies.
❌🎭
VSM: System-3 without System-3*. DTF: P3 acts without R3.
Portfolio plugs into T4 without C4
becomes logistics instead of intelligence.
Portfolio Management should live at: C4 ➡ R4 ➡ T4 ➡ P4.
Meaning:
understand future meaning (C4), judge investment legitimacy (R4),
transform options (T4), shape practices (P4).
Portfolio Management is anchored in C4-R4.
💣⚠️
What happens today is they usually plug into:
T4 ➡ P4 directly
Without: narrative coherence, ideological alignment, legitimacy of choice, it focuses on:
funding mechanics, capacity planning,
roadmaps, governance gates.
Portfolio becomes: "Which projects fit capacity?" instead of: "Which futures fit identity?".
Failure mode:
Zombie projects. Innovation theatre.
Overloaded change. Strategy drift.
❌🎭
VSM: System-4 reduced to program management. DTF: T4 acts without C4 and R4.
Service Desk plugs into P1 without C3
becomes reactive instead of reflexive.
Service Desk should live at: P1 ➡ C3 ➡ R3 ➡ T1
Meaning:
Service Desk is anchored via C3-R3.
💣⚠️
What happens is they usually plug into:
P1 ➡ T1
Without: systemic interpretation, legitimacy judgment.
Service Desk becomes: "Close the ticket.", following: SLAs, routing, escalation, instead of: "Understand the disturbance."
Failure mode:
Incident churn. Symptom fixing.
Trust erosion. Hidden systemic risk.
In VSM: System-1 reflex without System-3 sense.
In dtf terms: P1 acts without C3-R3.
A "Meaning Filter" for the time-stream
Worth" is the sensor that detects when the system is vibrating but not moving.
By placing "Worth" between Who and When, you have effectively created a "Meaning Filter" for the time-stream.
In a standard dashboard, the "Who" does a task at a certain "When," and the dashboard records a "Success."
Imagine the dashboard not as a flat list, but as a coordinate system:
X-Axis: Timeline, Speed
Y-Axis: Capabilities Structure
Z-Axis The Depth in Worth
👐👁️
If the Z-axis Worth is zero, the "Speed" and "Stucture" create a flat, 2D line.
This is the "Incomplete" technological view.
But when "Worth" is active, the line becomes a 3D Volume.
🧪 RN-1.5.4 Completing observations by worth: values, ethics, purpose
A system in T2.5 Illusion Collapse
The T2.5 trap, "The Illusion of Progress" happens when the Horizontal Speed (Leavitt's Power) is disconnected from the Vertical Direction (Parsons' Goal).
Detection: Divergence Analysis
The Signal: Your dashboard shows a high frequency of "When" (lots of commits, meetings, or deployments).
The "Worth" Check: If the "Worth" metric (the social/economic value defined in RN-3) is flat or declining while the "When" frequency is rising, you have a Divergence.
The Warning: This is the 4D system telling you that the "Who" is busy "simulating" progress to satisfy the dashboard, but the "Direction" is lost.
"Worth" as the Integration (I) Sensor 👐👁️
In Parsons' AGIL, Integration is what keeps the parts of the system working together.
By extending Zachman to include "Worth," it is building a sensor for Integration.
If a task has high technical "Speed" but low "Worth," it means the task is Isolated.
It might be a perfect "Task" (Leavitt), but it has no "Social Construct" (RN-3) value.
Safety by Design: This prevents the "Flattening" because the dashboard won't allow a task to be "Green" just because it's finished; it must also be "Weighted" by its worth to the environment.
The Rule of Safety: Any process where the volume (Worth vs Speed) is shrinking while the surface area (Who vs When) is expanding is a system in T2.5 Collapse.
It means you are hiring more people and doing more things to produce less value.
The adjustment of "Why" to "Which" becomes the steering wheel.
The new question to ask:
"Which goal did we drop?"
or "Which component of the environment did we ignore?"
A system in T3.5 Optimization Collapse
At T3.5, the dashboard usually looks "Perfectly Green" in terms of Speed (R3) and Direction (R4), but there is a nagging sense of "Worthlessness" because the system is optimizing for its own internal logic rather than the environment's needs. 👐👁️
To reveal a T3.5 Optimization Trap, we have to move past
"Are we doing things right?" and ask
"Are we doing the right systemic things?"
Specific R5/C5 questions to program into your dashboard sensors:
The R5 Complementarity Questions
Focus: How the internal parts relate to the whole.
The "Bottleneck Export" Check: "Does the high Speed (R3) of this specific component (C3) actually improve the total Worth (R5) of the value stream, or is it just moving the 'waste' faster to the next station?"
Why this reveals T3.5: T3.5 loves local optimization. If you are a hero in your silo but the customer still waits, your "Worth" is a lie.
The "Structural Harmony" Check: "Does our current Direction (R4) require us to ignore the Environment (C5) in order to maintain our internal Structure (Leavitt)?"
Why this reveals T3.5: This catches when a team is so focused on "doing Agile perfectly" (Task/Structure) that they stop listening to the market (Goal/Worth).
The C5 Contextual Dependency Questions
Focus: How the system relates to its environment.
The "Parasite vs. Symbiont" Check: "If the external Environment (C5) changed its definition of Worth tomorrow, how much of our current Direction (R4) would become instantly obsolete?
Why this reveals T3.5: T3.5 systems are often "Brittle." They are highly tuned to a world that no longer exists.
This question exposes the "Gravity Well" of old goals.
The "Feedback Decay" Check: "Which specific Environmental Part (Extension) is providing the 'Worth' signal for this task, and is that signal actually reaching the 'Who' (Leavitt) performing the work?
Why this reveals T3.5: If the "Who" is just following a "Which" (Direction) without seeing the "Worth," they are trapped in a mechanical loop.
👐👁️
The "Dashboard Alarm" Logic: The Worth-to-Speed Ratio
To make this visual, you can create a Worth-to-Speed (R5/R3) index.
High Speed / Low Worth: The dashboard should turn Purple (The Color of the T3.5 Trap).
It tells: "We are racing, but we are currently a parasite on the organization's resources.
"Low Speed / High Worth: The dashboard turns Yellow.
It says: "We have found the right thing, but we lack the Power/Speed (Leavitt) to deliver it."
By defining these questions in Ontology, it ensures that the viablity by Design is baked into the very definition of a "Task."
You are saying that a Task does not exist unless it has a Worth (R5) attribute attached to it.
This prevents the Flattening because the dashboard cannot render a 2D line (Speed/Direction) without a Z-axis (Worth).
If there is no Worth, there is no line.
The "Incomplete" parts are essentially empty sockets waiting for these R5 "Systemic Consciousness" sensors to be plugged in. ✅
The simplicitiy of a dashboard hiding the complexity of the system as whole.
RN-1.6 Preparing in unclear conditions for going to somewhere
Changing the classification in information for management, executives, into an approach that is based on:
Accepting a level of uncertainty unpredictability avoiding the technology details. Only showing basics to navigation.
Back to an alignment for what is known at operational execution as important information source for decisions.
Allowing for a diversity in approaches for the different levels by autonomous authority by a polyarchy.
🚧 Going for a lean way of management, executive, operations and change information.
🏗️ RN-1.6.1 Desire: engage stakeholders in the work of solving problems
A recurring story in the search of methodlogies and practices I
The OECD Observatory of Public Sector Innovation (OPSI) puts innovation at the heart of government.
Key challenges:
Cultural barriers and norms to Culture of openness and innovation/
Lack of feedback mechanisms and learning loops
Understanding and distributing the costs and benefits of cross-border efforts
Undeveloped ecosystems to clearly defined roles, Scaling up experiments
This is a complete different starting point, the top down but it is searching for the fractals. 🔰
OPSI innovation workshop :
What is the purpose of innovation, anyway?
How much of what types of innovation should be supported?
Are current activities sufficient or adequately supported?
How to do re-balance an innovation portfolio?
The OPSI mindset for types of innovation, see right side.
This one is aligned to the SIAR model orientation.
Stakeholders in this context is about civilians in a society and the political leaders.
A publication by this OECD-OPSI institute:
Achieving Cross Border Government Innovation (researchgate Oecd opsi 2021 )
The foreword is by Geof Mulgan for collective intelligence.
OPSI is a global forum for public sector innovation.
In a time of increasing complexity, rapidly changing demands and considerable fiscal pressures, governments need to understand, test and embed new ways of doing things.
Over the last few decades innovation in the public sector has entered the mainstream in the process becoming better organised, better funded and better understood.
But such acceptance of innovation has also brought complications, in particularly regarding the scope of the challenges facing innovators, many of which extend across borders.
OPSI's colleagues in the OECD Policy Coherence for Sustainable Development Goals division (PCSDG) and the EC Joint Research Centre have developed a conceptual framework for analysing transboundary interrelationships in the context of the 2030 Agenda. 🎭
A second challenge is how to institutionalise this work.
It is not too difficult to engage people in consultations across borders, and not all that hard to connect innovators through clubs and networks.
But transforming engagement into action can be trickier.
It is particularly hard to share data, especially if it includes personal identifiers.
It is also hard to get multiple governments to agree to create joint budgets, collaborative teams and shared accountability, even though these are often prerequisites to achieving significant impacts.
For the activities in a visual by the OPSI mindset, see right side.
This image is not made to be related to that of the innovation diamond, but doing that seeing them both is in line what I got into working bottom-up to get better understanding in the many existing framework and trying to combine those into something more generic.
A recurring story in the search of methodlogies and practices II
Systems, systems thinking, opens systems and what does Lean have to do with it?
From scalability and flexibility to resilience (LI: klaus Beulker, M.Balle 2025)
and How can we support lean systems? ( M.Balle, 2025) 🔰
We live in a world that is often described using the acronym VUCA.
Too often, the term sounds like a fashionable label, sometimes like an excuse, and occasionally like an intellectual shortcut.
Yet it captures a reality that many industrial organizations experience daily: markets change faster than planning cycles, supply chains break unexpectedly, customer requirements shift abruptly, and decisions must be made under conditions that resist prediction or repetition.
Stakeholders in this context is about anyone in the society but the scope is narrowed to a more specific topic so you you have workers consumers leaders intern of an organisation, leader extern of the organisations anybody that is somehow involved. ❶Scaling: Taylor and the Logic of Industrial Modernity
With industrialization came a fundamental question: how can human labor be organized in a way that makes it reproducible, controllable, and scalable?
The answer formulated by Frederick Winslow Taylor was as radical as it was effective.
By decomposing work into elementary tasks, standardizing execution, and separating thinking from doing, productivity could be increased and replicated at scale.
Taylorism was not an ideological aberration; it was a functional response to scarcity, scarcity of skilled labor, time, and transparency.
Scaling became the dominant competitive lever because environmental conditions favored optimization: relatively stable markets, long product life cycles, and limited variability.
Deviation was considered disturbance.
Control was considered rationality.
❷Flexibility: Ohno and the Expansion of the Efficiency Logic
This logic reached its limits where variability became the norm.
Taiichi Ohno worked under conditions fundamentally different from those of Western mass production: low volumes, high product variety, and severe resource constraints.
The response was not to abandon efficiency, but to redefine it.
Lean Management, often misunderstood as a cost-cutting or efficiency program, was, from the outset, a different concept of stability.
Stability through flow rather than buffers. Flexibility through standardization rather than ad hoc adjustments. Learning not as an exception, but as an integral part of daily work.
Concepts such as pull systems, jidoka, or mixed-model lines were not answers to chaos, but to structured variability.
Lean expanded the performance dimension: efficiency and adaptability. Uncertainty was present, but it remained manageable. ❸Lean Revisited - and Some Misconceptions
Lean can be condensed into a small number of statements, statements that are frequently misunderstood:
Lean does not aim at processes, but at problem-solving capability.
Gemba is not a place, but a principle of knowledge creation.
Problem solving is not a toolbox, but training of judgment.
Problem solving serves the systematic reduction of misconception.
Leadership does not design solutions, but learning conditions.
The term misconception is central here.
It does not refer to missing data or insufficient methods, but to flawed mental models: premature explanations, seemingly obvious causes, managerial certainties that have never been tested at the gemba.
In this sense, problem solving is less about eliminating causes than about working on false assumptions. ❹
Not Every Problem Is Worth Learning From.
Especially in complex environments, engineer-to-order contexts, project businesses, or global supply networks, specific causes often do not repeat.
Many disruptions are context-dependent, unique, or not meaningfully reproducible.
Applying classical root-cause logic indiscriminately in such settings overwhelms the organization.
Lean was never about analyzing everything, on the contrary, learning is costly.
It requires time, attention, and cognitive effort.
Resilient organizations are not those that analyze more, but those that choose more carefully.
Problem solving thus becomes an investment decision.
A small fraction of events is deliberately selected to challenge mental models, sharpen decision logic, and develop collective judgment.
The remainder is fixed, and consciously not analyzed further. ❺
Resilience as the Litmus Test of Lean
From this perspective, resilience takes on a different meaning, it is not a new goal, not an additional program, not another maturity model.
It is the litmus test of whether Lean has been understood and practiced as a learning system.
Where Lean has been reduced to efficiency, resilience appears as a supplement.
Where Lean has been understood as an architecture for learning and decision-making, resilience is not a surprise, but a consequence.
Put differently: resilience is not what an organization claims to have. It is what becomes visible when things go wrong. 🎭Final Thought:
Perhaps we do not need a successor to Taylor or Ohno. Perhaps the real challenge is not to formulate a new paradigm, but to take an existing one seriously. Lean is widespread, but rarely exhausted. Resilience, then, is less a new promise than a mirror. It reflects how seriously an organization takes learning, leadership, and uncertainty.
🏗️ RN-1.6.2 Sensory organs are creating segregated information flows
The Fractal focus for knowledge management
The shape mindset mediation innovation is for understanding
sentences containing: "the problem" and/or "the purpose"
requiring understanding the grammar that defines those sentences.
We need the understand more technical what the language in systems is.
Seven distinct categories define the invariant operators of sense-making and organization. 🎭
Purpose (POSIWID) and "the problem" are not additional distinctions, but emergent constructs produced when these operators are enacted through recurring 3*3 sense- act- reflect patterns. Combining:
For the grammar we end up in 6-7 distinctions although we are not aware of those.
In the grammar there are several perspectives of disinctions types for different purposes
Purpose (POSIWID) and "the problem" do not exist independently; they are constructed through the interaction of the 7 distinctions.
The 3*3 forms the sentence, express:
Horizontal: Sense, Act, Reflect
Vertical : Context, Process, Outcome
🎭
Information processing applying grammar for using sentences, the third wave
The operators are scale-free
The 3*3 is a projection
The loop creates meaning
Meaning retroactively defines purpose and problem
The common challenge with all complexities is that this is full of dualities - dichotomies.
A duality dichotomy in information: operational vs informational.
Combining the operational information (OIT) flow and the informational information flow (IIT).
The common mindset is seeing only the divide in operational and administration for the flow and ignoring the command & control.
The Siar model reveals there are two sets of four in cooperation and competition.
In this one the red/green/blue segments are representing OIT and the containers between those what is communicated to IIT.
See figure right side. 🔰 IIT in this describes what is going on at boundaries.
Solving perspective gaps between silos in the organisation is one of the goals of IIT
Having aligned information by involved parties it is avoiding different versions of the truth for the whole although there are different versions of the truth by different perspectives.
Reducing complexity to have only a minimum for what is needed by IIT should be a shared goal.
Support the values stream the operational flow as the whole by all should be the goal. 💡 Breaking the culture of "best practices" into good practice.
Although this looks simple this is very hard challenge caused by misunderstanding and hidden personal interests.
The real disruptive change is: to have dedicated sensors to develop and nurture in innovations.
This is avoiding the "best practice" of creating copies of the OIT assuming those copies are having somewhere the searched IIT.
It is more easy, comfortable, consolidating all kind of information to a central managed (bi analytics) data lake, data ware house, claiming that that would contain all the needed IIT.
layers in purpose for data management: Selfservice - Managed
dual-operating-system (Vladimir Riecicky januari 2026)
Let's reflect on the Kotter's Dual Operating System. Kotter proposes that organizations should run two systems in parallel:
Hierarchy: For stability, efficiency, reliability, operations
Network: For innovation, change, agility, strategic initiatives
So, the company has one system to run the business, and another to change the business. This model is grounded in the key assumption that hierarchy is fundamentally still needed, but it cannot deal with fast change alone.
This works, but it is a permanent organizational workaround out of the Kotter's underlying belief: We know the hierarchy can't change so, let's build a second organization next to it that can.
One could argue this is not transformation but organizational life support - designing a second nervous system because the first one is too slow. Impressive engineering but also a quiet confession that the original anatomy is wrong.
This is not agility but institutionalized schizophrenia - leadership's job is to constantly translate between two worlds that should never have been separated.
How to R.I.P.E. in Organizational Change:
R - Review & Assess Readiness: Determine the current maturity of the organization and its capacity for change to identify strengths and weaknesses.
I - Identify Needs & Goals: Establish clear, smart goals (specific, measurable, attractive, relevant, scheduled) for the transformation.
P - Prepare the Culture: Focus on employee engagement, manage resistance by involving stakeholders early, and build a sense of urgency.
E - Execute & Embed: Start with small, high-impact tasks (quick wins), provide training, and embed new behaviors into performance management.
layers in purpose for data management: Selfservice - Managed
The Difference Between Working Hard and Winning (LI: K.Kohls januari 2026)
We often talk about how productive we are, or how productive our organization is, but productivity only measures activity.
It tells you how busy people are, not whether the system is moving toward its goal.
Performance is different.
Performance is measured by throughput: the rate at which the system moves toward its goal.
You can increase productivity and still reduce performance:
producing the wrong things faster
improving non-constraints
optimizing locally while the system stalls
This is why throughput matters. It measures results, not effort.
Before launching any improvement, transformation, or KPI: ask two basic questions:
What is the goal of the system?
How do we measure progress toward that goal?
If you can't answer those clearly, productivity metrics will quietly pull behavior in the wrong direction.
Activity feels good, but throughput tells the truth.
Start every improvement journey with that clarity.
🏗️ RN-1.6.3 Dashboards simplified: the sensory organs when using ICT
Safety first by design, a practical case in air aviation
For information processing there are weird things in maturity for safety.
Just compare it to safety using airplanes. The safety for operating and safety for maintenance are at a high level.
Just for operating a plane, the pilot.
IMSAFE Checklist Acronym Explained
Ultimately, the safety of a flight is only as good as its weakest link.
With a significant amount of accidents caused by pilot error every year, pilots must ensure they are physically and mentally fit to fly.
In aviation, safety is the first, second and third priority.
That's one of the things I learned early during my pilots training, and it was repeated often.
After obtaining my license, it's still a constant focus.
The first thing on the checklist I use before even driving to the airport:
Illness, Medication (involuntary drugs), Stress
Alcohol (voluntary drugs), Fatigue, Emotion
I.M.S.A.F.E. , if any of these rais a flag, I don't fly. 🔰
Although flying, aviations, is a very new activity for travelling the speed of development is far beyond that of information technology.
What we can learn from those:
There is a strict separation in development, maintenance and operations for flying.
Regulations and regulators are strict separated from the flying technology constructors and operational executioners.
Double closed loops in all kind of activities and places. These are never avoided in the argument of simplification.
All procedures are simplified for the job to fulfil. The simplification a continous process.
Procedures that normally will not happened are documented and well verified & exercised.
🚧
It is weird to see in the approach for information processing technology usage the state of art is kept similar all years.
There is only a change in made in common available technology: the database, big data, cloud, AI.
However asking for goals risks and impacts in information processing results into reactions of boards showing lack of understanding.
Changing the way of informing.
Dashboards are a common challenge in the discipline of ICT (Information Communication Technology).
It was the first environment with a clear question for management information in an intangible world, management information systems (MIS EIS).
It failed by not getting the information that was really behind that question correct understood. 👁️
Going through a lot of theory it got sensible that is hard to get that correct by differencees in perspectives of involved stakeholders for the same at the same momment.
Using sensors for what is going on, locations & direction (IIT) , and that of the operational flow Power & speed, (OIT) are two different aspects in ICT that should not be mixed up.
There can be no single version of the truth because the truth is changing continuously by changed conditions changed goals changed values.
A dashboard is the compass, strategy is the roadmap.
Data, information, are the coordinates that determine where you truly stand.
The Digital Boardroom brings this together in a single management overview:
societal challenges, strategic goals, clear KPIs
reliable master data management and concrete decisions
A linear ordering for six categories.
See figure right side.
👁️
The Digital Boardroom is not a tool, it is a new way of governing.
For CDO's, this means:
from data projects to management direction,
from individual initiatives to demonstrably in control.
For directors, this means:
less discussion about figures, more focus on choices,
better accountability to society and oversight.
changing the ordering to a nine plane.
Accountablities in the X-matrix centralised.
See figure right side.
Only the strategical representation is shown (vertical) not the operations (horizontal)
The Ansoff matrix choices far future
dual-operating-system (LI: Sangbum Ro 2026)
The real values of strategic frameworks is not that they give you answers, but that they expand your cognitive horizon.
Good frameworks help leaders step back and explore broader options and possibilities in strategic planning.
Once you've done the necessary research on your industry and taken an honest look at your firm's capabilities, it's time to make deliberate choices about future moves.
Of course, this analysis should always be conducted with a clear understanding of your firm's capabilities and the opportunities and threats in the market, not based on revenue potential alone. 🔰
These outline four distinct paths.
Market penetration focuses on existing products in existing markets, with the goal of winning greater share from customers you already serve.
Product development involves introducing new products to existing markets, creating additional value for customers you already understand.
Market development applies existing products to new markets, such as new geographies, segments.
Diversification combines new products + new markets. It is ambitious and "risky" option.
Often requiring new capabilities and strong execution.
In practice, frameworks like this are most useful when they help leaders structure conversations and make clearer strategic trade-offs.
🚧⚠
There is in this framework the assumption that changing is the root cause for risk.
However not changing not able to adapt no innovation can be more risky than changing.
When others change improve adapt then keeping it as always is the sure dead-end.
🤔 There must be some more than these too easy presented trade-off choices.
🏗️ RN-1.6.4 Double closed loop usage presented by layered dashboards
Dashboard paralyses, information overload
Harnessing Less for More: The Art of Effective Dashboards (Medium: Andre Vinicius Rocha Silva 2024)
The Conundrum of Complexity:
Data-rich dashboards are no doubt the nerve centers for decision-makers.
When developing one, after you've completed the data extraction, cleansing, formatting, and ensuring all best practices, the next natural step seems to be presenting all these data on your dashboard for user access. 🔰
However, an overabundance of information can lead to analysis paralysis.
It can be particularly problematic in critical situations where timely decisions are essential, as the inability to act swiftly can lead to more significant issues than if a decision had been made promptly.
When time is of the essence and stakes are life-altering, simplicity in design is not just aesthetic, it's ethical.
Twin anti-pole of desing failure:
Doing precisely what the users asks vs ...
assuming you know what's best and ignoring the user.
Initial interactions should be exploratory, encouraging open-ended feedback without the influence of a pre-defined design. ⚠️🕳
When feasible, engaging with a diverse range of users frequently and early on can yield rich, varied insights that shape a more robust final product.
With the motto "less is more," we embarked on an analytical odyssey to distill which metrics were mission-critical.
The guiding simple question:
"Does this data save time, enhance decision-making, or improve patient care?"
If the answer is ambiguous, the data is scrapped.
This relentless pursuit of simplicity is your beacon.
IIT paralyses by best practices overload, restructuring into simplicity
There are three types of dashboards defined each covering a different persective.
In a 2D dashboard, these three are usually smashed together, which is why managers often trade Worth for Speed.
In the 3D/4D model, you can see if the Speed is actually "complementary" to direction and Worth.
Each level provides a constraint on the one below it, this is viablity of the system:
Worth (R5/C5) constrains Direction (R4/C4): You shouldn't steer (R4) toward a direction that has no systemic worth (R5).
Direction (R4/C4) constrains Speed (R3/C3): You shouldn't go fast (R3) if you are pointed in the wrong direction (R4).
P (Process) describes the historical trace of R3 to R4 to R5 movement.
T (Transformation) is the "Leap" required to move the system from a R3 state (just functioning) to an R5 state (integrated worth).
The three types of dashboards:
Dashboard
DTF
Zachman alignment
Dimensional role
Power and Speed
R3/C3
How, Who, When
Functional power / Limits How the machine performs within its boundaries.
Location and Directions
R4/C4
What, Where, Which
worthiness power / Embeddedness Who is steering and where they sit in the system.
Worth and Friction
R5/C5
Worth, Environment
Complementarity / Dependency How the system provides value to the environment.
IIT paralyses by best practices overload, back to the principles
A change in the meaning of ICT Information Communication Technology.
The context ICT into Inspiration Creativity Talent. (E.Loopstra 2025)
Inspiration: The spark or the problem that creates the need for a solution. It's about vision and seeing possibilities where others see obstacles.
Creativity: The process of devising that solution. Without creativity, technology is just a soulless tool; creativity makes it unique and effective.
Talent: The skill and expertise to translate inspiration and creativity into tangible results. It's about the craftsmanship of the creator.
When mixing these three elements, you get powerful outcomes for any creative project:
Inspiration + Creativity = Visionary Ideas
Where a spark meets a method to create something entirely new.
Creativity + Talent = High-Quality Execution
Ability for creative concepts and build those with professional skill.
Talent + Inspiration = Purposeful Innovation
Skills to solve real-world problems that matter.
Where traditional ICT is often perceived as cold or distant, "Inspiration, Creativity & Talent" brings the human connection back.
In a world where AI (Artificial Intelligence) is taking over technical tasks, these three human qualities will become the most important differentiators.
Focus Area
I
C
T
Education
Inquiry
Creating
Thinking
Technology Nerd
Information
Communication
Technology
Human centric
Inspiration
Creativity
Talent
Personal Growth
Intention
Connection
Tenacity
Data/Business
Insight
Collaboration
Trust
Social Impact
Impact
Community
Transformation
Shifting from "Technology" to "Talent" highlights that human ingenuity is the most important component.
In educational settings, this helps students see ICT not just as a "computer class," but as a way to develop 21st-century skills like critical thinking and problem-solving.
RN-2 The impact of uncertainty to information processing
RN-2.1 Reframing the thinking for decision making
This is a different path on information processing supporting for governance and informed understandable decisions.
This all started with an assumption in certainty for knowledge management, collective intelligence.
Decisions however are made in assumptions and uncertainty.
What kind of thinking is used & for what decisions
The relationship in decisions transformations to Zarf Jabes
Abstraction adjustments in this level to Zarf Jabes Jabsa
The almost green area for this abstraction level in decisions
🧱 RN-2.1.1 Distinctions containing tensions in grammar
A culture in understanding defining concepts
Before we argue about systems, we need to define definitions (LI: A Abduhl 2026)
We use different kinds of definitions for different purposes, without noticing. We often conflate:
Lexical definitions - describe how a term is commonly used
Theoretical definitions - specify how a term functions within a theory
Stipulative definitions - declare meaning for a specific context ("for this project")
Operational definitions - define meaning through measurement or execution
Persuasive definitions - frame meaning to influence behaviour or belief
Precising definitions - narrow an existing concept to reduce ambiguity "across contexts"
Meta-Semantic Definitions - how meanings themselves are constructed, selected, or transformed across contexts.
👐
It doesn't define a term, it defines the rules for defining.
Think of it as the governance layer for meaning.
What this 7th layer does:
Integrates multiple definition types into a coherent semantic strategy
Specifies criteria for a definition type depending on: purpose, audience or constraints
Establishes meta-rules for meaning stability vs. adaptability
Defines how meanings evolve across time, culture, or system layers
Supports interoperability across domains (e.g., legal, technical, cultural, operational)
This is exactly the kind of layer I use in JABES: a semantic governance layer.
This seventh layer is what allows to build fractal, recursive, multi-perspective governance models, my home turf.
The first six:
none are wrong in isolation.
But when we slide between them unconsciously or tell lay audiences "there are no such things as systems", we create confusion and end up talking past each other.
If we want to coordinate action, we need to get past arguing about "the right definition" and be explicit about purpose.
Here I suggest a "precising" definition of a system. It doesn't try to resolve tensions, it surfaces them. 👐
"A system is a set of interconnected elements whose relationships, constraints, and structure generate emergent behaviours different from those of the isolated parts, which may be recursively nested across multiple scales. It is distinguished by boundaries (physical or conceptual), operates through feedback loops, and may maintain identity through regulation and adaptation - though its definition and boundaries are ultimately determined by the observer's perspective and intent."
What is happening is:
System rules, understanding, taxonomy in the sender and receiver context that should get aligned for an understanding, based on R.Ross business rules getting a grammar.
The word grammar is a construct for operations in languages making up sentences for a meaning in communication.
That holds an observer dependency in the communication using sentences.
A culture in understanding defining concepts
The continuation of A.Abduhl for his goal was in doing a more precise defintion on system-2 in ViSM (viable systems).
The tension is about inside outside thinking in systems thinking. 👁
It's a deliberate synthesis, grounded in the several traditions:
Interconnection & emergence ➡ Ludwig von Bertalanffy
Feedback & regulation ➡ Wiener, Ashby
Viability & identity ➡ Beer
Observer, purpose, boundary choice ➡ Checkland, Heinz von Foerster
Moving beyond a false dichotomies 👁
(Systems) thinking oscillates between two positions:
"Reality is out there": objective entities waiting to be discovered.
"Reality is socially constructed": - Systems are narratives shaped by perspective and purpose.
Both are incomplete.
This tension didn't start with systems thinking.
As Kant showed, reality is real, but never encountered unmediated.
More recently, Iain McGilchrist makes the same move from a different angle:
"Reality is real": but our access to it depends on how we attend to it.
That maps directly to systems thinking:
feedback and constraint push back
boundaries and purposes are chosen.
As Checkland put it: systems are formulated, not found.
The irony: the debate itself is a systems failure.
The endless swing between: "systems are out there" and "systems are constructed", is itself a system oscillation.
In VSM, this is a System 2 failure to damp oscillation between competing logics. 👐
My precising definition is a System 2 move:
it doesn't eliminate the tension, it holds it in place long enough for coordination, without demanding false consensus.
This is the essence of the Cynefin framework in phase shifts.
Hard systems thinkers worry that acknowledging observer dependence makes everything subjective.
Soft systems thinkers worry that acknowledging structure smuggles objectivism back in.
What's crucial is recognising that systems practice requires both:
Observer-independence in structure and dynamics feedback loops, constraints, and causal relationships that persist regardless of observation (Ashby, Forrester, Wiener etc).
Observer-dependence in framing and relevance boundaries, purposes, and what counts as "the system" are always brought forth by an observer in relation to intent (Checkland, HvF, Ulrich etc).
The synthesis isn't new either. See Gerald Midgley's boundary critique, Michael Jackson's CST and more recently Derek Cabrera's DSRP.
Without holding both sides, I'm not sure there's a meaningful debate at all e.g appreciating single vs multiple causation, or structure vs interpretation.
The Dialectical Thought Form Framework (DTF)
Thinking dialectal for underpinning at decisions the source is limited in names and history it is a recent development.
This is far beyond the personal comfort zone but LLM usage is helpful.
A LLM can see the DTF as grammar and its usage as sentences.
There is a lot of management and philosophical content accessible for meaningful knowledge.
The names to start with: 👁️
Otto Laske is a multidisciplinary consultant, coach, teacher, and scholar in the social sciences, focused on human development and organizational transformation.
Jan De Visch is an organization psychologist, executive professor, and facilitator with extensive experience managing organizational development and change processes.
Key contributions:
CDF (Constructive Developmental Framework): a developmental model for adult growth that helps consultants, coaches, and leaders assess and nurture complexity-capable thinking.
DTF (Dialectical Thought Form Framework): , tools for critical facilitation and boosting individual cognitive development.
Dialectical Thought Form Framework (DTF) is aimed at understanding and nurturing reasoning complexity: how people structure thought as they handle context, change, contradiction, and transformation.
The counterpart of this page 6x6systemslean (Shape design Zarf Jabes Jabsa) asked to verify in overlap and differences.
The result of that is interesting:
It is not descriptive systems thinking (formal-logical), it is meta-structural systems thinking.
This is the same territory Laske calls dialectical, DTF is operating in the same cognitive space.
Key indicators (DTF markers) present throughout 6x6systemslean:
Reference frames instead of models
Fractals instead of hierarchies
Dualities instead of binaries
Cycles instead of linear causality
Architecture of viewpoints instead of single perspectives
The overlap is deep, but unevenly distributed across DTF categories.
Important boundaries, There are also clear non-overlaps, which is healthy.
What DTF has that my ideas does not aim to do:
Assess individual cognitive development
Distinguish developmental levels
Score or profile reasoning complexity
What 6x6systemslean has that DTF does not
Normative design intent
Architectural completeness
Operational guidance for enterprise/system design
DTF is diagnostic, 6x6systemslean is generative, they are complementary, not redundant.
The SIAR model operationalizes dialectical thinking at the system-design level, while DTF explicates the cognitive forms required to meaningfully operate such a model. 👐
This is an opening to connect what has developed into very soft-thinking back to more hard-thinking in seeking the balance.
🧱 RN-2.1.2 Using DTF as one of the perspectives aside Zarf Jabes etc.
The Dialectical Thought Form Framework (DTF) summary
Dialectical Thought Form Framework (DTF) consists of 4 categories (quadrants), each with 7 Thought Forms (TFs), for a total of 28.
The standard IDM / Laske formulation, wording can vary slightly across publications and trainings, but the structure is stable.
Relationship (R) - Mutual influence and structure
Focus: interdependence, coordination, and structural relations.
How elements relate in structure or function.
Process (P) - How things unfold over time
Focus: movement, sequencing, emergence, and ongoing activity.
Dynamics and changes over time.
There are for each categories:
Relationship (R)
👐
Process (P)
R1 - Relationship as mutual influence
P1 - Process as a whole
R2 - Structural relationship
P2 - Process phases
R3 - Functional relationship
P3 - Process directionality
R4 - Power / asymmetry
P4 - Process rhythm / pace
R5 - Complementarity
P5 - Process interaction
R6 - Tension / contradiction
P6 - Process interruption
R7 - Relational integration
P7 - Process stabilization
Context (C) - Conditions and embedding (multiple contexts in layering)
Focus: environment, systems, constraints, and enabling conditions.
Situating phenomena in conditions and constraints.
Transformation (T) - Change of form
Focus: qualitative change, emergence of the new, negation of the old.
Deep change or integration beyond categories.
There are for each categories:
Context (C)
👐
Transformation (T)
C1 - Context as container
T1 - Emergence
C2 - Contextual limits / boundaries
T2 - Transformation of function
C3 - Contextual resources
T3 - Transformation of structure
C4 - Contextual embeddedness
T4 - Breakdown / negation
C5 - Contextual dependency
T5 - Reorganization
C6 - Contextual shift
T6 - Developmental leap
C7 - Contextual layering
T7 - Integration at a higher level
Each class, Process (P), Context (C), Relationship (R) and Transformation (T) captures a way of thinking, from seeing events in relation to conditions, diagnosing interdependencies, and dealing with contradictions, to achieving integrative transformation.
This is typically used:
In developmental assessments (cognitive interviewing),
For team dialogue and facilitation (Laske & De Visch),
To distinguish formal-logical from dialectical thinking,
As a developmental map, not a competency checklist.
This is a generic thinking approach that is usable on groups of persons and systems acting is a similar way.
That is different boundary scope than DTF has got growing in.
Using six catergories to do learning dialectual thinking.
The text is derived for a course offering.
Increasingly, the issues on which the survival of our civilization depends are 'wicked' in the sense of being more complex than logical thinking alone can make sense of and deal with.
Needed is not only systemic and holistic but dialectical thinking to achieve critical realism.
Dialectical thinking has a long tradition both in Western and Eastern philosophy but, although renewed through the Frankfurt School and more recently Roy Bhaskar, has not yet begun to penetrate cultural discourse in a practically effective way.
👉🏾
We can observe the absence of dialectical thinking in daily life as much as in the scientific and philosophical literature.
It is one of the benefits of the practicum to let participants viscerally experience that, and in what way, logical thinking, although a prerequisite of dialectical thinking, is potentially also the greatest hindrance to dialectical thinking because of its lack of a concept of negativity.
To speak with Roy Bhaskar, dialectical thinking requires "thinking the coincidence of distinctions" that logical thinking is so good at making, being characterized by "fluidity around the hard core of absence" (that is, negativity, or what is missing or not yet there).
👉🏾
For thinkers unaware of the limitations of logical thinking, dialectical thinking is a many-faced beast which to tame requires building up in oneself new modes of listening, analysis, self- and other-reflection,
the ability to generate thought-form based questions, and
making explicit what is implicit or
absent in a person's or group's real-time thinking.
These components are best apprehended and exercised in dialogue with members of a group led by a DTF-schooled mentor/facilitator.
There is a nice duality dichotomy in this, the course design is offered as a lineair path.
For the content what it is about it is about non-linearity.
The practicum takes the following six-prong approach:
Foundations of Dialectic:
Understand moments of dialectic and classes of thought forms and their intrinsic linkages as the underpinnings of a theory of knowledge.
Structured dialogue and communication:
Learn how to use moments of dialectic when trying to understand a speaker's subject matter and issues, or when aiming to speak or writing clearly.
(Developmental) listening and self-reflection
Learn to reflect on the thought form structure of what is being said by a person or an entire group in real time
Text analysis:
Learn to understand the conceptual structure of a text (incl. an interview text) in terms of moments of dialectic and their associated thought forms as indicators of optimal thought complexity.
Question & problem generation and formulation
Learn how to formulate cogent and visionary questions (including to yourself), and give feedback based on moments of dialectic and their associated thought forms
Critical facilitation
Learn how to assist others in understanding what they are un-reflectedly saying, thinking, or intending
Acquiring these six, mutually supportive capabilities takes time and patience with oneself and others.
It goes far beyond 'skill training' since participants need to engage in revolutionizing their listening, way of thinking, structure of self-reflection, and attention to others' mental process, something that logical thinkers for whom the real world is "out there" (not "in here") are not accustomed to.
The four dtf types in a wheel conform what was done at Zarf, see right side.
👁️
For a limiting scope context in dialectual thinking usage, I am not:
The interest is at: Architectural, Systemic, Comparative (Zarf Jabes Cynefin), artifacts: models, texts, strategies, frameworks.
Working at the level of: Architectural, Systemic, and Comparative sensemaking across frameworks and artifacts.
That is DTF-informed systems design, Second-order observation, not diagnosis. 💰
I use DTF concepts as an interpretive lens to examine the developmental affordances, constraints, and ceilings of architectural and systemic artifacts, and to compare frameworks across Zachman and Cynefin domains."
The Zarf Jabes approach triangulates:
Zachman ➡ structural completeness
Cynefin ➡ epistemic domain sensitivity
DTF ➡ developmental affordance
Cutler ➡ problem framing and reframing
🔏
DTF is one lens, not the authority this avoids: Reductionism, Overreach, Pseudo-psychometrics.
The repeating Autonomous repetitions for limited number in distinctions
Feeling a repeating pattern of ~6 distinctions in a dimension.
The question is why this happens, the generative LLM answer: 🔏
A dimension is only "adequately articulated" when it can express internal tension, differentiation, and integration without self-contradiction.
To do that, you need at least:
A grounding distinction
Differentiation
Relational mediation
Tension / contradiction
Negation or boundary
Re-integration
That already gets you to 6.
The 7th is not additiv , it is closure at a higher level.
This convergence shows up again and again.
"framework-ish"
complete but navigable
10+ encyclopedic
Too few (LE 4)
Optimal (6-7)
Too many (GE 9)
Oversimplified
Expressive
Redundant
No contradiction
Tension + resolution
Loss of salience
Binary thinking
Dialectical movement
Semantic inflation
The search for the optimal number of distinctions.
A simplified answer.
Zarf Jabes started from:
Governance, Organization, Civic systems, Practice
Knowledge system(KS), Technology for KS, Usage of KS, Structure in KS
And ended up with:
~6-7 stable distinctions per dimension, repeatedly, across roles, scales, and contexts.
🔏
That is not coincidence, it is a sign of working against the same cognitive constraints that DTF formalizes.
The "6-7 distinctions per dimension" rule is not a design choice but an empirically and dialectically grounded minimum required for stable, non-redundant articulation of complex meaning.
🧱 RN-2.1.3 Reframing the SIAR model sing dialectal abstractions
The cycle dialectal: Sense - Interpret - Act - Reflect
What is not done: replace SIAR with DTF labels, instead:
Each SIAR phase is expressed as a dominant dialectical move
Using DTF categories + typical T/P/R/C operations
In language that still supports action and facilitation
Think of this as SIAR with its cognitive mechanics exposed. 👁️ S , Sense Situate the situation within its enabling and constraining contexts.
DTF language (dominant: Context + Relationship):
Establish system boundaries (C1, C2)
Identify contextual dependencies and conditions (C5)
Surface relevant actors, viewpoints, and roles (R1, R2)
Key dialectical move: "What contextual conditions make this situation what it is?"
This is not data gathering , it is situated sense-making. 👁️ I, Interpret Structure meaning by relating elements, perspectives, and tensions.
DTF language ((dominant: Relationship)):
Identify structural and functional relationships (R2, R3)
Surface tensions, contradictions, and misalignments (R6)
Integrate multiple viewpoints into provisional coherence (R7)
Key dialectical move: "How do these elements mutually shape and constrain one another?"
Interpretation is relational structuring, not explanation. 👁️ A , Act Intervene in ongoing processes to test and influence system behavior.
DTF language (dominant: Process):
Select intervention points in unfolding processes (P2, P5)
Acknowledge timing, rhythm, and flow (P3, P4)
Expect and monitor interruptions and side effects (P6)
Key dialectical move: "Where and how can we intervene in the process as it unfolds?"
Action is processual engagement, not execution of a plan. 👁️ R , Reflect Transform frames, assumptions, and structures based on what emerges.
DTF language (dominant: Transformation):
Negate or let go of inadequate assumptions (T4)
Recognize emergent patterns and new coherence (T1)
Integrate learning at a higher systemic level (T7)
Key dialectical move: "What must change in how we frame the system for the next cycle?"
Reflection is structural reframing, not evaluation.
The cycle grammar to sentence: Sense - Interpret - Act - Reflect
The implied cycle, one of the variations of a time dimension. ⚖️
Important:
SIAR traverses C ➡ R ➡ P ➡ T in every cycle, that is full dialectical movement, not partial.
These are grammar operations in the dialectal context.
Using that into sentences a similar structure is generated in a different meaning, different intention.
In practice: it situates contexts, structures relations, intervenes in processes, and transforms frames, whether or not this is made explicit.
SIAR
Plain wording
Dominant DTF move
Sense
Situate the situation
Contextualization (C)
Interpret
Structure meaning
Relational integration (R)
Act
Intervene in process
Process engagement (P)
Reflect
Reframe the system
Transformation (T)
The mapping of the reframed SIAR to DTF dimensions, see table.
🤔 The Transformation is dialectical different, but it is the interpret "relational integration" that becomes the object when projected in a 9-plane.
⚖️
The search is for content lay-outs to explain this.
It should be a dialectical closure that fulfils the following requirements.
It is minimal but complete in lower-bound articulation:
9 cells = no redundancy
Each word does one job
No word can be removed without breaking the loop
No word needs explanation if used in practice
🔰 We sense a problem, execute an intervention, observe effects, and eventually reflect on what the system's real purpose is.
Sense
Act
Reflect
Context
Problem
Mandate
Reframe
Process
Signal
Execute
Learn
Outcome
Effect
Stabilize
Purpose
❶
What does change:
Reflection becomes non-optional
Learning must alter frames, not just actions
"Action" is understood as process intervention, not task completion
This makes SIAR robust under complexity.
An alternative using other words but same grammar.
Aim, plan, and execution are not dimensions but sentences spoken across the Context- Process- Outcome and Sense- Act- Reflect grammar, with execution necessarily occupying the center.
Sense
Act
Reflect
Context
Aim
Govern
Adjust
Process
Plan
Execute
Improve
Outcome
Assess
Achieve
Purpose
❷
These are other logical levels:
Aim / Arrange / Achieve ➡ intent-to-result flow
Plan / Organize / Execute ➡ process enactment
Governance / Management / Operations ➡ structural loci of action
Some alternatives would fail (important) because they would break dialectical closure.
Governance / Management / Operations as rows: collapse context into structure.
Aim / Plan / Achieve as columns: turn learning into linear control.
⚠ Same words are used in different locations for a different intended meaning.
This breaks the idea, assumption, of a shared language would always help in solving misunderstandings.
🧱 RN-2.1.4 Diagnosing dialectal the broken system in decision making
The agentic AI shift int the process of decisions
Why Human-Centric Design Breaks in Agentic Systems and What to Do Instead (LI: J.Lowgren 2025)
🤔
Most teams still design like the human is always in charge. That worked when software was a tool in a human's hand.
It breaks when software is an actor with its own perception, its own objectives, and the right to act.
The result is familiar; a chatbot that sounds empathetic but never escalates, a logistics optimiser that saves fuel and blows delivery windows, a fraud detector that performs well at baseline and collapses during a surge.
🚧 None of that is a bug. It is design that started in the wrong place.
The Agentic Double Diamond begins with inversion; cognitive design from inside the agent's world.
It continues with authopy; system design that encodes data, activation, and governance.
The goal of this: autonomy is trusted and traceable.
At the centre sit roles and cognition; the explicit boundary between what agents do and what people must decide.
🤔 Teams that work this way waste less time apologising for their systems.
They spend more time improving them. That is the difference between software that merely runs and software that behaves.
That is the difference between pace and regret.
Agentic Governances a redirected book
The LI posts were dialectical more rich than this book that is the result.
Making Intelligence Trustworthy (Zeaware -J.Lowgren 2025 Note: the form is hidden when strict tracepreventation is activated)
This is not a book about the present state of AI.
It is about the threshold we have just crossed, the shift from automation to autonomy, from decision rules to decision flows, from governance as control to governance as coordination. The work ahead is not to restrain intelligence but to ensure it remains account-able as it learns, negotiates, and changes shape.
🤔 The paradigm unfolds through three companion volumes, each viewing the same transformation from a different altitude:
Agentic System Design
Explains how to design agentic systems that scale. It embeds governance at the core of design, turning alignment, constraint, and accountability into fea-tures, not afterthoughts.
Agentic Governance
Explores how to govern when those systems come alive. It focuses on the space between agents, on the relations, dependencies, and emergent logics that arise when autonomy multiplies.
Agentic Architecture
Unites the two. It defines the infrastructure, operating system, and coordination fabric that allow intelligent ecosystems to operate coherently at enterprise scale.
Together they form the Agentic Trilogy; a framework for building, govern-ing, and evolving intelligent systems that can explain themselves, adapt respon-sibly, and sustain human intent at machine speed.
Key points:
Crises no longer stem from single failures but from interactions be-tween many agents.
Traditional governance collapses because it is too slow, too narrow, and too retrospective.
The governance gap is widening - official systems move too slowly, shadow systems too fast.
Agentic Governance is about governing the flows between agents, not just the rules within them.
Leaders must design for resilience, not prediction
The devlopment of governance and leadership
The dialectal thinking framework is mentioning leadership, working at leaders.
The question is how that is related to a strategy of governance strategy.
See the document at:
Human Developmental Processes as Key to Creating Impactful Leadership (researchgate Graham Boyd Ottol Laske 2018)
The analysis for holacracy:
In the Shared Leadership document, Laske is operating squarely inside the Constructive Developmental / DTF frame.
Key characteristics of his position:
Leadership is shared among persons
Authority is distributed across roles, not concentrated in individuals
Governance is still fundamentally human-cognitive
Structures (holacracy, circles, roles) are supports for human sense-making
When Laske references holacracy, he is not endorsing it as a governance solution per se, he uses it as an example of role-based, non-hierarchical authority distribution that requires sufficient developmental capacity to function.
In DTF terms, Laske's shared leadership presupposes:
at least T3 (role differentiation without identity fusion),
emergent T4 (ability to reflect on systems of meaning),
but governance is still enacted by humans.
💡
Holacracy is therefore treated as a container for shared leadership, not as an autonomous governance mechanism. (operates primarily T3 ➡ early T4)
Lowgren: Polycracy and agentic governance move is fundamentally different.
Key characteristics:
Governance is no longer primarily enacted by persons, agency is distributed across:
humans, software agents, policies-as-code, feedback systems
Meaning, validation, and constraint enforcement are embedded in flows
💡
This is why polycracy is the right word here, not shared leadership.
Polycracy is about multiple centers of agency, not merely multiple leaders.
Lowgren explicitly steps beyond role-sharing among humans into:
infrastructural semantics, automated validation, agentic AI participation in governance loops.
This is already post-holacratic (operates late T4 ➡ T7) 🎭✅
They match as important alignment, both:
Laske's shared leadership describes the developmental conditions under which leadership can be distributed among humans.
Lowgren's polycratic governance describes how leadership itself migrates into socio-technical infrastructures, including agentic AI.
The transition between the two is not organizational but developmental.
A more detailed analyses and connection to transformations to refine.
RN-2.2 A new path in thinking - reflections
In this new era reflection in thinking has become possible using AI based on grammar forming sentences and a lot of open accessible sources.
It is not about simple prompt questions but how to usage what is all there beyond the human capacity to process in a sensible way.
What kind of thinking is used at & what cognitive level
Relationships in cognitive knowledge and to Jabes-Zarf
The reasoning of a LLM in the Jabes-Zarf context
Proposal for dialectal closure made practical usable
🔭 RN-2.2.1 Understanding of options in the many confusing AI types
knowledge management, getting help by a machine
What is missing is AI literacy the hype, buzz, in AI is causing more noise and confusion than better understanding.
An ateempt for a very simplified breakdown:
AI literacy
Cognitive capacity
1
AI is a generic noun for new technology
Used for all kind of stuff machines can do in processes using technology.
2
LLM large language models are for text
Using text/speech as communication it is not a about better calculator or anything in Science, Technology, Engineering, and Mathematics (STEM) usage.
👉🏾 It is based on al lot of probabilistic in text and there is lot of good accessible text around.
3
ML machine learning (big data based)
ML is very good in supervised generating better aid in decisions. It is probabilistic so there is a need to understand and manage uncertainty in results. Quite different than basic simple algorithms using formulas for the only possible correct outcome.
4
Dedicated bound domain AI usage
Dedicated domains are those from learning chess, go, that extended to STEM domains usage in recognizing special patterns.
⚒️ ANPR camera's , reading text from scans, Face recognition, fingerprint recognition, the moving analyses in sport etc.
There is a sound theoretical model behind those patterns where the analyses is build on.
⚒️ Optical readable text (OCR) automatic translation of text is not seen as AI anymore but it is.
5
Defining dedicated domains Enabling overlap with product/technology
From a sound theoretical model it is possible to start with better reasoning.
👉🏾 There is need for a well defined design theory. The missing part of design theory is where there is the gap now.
👉🏾 Training a LLM won't be very practical it will miss the boundaries and context for what is really needed.
These must set by design in AI for that defined scope. This is bypassed by building up a dedicated boundary while working on the topic.
6
Ai generating the code for the design
Having al well defined design for the minimal what is practical needed, the next challenge is the transformation into programming languages that are appropriate for the job.
⚒️ The last part is not really new. Would the language be Cobol than there products of the 90's trying to do that e.g. Coolgen.
This is a signal we need to have a generic design/knowledge system to prevent a technology-lockin for generating code.
⚒️ The other point that it gives a signal for is that the resulting code should be based on understandable proven patterns but also having the options for extending into adjusted new patterns doing the job better. Also at this point there is need to prevent a technology-lockin.
Nothing really new at this there was a time to standardize metadata to code generation using predefined standard patterns.
The Common warehouse metamodel CWM an attempt to standardize dat to information processing
OMG the institute for the CMW standard
DMG the institute for well known data mining processes.
7
Transformational
Re-framing the chosen solution, ongoing change will adopt some of this and while adding much more.
One additional important aspect in this is moving cyber-security safety into these functional processing layers.
This will solve the ongoing issues of failing cyber-security by relocating them where the activities are now positioned where they cannot be solved structural.
Common constraints when managing change
The iron triangle
The Architecture of Illusion (LI: A.Dooley 2025)
Some things are worth repeating.
The term 'Iron Triangle' was coined in 1956 in relation to the legislative process in the USA.
It has nothing to do with project management.
The iran triangle
-
The triple constraint
1
Low regulations, special favors
Functionality
2
Funding & political support
Time
3
Electoral support
Cost
4
Congressional support via lobby
Scope
5
Friendly legislation & oversight
Quality
6
Policy choices & execution
Quantity
7
To add, it is missing
Realisations by transformation
Only three are mentioned by Barnes but there are at least three more and there is transformation.
The other three are: Functionality, quality, quantity.
This gives a total of 6 distincions.
The Barnes Triangle (more recently the Triple Constraint) was created by Dr. Martin Barnes in 1979.
It has everything to do with project management.
The purpose of the triple constraint is to start a conversation about finding a balance between the constraints that is acceptable to all parties.
There is nothing about it that is cast in iron and inflexible.
Constraints in the legislative process using named stakholders a different context than constraints in project management using distinctions.
Summary of the DTF framework Zarf Jabes overlay comparison
There are several aspects that got reviewed. Feeding my pages and mentioning other sources.
To my surprise the LLM got far in the reflection of this kind of cognitive thinking. 👁️ Evaluating Zarf Jabes in DTF constructs
Zarf Jabes Jabes is giving a meaning at the "Shape Systems Thinking: 6x6 Lean & Zachman Augmented Framework" page.
The idea is that to manage complexity, one must see multiple interdependent dimensions, not just a single linear process, that is not descriptive systems thinking (formal-logical).
It is meta-structural systems thinking, the same territory Laske calls dialectical.
Key indicators (DTF markers) present throughout that are:
Reference frames instead of models
Fractals instead of hierarchies
Dualities instead of binaries
Cycles instead of linear causality
Architecture of viewpoints instead of single perspectives
This places it beyond Context-only (C) and Relationship-only (R) thinking. Consistently combines:
SIAR = Sense ➡ Interpret ➡ Act ➡ Reflect. This is where the overlap becomes very concrete.
SIAR is not: just a learning cycle, only PDCA with different labels, merely process optimization.
➡️ Cognitively, SIAR is a recursive meaning-construction loop. 👁️ Testing for hitting upper and lower bounds
There is a good balance neither of the bounds is passed.
➡️ Lower bound (under-articulation), a dimension hits the lower bound when:
a distinction is doing double duty
a TF must be inferred, not enacted
users collapse different operations into one mental move
Symptom: "I kind of get it, but I don't know what to do."
➡️ Upper bound (over-articulation), a dimension hits the upper bound when:
distinctions become context-dependent synonyms
users cannot tell which distinction to use now
sequencing becomes unclear
Symptom: "This is rich, but I'm lost." 👁️ Aliging the used vocabularies in change
In Laske's sense, Transformation (T) is not "change over time", that's Process (P).
T-forms enable:
Changing the frame of meaning
Holding and resolving contradictions
Moving between levels / scales
Letting a structure break down so a new one can emerge
Key T-moves relevant to the Jabes Zarf framework:
T4 - Breakdown / negation
T1 - Emergence
T7 - Integration at a higher level
Keep those three in mind, they recur everywhere.
This is very promising to carefully investigate what is more possible.
🔭 RN-2.2.2 Asking not only results (appeasing) but also the reasoning
DTF Alignment to 6x6 Zarf, the AI reasoning
❶
Lean cycles like PDCA/SIAR are about iterative improvement based on experience and evidence, which resonates with Process (P) and Transformation (T).
P thought forms can represent steps like flow, interruption, rhythm, which correspond to: PDCA's Plan ➡ Do ➡ Check ➡ Act
(and many alternatives).
T thought forms would articulate qualitative change & integration, moving beyond process optimization to organizational culture and systemic insight.
❷
Stresses duality and dichotomy (e.g., engineering vs system change, frontend vs backend). In DTF:
Recognizing contradictions is a precursor to dialectical resolution (T-level).
Using contradictions to drive higher-order integration resonates with T-forms like Transformation of Structure, Emergence, and Integration at a Higher Level.
❸
Key indicators (DTF markers) present:
Reference frames instead of models
Fractals instead of hierarchies
Dualities instead of binaries
Cycles instead of linear causality
Architecture of viewpoints instead of single perspectives
This already places the page beyond Context-only (C) and Relationship-only (R) thinking. ❹
Consistently combines:
Fractal scaling e.g: system ⇄ subsystem ➡ change of level ➡ T1 / T6
This explains why many people: understand the grid, but cannot use it effectively.
They lack T-capacity, not knowledge.
The 6*6 grid is a structural scaffold that implicitly demands increasing dialectical capacity as one moves downward and reflexively through it; DTF makes those demands explicit.
Testing Jabes- Zarf for Completeness for all DTF's
All 28 TFs are present, no gaps, no redundancies, that is not common. 👁️
In DTF (Laske), the 28 TFs are, structurally:
Relationship: coordination, role differentiation, power
Transformation: negation, emergence, integration
A framework "covers" a TF only if it forces the thinker to perform that operation.
Naming something is not invoking a TF. 👁️
When people map rich frameworks (Zachman, VSM, Cynefin, SAFe, etc.) to DTF, the pattern is almost always:
⚠️ Typical pattern A - Gaps Results to rigid systems
Strong Process and Relationship
Weak or absent Transformation,
Context treated implicitly.
⚠️ Typical pattern B - Redundancies Creates conceptual noise.
Same TF invoked multiple times under different labels, e.g. multiple versions of "coordination" or "planning".
⚠️ Typical pattern C - Skew Explains why people "can't use" the framework.
One quadrant dominates (often P or R), others are decorative.
Most frameworks are built from one of three starting points:
Managerial practice overweights Process & Relationship
Philosophical theory overweights Context & Transformation
Technical architecture overweights Process
Your framework did not start in one place.
It was built by iterative reconciliation of contradictions:
hierarchy vs autonomy
institution vs citizen
stability vs innovation
belief vs execution
That dialectical construction is exactly what DTF measures. 👁️
There are inherent failure modes by misunderstanding, wrong usage, structural failure points without DTF T-forms.
⚠️ Failure mode A: Grid treated as static classification
What happens:
People "fill in the boxes", No reframing occurs, Lean becomes reporting, not learning
diagnosis:
Context + Relationship only
No T4 (negation) ➡ nothing is allowed to break
⚠️ Failure mode B: Local optimization destroys system coherence
What happens:
⚠️ Failure mode C: Fractal scaling collapses
What happens:
What works at team level fails at enterprise level
People copy structures instead of re-creating them
diagnosis:
No T1 (emergence across scale)
These are T-failures, not design flaws.
🔭 RN-2.2.3 Asking for the reasoning in adjusted 3*3 frames
The cycle dialectal: Sense - Interpret - Act - Reflect
The SIAR model got reframed in dialectual sentences.
I used variations of the 3*3 frame.
The reframe in dialectual sentences is another perspective of the simplified projection in four levels for roles/tasks.
The reasoning of the LLM is the most interesting part.
Sense
Act
Reflect
Context
Problem
Mandate
Reframe
Process
Signal
Execute
Learn
Outcome
Effect
Stabilize
Purpose
This grid is not a taxonomy, it is a sentence generator.
Population of the 9 cells, this is the key step, naming each cell by its function, not by a label fetish.
👁️
Row 1: Context Problem ➡ Mandate ➡ Reframe "Why is action allowed at all?"
(1,1) Context * Sense ➡ Problem state Upper left DTF operators: Context + Negation. This is where "the problem" must live.
What about the current situation is experienced as problematic, given this context?
This is: boundary awareness, mismatch detection, dissatisfaction before solution
(1,2) Context * Act ➡ Problem framing / mandate DTF operators: Context + Relationship (authority)
How do we formally define or authorize engagement with the problem?
This includes: mandate, scope, legitimacy, "are we even allowed to act?
(1,3) Context * Reflect ➡ Reframing / problem dissolution DTF operators: Context + Transformation
Is this still the right problem, given what we now know?
This is where: problems disappear, assumptions are dropped, scope shifts
👁️
Row 2: Process Signal ➡ Execute ➡ Learn "Who does what, and answers for it?"
(2,1) Process * Sense ➡ Signal / pattern recognition DTF operators: Process + Differentiation
What is actually happening? What patterns do we see?
This is: observation of flow, early diagnosis, leading indicators
(2,2) Process * Act ➡ Intervention = DTF operators: Process + Relationship
What are we doing to change the flow?
This is: execution, coordination, decision-in-action
(2,3) Process * Reflect ➡ Learning = DTF operators: Process + Integration
What changed because we acted?
This is: feedback, adjustment, improvement
👁️
Row 3: Outcome Effect ➡ Stabilize ➡ Purpose "What does this produce in the world?"
(3,1) Outcome * Sense ➡ Observed effects = DTF operators: Outcome + Differentiation
What effects are visible now?
This is: measurement, impact detection, consequence awareness
(3,2) Outcome * Act ➡ Stabilization / exploitation DTF operators: Outcome + Process (stabilization)
Which outcomes do we reinforce, scale, or institutionalize?
This is: policy, standardization, investment
(3,3) Outcome * Reflect ➡ Purpose (POSIWID) Lower right
DTF operators: Integration across Context, Process, Outcome = POSIWID proper placed
Given what the system consistently produces, what is its actual purpose?
This is: emergent purpose, not intention, not aspiration
➡️
Why problem is upper-left:
Problems are contextual negations, they exist before action, they are sensed, not decided
Putting "problem" anywhere else either: turns it into a solution-in-disguise, or a KPI failure.
➡️
Why purpose (POSIWID) is lower-right:
Purpose is retrospective, it requires outcomes, it requires reflection
Putting purpose at the top: confuses intention with effect, breaks Beer's insight
"The purpose of a system is what it does.", not: what it intends to do, what it claims to do, what it is designed to do, but what it reliably produces over time.
That single sentence already implies time, outcomes, and reflection.
Explanation of "breaks Beer's insight"
If you place purpose: at the start, at the top or as an input, you are no longer describing POSIWID.
What happens if purpose is not lower-right
Purpose in Context * Sense
This turns purpose into: ""What we think we're here for."
that is mission, losing: feedback, accountability, learning
Purpose in Process * Act
This turns purpose into: "What we are trying to achieve while acting."
That is strategy-in-use, losing: unintended consequences, structural bias, emergent effects
Purpose in Outcome * Act
This turns purpose into: "What we decide to count as success."
That is KPI-driven control, losing: ethical reflection, systemic side effects, long-term viability
Beer's conditions
why breaks Beer's insight
Observed behavior
purpose becomes a cause, not an effect
Persistence over time
learning becomes self-confirming
Independence from stated intent
the system becomes blind to itself
💣
Intention, mission, aspiration, ideology, those may matter, but they are not Beer's purpose.
Breaking the conditions in Beer's terms, the system becomes unviable, because it cannot correct its own misalignment.
POSIWID requires purpose to be inferred retrospectively from outcomes, not asserted prospectively as intent.
Tensions in the diagonals: learning emergence vs normative intentional
In the reasoning a diagonal got mentioned.
The hidden important diagonal, Upper-left ➡ lower-right, notice the diagonal tension:
Problem state ➡ Purpose
Negation ➡ Integration
Dissatisfaction ➡ Meaning
That diagonal is the learning journey.
If a framework does not allow this diagonal to be traversed, it cannot learn.
🤔 In a 3*3 reference with Context- Process- Outcome and Sense- Act- Reflect, the problem appears as a contextual negation in sensing, while purpose (POSIWID) emerges only as an integrated reflection on stabilized outcomes.
Very well the LLM halted her and no clue for the other diagonal, using an explicit questions for that to continue.
The other diagonal: lower-left ➡ upper-right
That diagonal is: Effect ➡ Execute ➡ Reframe or, abstracted Consequences ➡ Action ➡ Values.
This is not learning-first, It is normative and intentional.
Lower-left: Outcome * Sense ➡ "What do we want?"
This is: anticipation, aspiration, imagined effects, intention, not "what is", but "what ought to be"
Center: Execute, Same center, no surprise. Both diagonals must pass through execution.
Execution is where: intention meets reality, values get tested, consequences are produced
Upper-right: Context * Reflect ➡ "What matters?"
This is: values, principles, norms, legitimacy, ethics (broadly, not morally) to decide for: "What kind of system do we want to be?"
So what is this diagonal called?
If the first diagonal is the learning / POSIWID diagonal, this second one is the normative / intentional diagonal.
In plain words:
Diagonal 1: What is happening ➡ what does it mean?
Diagonal 2: What should happen ➡ why does it matter?
They must intersect, but must not collapse into each other.
You sensed correctly that Context- Reflect and Outcome- Sense don't feel like "facts".
That's because they aren't.
So a parallel 3*3, using normative language, often helps.
Alternative wording (same structure, different semantics) 👁️
Row 1: Context Values ➡ Principles ➡ Legitimacy "Why is action allowed at all?"
(1,1) Context * Sense ➡ Values are felt, not enforced.
"This feels important / unacceptable / worth protecting."
This is: What matters to us, Often implicit, Pre-verbal emotional cultural
(1,2) (Context * Act) ➡ Principles are values made actionable.
"Given our values, we will act like this."
This is: Values translated into guidance, Decision rules, "If this, then that"
(1,3) (Context * Reflect) ➡ Legitimacy only appears after action is visible.
"Was this right, given who we are?"
This is: Retrospective judgment, Was this action acceptable?, By whom?
👁️
Row 2: Process Options ➡ Execute ➡ Responsibility "Who does what, and answers for it?"
(2,1) (Process * Sense) ➡ Options exist before commitment.
"We could do A, B, or C."
This is: Possible actions, Trade-offs, Paths not taken
(2,2) (Process * Act) ➡ Execution collapses many options into one reality.
"We are doing this now."
This is: The chosen action, the point of no return, Where energy is spent
(2,3) (Process * Reflect) ➡ Responsibility arises after execution, not before.
"We are answerable for what happened."
This is: Ownership of consequences, Accountability without blame, Learning obligation
Time-shift: responsibility cannot be assigned honestly until something has been done.
👁️
Row 3: Outcome Intent ➡ Deliver ➡ Meaning. "What does this produce in the world?"
(3,1) (Outcome * Sense) ➡ Intent is future-oriented imagination.
"We want this to happen."
This is: Imagined effects, Desired change, Hopes and fears
(3,2) (Outcome * Act) ➡ Delivery is fact, not promise.
"This is what happened."
This is: What actually shows up, Tangible effects, Irreversibility
(3,3) (Outcome * Reflect) ➡ Meaning emerges after outcomes are lived with.
"So this is what it meant."
This is: Interpretation of consequences, Stories we tell, Purpose attribution
Time-shift: Meaning cannot be fixed in advance without ideology.
🔏
This is not linear planning, It's accountable emergence.
Why this fails that often in collapsed time and destroyd learning.:
treat values as static, assign responsibility in advance, declare meaning upfront
Each row expresses a temporal shift from anticipation through action to retrospective judgment, preventing values, responsibility, and meaning from being declared before they are earned.
Before action
During action
After actions
Imagine
Commit
Justify
Context
Values
Principles
Legitimacy
Process
Options
Execute
Responsibility
Outcome
Intent
Deliver
Meaning
A hidden tension, many ways time is acting on the system:
Left to right for each row
the cycle e.g. produc/service
the state of the system
Each row expresses a temporal shift from anticipation through action to retrospective judgment, preventing values, responsibility, and meaning from being declared before they are earned. 🔏
Why both diagonals are needed (critical), If you use only:
the first diagonal ➡ you get adaptive systems with no compass
he second diagonal ➡ you get ideology, mission statements, and control illusions
Dialectical closure requires both diagonals to be visible and in tension, that tension is healthy.
The upper-left to lower-right diagonal explains how meaning emerges from action, while the lower-left to upper-right diagonal explains how values and intentions seek expression through action.
🔭 RN-2.2.4 The challenge: "From Tension to Direction"
This not a control framework, it is a time-respecting grammar for collective action.
That's why it scales fractally and why it feels unfamiliar to command-and-control thinkers.
A jump out of the box. 🎯
The Facilitation to "From Tension to Direction" is a two-diagonal move you can use with teams, communities, or policy groups.
It works on a whiteboard, Miro, or paper, no theory explanation required.
Use it when:
people talk past each other
values and facts are mixed
action feels premature or blocked
purpose is asserted but not grounded
Goal: We'll look at what's actually happening, followed by what should matter, then adjust what we do so the two line up.
Time: 15- 30 minutes Group size: 3- 12.
Sense
Act
Justify
Context
Problem
🕳
Values
Process
🕳
Execute
🕳
Outcome
Intent
🕳
Purpose
Imagine
Commit
Reflect
⚖️
Step 1 --" Draw only this (don't explain yet).
Intentionally; do not fill the other cells.
Note: this is the x-matrix in disguise made universally usable
⚖️
Step 2 --" Diagonal 1: What is actually happening? (Learning)
Ask only these three questions, in order:
Problem (Context * Sense): What is not working right now, for real?
Execute (Process * Act): What are we actually doing about it?" not planning, not intending?
Purpose (Outcome * Reflect) Given our repeated actions, what does this system seem to be for?
Write short phrases, No debate yet. This diagonal reveals reality. ⚖️
Step 3 --" Diagonal 2: What should matter? (Normative)
Now ask the other three:
Intent (Outcome * Sense) What outcome do we want to see more of?
Execute (Process * Act) What action would express that intent, starting now?
Values (Context * Reflect) What principle or value should guide our choices here?
Write short phrases, No debate yet. This diagonal reveals aspiration. ⚖️
Step 4 --" The critical move: compare the diagonals: Now point to the centre Execute and ask:
Where do our actual actions diverge from our intended values?
There are only three possible answers:
They align ➡ proceed
They partially align ➡ adjust execution
They conflict ➡ stop and reframe
This moment creates dialectical closure, no voting needed . ⚖️
Step 5 --" One legitimate next step
Ask only one final question:
What is the smallest change in execution that would better express our values without denying reality?
Write one action. (That's it.) 🎯 Those limited set of actions should be defined in a stated problem structure so it is possible to derive proposals in a requirements structure.
By this the suggestions, ideas knowledge share gets
The ideation feed for initiating required changes.
Change, adaptation is needed to be viable, at least the verification not to be missed.
Left open is the question of the needed change is achievable
✅
Why this works (without explaining theory):
People recognize facts without feeling attacked
Values are surfaced without moralizing
Execution stays singular and central
Purpose is inferred, not asserted
No one has to "win" an argument
⚠
Failure modes (useful signals)
If people argue about purpose ➡ they skipped the first diagonal
If people argue about values ➡ they skipped the second diagonal
If people argue about execution ➡ governance is unclear
If people want to fill all 9 cells ➡ abstraction anxiety
RN-2.3 Purposeful usage of dialectal thoughts
This different path on information processing supporting for governance and informed understandable decisions requires more detailed scape and bounaries to make it more practical.
The four areas in better understanding hold:
Constraints in the distincions thought forms
Is there a problem that is felt to act on?
Do we really understand what the problem is?
How to measure in a sensible way what is changing
🌗 RN-2.3.1 Underpinning nominal limit in distinctions at a dimension
formally justification why "8" becomes redundant
This question was bothering me seeing the repeating pattern.
There is no reference for this found (search engine).
Using a LLM to get it understandable explained.
The closure condition at 6- 7 (key step) explained.
Across dialectical systems, closure occurs when all logical moments of determination are present. ⚖️
These moments are invariant (names vary):
Grounding - what exists / is given
Differentiation - distinction from others
Relation - mutual influence
Opposition - tension / conflict
Boundary / Negation - limits, breakdown
Reorganization - new pattern
Integration - higher-order coherence
Once all 7 are present, any new distinction must either repeat one of these operations or combine two already present, that is closure.
This is the same notion of closure used in:
Piaget: operational closure,
Jaques: requisite organization,
Laske: TF completeness.
Why an 8th distinction cannot be irreducible (the proof)
Assume an 8th distinction D8 is irreducible. Then D8 must perform a cognitive operation not covered by the 7 above.
There are only three possibilities:
Case A: D8 introduces a new kind of relation, but all relations are already captured by Relation or Opposition any "new" relation is either:
a subtype (derivative), or contextual specialization
❌ Not irreducible.
Case B: D8 introduces a new kind of change, but change is already captured by
Case C: D8 introduces a new meta-operation, but meta-operations are already covered by integration metaA2 collapses into rhetoric, not action
At that point, the distinction:
👁️
Therefore Any proposed 8th distinction is either a recombination, specialization, or rhetorical elaboration of existing ones. QED.
Once grounding, differentiation, relation, opposition, boundary, reorganization, and integration are present, the system of distinctions is closed; any further distinction must be a recombination or contextual specialization, and is therefore redundant at the structural level.
The comparative justification for why ~6-7 distincions
The reasoning for a limited number of distinctions in
comparative convergence:
DTF Cognitive operators 7 per quadrant,
VSM Control functions 5 + 2,
Cynefin Sense-making regimes 5 + boundaries,
Zachman Enterprise perspectives 6 (+ integration)
VSM breakdown
Cynefin domains
Zachman ⇄
Zachman ⇅
System 1 Operations
⇄
Clear Sense- categorize- respond
1
What (data)
⇄
Context (Scope)
System 2 Coordination / damping
⇅
Complicated Sense- analyze- respond
2
How (function)
⇅
Concept (Business)
System 3 Internal regulation
⇄
Complex Probe- sense- respond
3
Where (network)
⇄
Logic (System)
System 3* Audit / reality check
⇅
Chaotic Act- sense- respond
4
Who (people)
⇅
Technology
System 4 Intelligence / future
⇄
Confused Not knowing which domain
5
When (time)
⇄
Detailed, (components)
System 5 Identity / policy
⇅
Disorder Transitional ambiguity
6
Which (motivation)
⇅
Functioning
Environment External complexity
Aporetic boundary Collapse / phase shift
7
(Implicit Iteration)
(Implicit Iteration)
👁️
Across organizational cybernetics (VSM), sense-making (Cynefin), enterprise architecture (Zachman), and cognitive dialectics (DTF), systems converge on roughly six to seven irreducible distinctions per dimension because that is the minimum articulation required for stable, non-redundant understanding and control of complexity.
textual references in this:
Beer himself resisted adding more because:
fewer ➡ loss of viability,
more ➡ conceptual duplication.
Cynefin Most presentations stop at 5, but in practice,
Confusion is a distinct cognitive state,
boundary collapse (complex ➡ chaotic) is operationally distinct.
Snowden himself emphasizes: "The boundaries matter more than the domains."
Zachman's success comes from:
completeness without redundancy,
independent but intersecting dimensions.
Zachman originally resisted adding more columns or rows for the same reason Laske does.
📚
The statement: "Each dimension, when articulated adequately but minimally, needs about 6-7 stable distinctions." does not originate as a design rule in Laske.
It is a convergence result across several intellectual traditions that Laske draws together.
Hegel (dialectic constraints)
Piaget (epistemic operators)
Jaques (Stratum - Cognitive)
Immediate ⇅ Undifferentiated unity
Reversibility ⇅ Undoing
Declarative ⇅ Facts
Negation ⇅ Differentiation
Conservation ⇅ Invariance
Procedural ⇅ Processes
Mediation ⇅ Relation
Compensation ⇅ Balance
Serial ⇅ Sequences
Opposition ⇅ Tension
Composition ⇅ Combining
Parallel ⇅ Systems
Contradiction ⇅ Instability
Negation ⇅ Differentiation
Meta-systemic ⇅ Systems of systems
Sublation ⇅ Reorganization
Reciprocity ⇅ Mutuality
Dialectical ⇅ Contradiction
Totality ⇅ Integration
Transformational ⇅ Re-framing identity
Hegel does not enumerate categories arbitrarily. He shows that thinking generates distinctions until contradiction stabilizes.
Hegel's dialectic unfolds through triadic movement, but stability requires more than three moments, Across Being ➡ Essence ➡ Concept .... (see table) though Hegel never lists them as such.
Piaget repeatedly finds: fewer operators ➡ unstable reasoning, more ➡ redundancy, no new power. Operational systems stabilize at ~6 coordinated operators.
Jaques never formalizes "7" as a rule, but Below ~6 ➡ roles fail, above ~7 ➡ no additional explanatory power.
Laske empirically finds that: fewer ➡ clients cannot complete dialectical moves, more ➡ TFs collapse into each other,
Laske and collaborators coded hundreds of DTF interviews, observed that:
Below ~6 distinctions ➡ thinking collapses into vagueness
Above ~7 ➡ distinctions collapse back into synonyms or rhetoric
Key sources:
Hegelian dialectics (structure of determination) Hegel published his first great work, the Phenomenologie des Geistes (1807; The Phenomenology of Mind). This, perhaps the most brilliant and difficult of Hegel's books, describes how the human mind has risen from mere consciousness, through self-consciousness, reason, spirit, and religion, to absolute knowledge..
Piaget / Kegan (constructive-developmental limits)
Developmental psychology shows that:
Piaget's theory of cognitive development, or his genetic epistemology, is a comprehensive theory about the nature and development of human intelligence. Kegan described meaning-making as a lifelong activity that begins in early infancy and can evolve in complexity through a series of "evolutionary truces" (or "evolutionary balances") that establish a balance between self and other (in psychological terms), or subject and object (in philosophical terms), or organism and environment (in biological terms).
This is not Miller's "7±2" memory claim it is about structural differentiation, not memory load.
Jaques' stratified systems theory Elliott Jaques Jaques incorporated his findings during "Glacier investigations" into what was first known as Stratified Systems Theory of requisite organization. This major discovery served as a link between social theory and theory of organizations (strata).
Empirical validation in DTF research
😲 The 7-per-quadrant pattern is empirical, not aesthetic.
Historical source for limited number of distinctions
Another direction of why there is that limitation in number of distinctions.
Asking not a citation chain but a structural genealogy: how the same necessity for articulated distinctions reappears as theories of mind mature.
To trace it explicitly and conservatively, showing what is inherited, what is transformed, and why the 6-7 pattern keeps re-emerging.
Hegel - Dialectic as Generative Constraint
Core move: Hegel does not enumerate categories arbitrarily.
He shows that thinking generates distinctions until contradiction stabilizes.
Key structure (Logic): Hegel's dialectic unfolds through triadic movement, but stability requires more than three moments.
Across Being ➡ Essence ➡ Concept we (see table) 7 functional moments, though Hegel never lists them as such.
👉🏾 Crucial point, Hegel discovers that:
thought must differentiate, but cannot differentiate endlessly, because coherence collapses
✅ Dialectic stabilizes when all necessary moments are present
Piaget - Epistemic Operators in Development
Piaget takes Hegel out of metaphysics and into empirical cognition.
Explicit inheritance from Hegel: dialectic becomes equilibration, Contradiction becomes cognitive disequilibrium, sublation becomes re-equilibration.
Piaget's key shift into formal Operational Thinking:
From categories of being ➡ operations of knowing.
identifies coordinated operations, not facts.
These form closed operational systems.
👉🏾 Piaget repeatedly finds:
fewer operators ➡ unstable reasoning, more ➡ redundancy, no new power.
Operational systems stabilize at ~6 coordinated operators
✅ The same constraint appears, now empirically grounded
Elliott Jaques - Stratified Cognitive Complexity
Jaques applies Piagetian operations to work, time, and organizations.
Jaques' contribution, he discovers that: roles require specific levels of cognitive integration.
The critical move, Jaques ties cognitive differentiation to:
Laske makes the latent structure explicit, Laske's synthesis integrates: Hegelian dialectic, Piagetian operations, Jaques' strata, Adult development research.
He created a DTF structure in four classes, each with 7 thought forms:
Class
Function
1
Context
Framing
2
Process
Change
3
Relationship
Interaction
4
Transformation
Re-organization
The four classes serve each a different function.
👉🏾 Why 7 thought forms? Because Laske empirically finds that:
fewer ➡ clients cannot complete dialectical moves
more ➡ TFs collapse into each other
✅ Dialectical completeness becomes necessity
These are Hegelian moments, operationalized.
The through-line (compressed):
Thinker
Contribution
What stays invariant
Hegel
Dialectic of concepts
Necessary moments
Piaget
Dialectic of cognition
Operational closure
Jaques
Dialectic of work
Functional sufficiency
Laske
Dialectic of thought
Explicit minimal set
What persists is not the number but the necessity of a bounded set, 6-7 appears because:
👉🏾 That is the smallest number of distinctions that allows contradiction, mediation, and integration without collapse or redundancy.
✅ Laske is the first to state the constraint explicitly
From Hegel's Logic through Piaget's operations, Jaques' strata, and Laske's DTFs, the recurrence of approximately six to seven distinctions per dimension reflects a deep structural constraint of dialectical cognition:
it is the minimum articulation required to hold difference, tension, and integration simultaneously without conceptual collapse.
👁️💡
A good explanation but no verification by others, stated: mentioned nowhere.
🌗 RN-2.3.2 Thinking dialectical on how to define "the problem"
Starting with understanding "the problem"
There is an old never mentioned gap. When there is need for change felt it is a problem to state to problem why that needed for changed is felt.
"So you want to define "the problem" (LI: John Cutler 2025)
The full page is at:
The beautifull mess, TBM 396" 🕳️
In product, we're told to "define the problem."
I've always felt that this is hubris, at least with anything beyond fairly contained situations.
"Go talk to customers, and figure out what the problem is!"
Their problem?
My problem with their problem?
A problem we can help with?
What they say their goal is?
Ultimately, as product builders or interveners, we may choose to take a shot at "solving the problem" with the tools at our disposal.
So I guess my intent with this is to get people thinking at multiple levels.
👉🏾 This is not a root cause model.
The layers are not steps toward a single, correct explanation.
They are ways of seeing the situation from different angles, adding context and constraints.
The goal here is not to fully explain the situation, but to act more thoughtfully within it.
There is no privileged "problem definition" moment.
This is in line with dialectical thinking, the problem definition in sensing what the intention is, context (C), with the goal of able to act on processes(P) by using relationship(R) thoughtforms.
Distinctive capabilities in problem understanding
This can be made part of "The Two-Diagonal Facilitation Move: From Tension to Direction".
"Define the problem" is often hubris in complex situations and there is no single privileged problem definition.
The goal should be to act more thoughtfully by looking at the situation from multiple angles. ❶Customer's mental model/ stated problem
Start with how the customer describes the problem in their own words and suspend judgment
👉🏾 It is their mental model of the problem. This is their story, not ours, no matter how strange it might sound, or how strongly we might feel they are wrong or missing the point.
👉🏾 Even if the framing is misguided, it is still the belief system and narrative currently organizing their understanding of the situation.
👉🏾 If anything is going to change, it is this story and its explanatory power that will ultimately need to be replaced by something more compelling. ❷Human Factors and behavorial Dynamics
Examine the system forces shaping behavior including incentives norms tools power and constraints.
Shifts focus to the environment and the forces acting on people within it.
We intentionally look at the system through multiple lenses, including:
human factors, learning design, behavioral psychology,
anthropology, politics, social practice theory and
power.
The aim is not to find a single cause, but to understand how the system shapes what feels normal, risky, effortful, possible, etc. ❸Ecosystem view. Other actors perspective
Look at how other people around them experience the same situation and
notice bias and false consensus.
Here we explicitly acknowledge that how one person sees or feels the problem is just one take on the situation.
People often inflict their framing of the problem onto others, intentionally or not. ❹Restated Problem with status quo attempts
Integrate perspectives with history and prior attempts and treat past fixes as useful data.
This is where we start integrating. We take the actors from Layers 1 and 2 and the forces identified in Layer 3, and we add history.
What has already been tried? What workarounds exist?
What has failed, partially worked, or succeeded to much fanfare?!
We begin restating the problem through this richer lens, knowing full well that we are now converging and imposing a perspective, whether it turns out to be right or wrong. ❺Feasible influence & Meeded Capabilities
Back to reality, informed by everything we have learned so far.
Our understanding of what is possible is shaped by the stories we heard, the perspectives surfaced, the system forces examined, and the history uncovered. (layer 1-4)
This is where we move from understanding to action.
Here we form concrete, feasible actions for how we might intervene in the situation.
We ask and decide what:
we can try, not in theory, but in practice.
can we realistically influence today?
small actions are feasible?
capabilities that are qualitative missing or quantitively not sufficient
capabilities we need to borrow, buy, or build to support those interventions?
levers are actually within reach?
These choices cannot be made in isolation.
They must cohere with prior efforts, align with the incentives and constraints already at play, fit the needs and beliefs of the actors involved, and still connect back to the problem as it was originally described, even if that description now feels distant from where we believe the strongest leverage exists. ❻Enabling overlap with product/technology
Consider how your product or expertise could realistically influence these dynamics without selling.
We consider our product, expertise, or technology, and how it might influence the situation.
Not how it will, not how it should, but:
how it could, in theory, intersect with the dynamics we now understand.
The issue is one of opportunity, can we reduce friction or create new pathways?
If it is capability, can we scaffold learning or decision-making?
If it is motivation, can we alter incentives, visibility, or feedback loops?
This is hypothesis-building, not pitching. ✅
The aim is better judgment and leverage not a perfect explanation.
Defining an index reference for the problem-state
"The problem" is very generic, in this we have a starting point at any level if there is a start made by stating: "a problem".
"DTF-safe" scoring vocabulary for ZARF using the problem state from Cutler is:
Key identity
Key thoughts
Involved thoughts for information review
?-PTF-1
Customer's mental model/ stated problem
What problem does the customer say they have, in their own words?
?-PTF-2
Human Factors and behavorial Dynamics
What frictions, incentives, norms, habits, or power dynamics are blocking or reinforcing current behaviors?
?-PTF-3
Ecosystem view. Other actors perspective
How do other actors in the customer's environment interpret or feel the impact of this problem?
?-PTF-4
Restated Problem with status quo attempts
When we integrate these views and factors, what is the "real problem" , and why have existing fixes or workarounds failed?
?-PTF-5
Feasible influence & Needed Capabilities
What can we realistically influence today, and what additional capabilities would be needed to expand that influence?
?-PTF-6
Enabling overlap with product/technology
How does our product, expertise, or technology directly address these dynamics and create better conditions?
?-PTF-7
Transformational realising solutions
Re-framing the chosen solution
👁️💡 The pattern is usable as fractal at any level any type of of context.
There are minor adjustments made in Cutlers text.
Two sub-fractals, each of them in 6 distinctions, are made better visible.
The Key-indentions are enablers for supporting in an information system.
The transformational step is what it initiates to the connected stage of extracting defining sugestions enabling requirements.
This is a closure in line with eDIKWv.
🌗 RN-2.3.3 The role of certainty in systems, TOC: first order
Anti-buzz hype data understanding limitations
Just asking the LLM to review this:
why-data-cannot-be-understood-scientifically (Malcolm Chisholm Oct 16 2025)
The text is about how we see "data".
Key points:
Data is often assumed to be "scientific"
Common belief: because something is labelled "data-driven" it must somehow be aligned with the rigour of the scientific method (hypotheses, measurement, predictable behaviour).
In this view, data is treated like a class of things whose individual elements behave according to general laws. (e.g., "all ticks suck blood, so if I see one I know it will do so"
Assumption: experts know how to treat "data" properly, since it is scientific.
But in practice, data often resists that kind of scientific understanding
A practical example: a financial-instruments database where each record had an identifier of eight digits. The first three digits appeared random; the remaining five sequential."
Discovered (by talking with "old timers") that originally the identifier was purely sequential, but at one point someone changed the first three digits to a "random" prefix because the storage system had performance issues (all new records were getting physically crowded on a hard drive), that change remained.
The author reflects: the original reason (hard drive head wear) is obsolete now; yet the "quirk" remains in the data schema. Data artifacts persist."
Why this matters
Because data is often inherited through migrations, evolutions of systems, and forgotten design choices, the "why" behind particular patterns or structures may be lost.
Result: we cannot simply "inspect" current data and assume it behaves according to some neat scientific laws. Features may be historical, accidental, ad-hoc fix, legacy artefacts.
Argument: this undermines the idea that data can always be treated via a purely scientific approach, because the context, history, and idiosyncrasies matter.
The warning, consequences": slower adaptability, additional effort, "sclerosis" in organizations that rely on old data but cannot fully reinterpret or clean it.
Take-away
The modern prejudice that everything must be understood scientifically (i.e., via general laws, predictable behaviour, standardised models) doesn't always apply to data.
Practically: data management must account for history, context, design decisions, migrations, legacy systems,not just treat data as "scientific stuff" that behaves uniformly.
The author implies that acknowledging this gap is important for realistic data strategies.
Certainty uncertainty in the theory of constraints
The theory of constraints (TOC) is focussing on a single issue that is holding op the system.
This classic Theory of Constraints (TOC) thinking assumes a predictable system in the way of a pendulum.:
First-order pendulum characteristics
The system has one dominant degree of freedom
Focus on the constraint.
Variability is treated as noise around a stable center
Act decisively on the best current model.
The observer is outside the system
Learn from system feedback.
⌛
Even when they acknowledge learning and adaptation, the structure of causality remains linear:
"We act ➡ reality responds ➡ we adjust."
This is a single-loop learning architecture. The pendulum swings, but the pivot point is fixed.
👉🏾 The problem lives in the uncertain world, the task is to act despite it.
The reality of complex system is far more unpredictable like a double pendulum set under high stress.
Decisions in a simple order: What how where who and when the last one is more interesting ... which!
The Logical Thinking Process: A Systems Approach to Complex Problem Solving a review by Chet Richards. (2007),
TOC amd what is in a LI post. ⏳
The thinking processes in Eliyahu M. Goldratt's theory of constraints are the five methods to enable the focused improvement of any cognitive system (especially business systems). ...
Some observers note that these processes are not fundamentally very different from some other management change models such as PDCA "plan-do-check-act" (aka "plan-do-study-act") or "survey-assess-decide-implement-evaluate", but the way they can be used is clearer and more straightforward.
A review of the work of Dettmer.
Dettmer begins the chapter by sketching the basic principles of human behavior, but there's a limit to what he can do in a couple of dozen pages or so.
People do get Ph.D.s in this subject.
So regard it as more of a brief survey of the field for those lab rats from the engineering school who skipped the Psych electives.
Then he does a very unusual thing for a technical text.
He introduces John Boyd's "Principles of the Blitzkrieg" (POB) as a way to get competence and full commitment, "even if you're not there to guide or direct them" (p. 8-11).
Which means that people have to take the initiative to seek out and solve problems, using the common GTOC framework to harmonize their efforts.
Certainty uncertainty in the theory of constraints
An LI article on TOC is claiming TOC felt as being incomplete but the question is what that is.
The Illusion of Certainty (LI: Eli Schragenheim Bill Dettmer 2025) ❶
When there is no way to delay a decision, the clear choice is to choose the course that seems safer, regardless of the potential gain that might have been achieved.
In other words, when evaluating new initiatives and business opportunities, the personal fear of negatives results, including those with very limited real damage to the organization, often produces too conservative a strategy.
Ironically, this might actually open the door to new threats to the organization.
Organizations must plan for long-term as well as short-term objectives.
However, uncertainty often permeates every detail in the plan, forcing the employees in charge of the execution to re-evaluate the situation and introduce changes.
By confronting uncertainty, both during planning and execution, the odds of achieving all, or most, of the key objectives of the original plan increase substantially. ❷
Living with uncertainty can create fear and tension.
This can drive people to a couple of behaviors that can result in considerable "unpleasantness."
Relying on superstitious beliefs that promise to influence, or even know a priori, what's going to happen.
For instance, going to a fortune teller, believing in our sixth sense to see the future, or praying to God while rolling the dice.
Ignoring the uncertainty in order to reduce the fear. When we ought to have a frightening medical test, we might "forget" to actually take the test.
Politicians and managers typically state future predictions and concepts with perfect confidence that totally ignores the possibility for any deviation.
When managers, executives, and even lower-level supervisors assess the organizational decisions they must make, they have two very different concerns.
First, how will the decision affect the performance of the organization?
And second, how will the decision be judged within the organization, based on subsequent results?
Actually, in most real-world cases the net impact of a particular move on the bottom line is not straightforward.
In fact, determining the net contribution of just one decision, when so many other factors influenced the outcome, is open to debate and manipulation.
It's easy to see this kind of after-the-fact judgment as unfair criticism, especially when it ignores the uncertainty at the time the decision was made.
In most organizations leaders evaluate the performance of individual employees, including managers and executives. This practice is deeply embedded within the underlying culture of most organizations.
❸
What motivates this need for personal assessment?
It's that the system needs to identify those who don't perform acceptably, as well as those who excel.
In order to assess personal performance, management typically defines specific "targets" that employees are expected to achieve.
This use of such personal performance measurements motivates employees to try to set targets low enough so that, even in the face of situational variation, they'll be confident that they can meet these targets.
In practicality, this means that while targets are met most of the time, only seldom they are outperformed, lest top management set higher targets.
(Today's exceptional performance becomes tomorrow's standard.) ❹
In practice, this culture of distrust and judgment-after-the-fact produces an organizational tendency to ignore uncertainty.
Why? Because it becomes difficult, if not impossible, to judge how good (or lackluster) an employee's true performance is. ⏳
The analysis:
Schragenheim & Dettmer argue that uncertainty is unavoidable, but that paralysis in the face of uncertainty is a choice. Their core claims:
Decision-makers never have full information.
Waiting for certainty is an illusion.
Effective action under uncertainty requires commitment + fast correction.
Systems (especially organizations) must be designed to act, observe, and adjust.
Crucially, uncertainty is treated as an external condition that the decision-maker must cope with.
TOC optimizes for:
A true double-pendulum
Operational clarity
Weakens managerial authority.
Actionability
Delays commitmentt current model.
Managerial decisiveness
Requires reflexive leadership capacit.
The issue:
Why TOC tends to stay first-order, is not a mistake, it is a design choice.
Schragenheim & Dettmer are firmly within strategic rationality, even when they talk about learning and adjustment.
Even when they warn against after-the-fact blame, the logic remains: "A good decision is one that increases the likelihood of success.".
This is teleological rationality, not discursive validity.
Habermas: "this is means- ends rationality under uncertainty" and "The lifeworld assumptions are taken for granted."
🌗 RN-2.3.4 The role of certainty in systems, SD: second order
Uncertainty shifts from environment ➡ interpretation
Instead of: "We lack information" It becomes: "We lack shared understanding of what matters".
The problem becomes discursive, not operational. ⏳
A double pendulum is not just "more uncertainty", but a qualitative change in system behavior:
Small changes in initial conditions radically alter trajectories
The observer becomes part of the dynamics
Prediction collapses into retrospective sense-making
First-order pendulum characteristics
Double pendulum characteristics
How uncertainty is framed
Aspect
Aspect
Incomplete information
Uncertainty is external
Uncertainty is co-produced
The environment / future
Problem location is stable
Problem location shifts
Actor responding to reality
Actor responds to system
Actor is part of system
Feedback and adjustment
Learning corrects action
Learning redefines framing
The system itself is intelligible
Constraint is "out there"
Constraint may be epistemic
A double-pendulum model would ask:
How does our way of seeing create the constraint?
What assumptions stabilize the "problem" prematurely?
How does authority freeze interpretation too early?
This is second-order observation (Laske, Luhmann, von Foerster).
👉🏾 The problem lives in the interaction between interpretation, power, and action.
Under communicative action:
Decisions are temporarily stabilized meanings
Authority legitimizes process, not outcomes
Revision is not failure, but rational continuation
This is the double pendulum: One arm = action, Second arm = interpretation legitimacy.
Habermas' four validity claims become central:
Claim
Question
Truth
Plausible understanding of reality?
Rightness
Acceptable to those affected?
Sincerity
Are we honest about uncertainty?
Comprehensibility
Do we understand each other?
Issue:
None of these are operational metrics, they destabilize "decisiveness", expose power asymmetries:
Who defines the problem?
Who declares uncertainty "manageable"?
Who bears the risk?
⚠️❗ A missing level for more certainty.
Organizations stabilize uncertainty by privileging strategic action (Habermas) and work (Arendt) at cognitive levels (Laske C3- C4) that cannot tolerate the reflexive instability introduced by communicative action and action proper, thereby collapsing the second pendulum of meaning, legitimacy, and emergence.
The real constraint is not uncertainty, it is developmental capacity under authority.
Until that is acknowledged:
Double pendulum models will be rejected as "impractical"
Second-order observation will be performed but not inhabited
The problem will continue to appear "out there"
The next option is using system dynamics (SD): shifting what is perceived in uncertainty.
RN-2.4 Becoming of identities transformational relations
In this dialectal path on information processing supporting for governance and informed understandable decisions the identity of persons group of persons and organisations will have to change.
The classical hierarchical power over persons is outdated an has become a blocking factor.
The decoupling of fame - honour from hierarchical power
Reidentify the fame - honour value different in a holarchy
Using machines technology AI for reflections in mindsets
The quest for closed-loops in emerging human thinking
🧬 RN-2.4.1 Communities of practice - collective intelligence
"Communities of practice" theoretical
It is far beyond the personal human comfort zone but helpful in reflection and finding the references for trustful sources.
My approach is trying to align to the DTF Framework using LLM.
When I started with the communities of practice CoP of the EU CoP JRC it bypassed Wenger.
Using a Book Review (researchgate book review 2003 Mellony Graven, Stephen Lerman) gives the highlights.
Domain
what the community is about
1
Participation
⇄
Reification
Community
social fabric and mutual engagement
2
Local practice
⇄
Global alignment
Practice
shared repertoire of doing
3
Experience
⇄
Competence
Identity / Learning
becoming through participation
4
Identity
⇄
Community
Wenger's mature CoP theory (1998-2010) rests on four pillars:
👁️
Wenger explains that communities of practice are everywhere and because they are so informal and pervasive they are rarely focused on.
Focusing on them allows us to deepen, to expand and to rethink our intuitions.
He relates communities of practice to the learning components of meaning, practice, community and identity.
And rests on three learning modes:
Engagement, Imagination, Alignment.
This already tells us something important: Wenger is not describing a social structure, he is describing a meaning-producing system over time.
That places him squarely in dialectical territory, even if he never uses the word.
The used visual is showing four lines in two diagonals.
Modern Management Consulting origins
There is a long ongoing cultural split for operating the shop and govern formal by administration.
That is still ongoing in the misundertanding for a mind on the problem (product) purpose vs the intent to value why it usefull.
history of management consulting. (D. McKenna 1995)
In 1993, AT&T spent ore on management consulting services than on corporate research and development, and AT&T is not alone.
Wall Street analysts expect billings for consulting services to advance at twice the rate of corporate revenues over the next decade.
Yet, despite the size, growth, and influence of consulting firms, business historians have remained uncharacteristically silent about the origins, development, and impact of management consulting, or "management engineering" as it was known before the Second World War.
Arguing that:
historians have wrongly assumed that management consulting arose directly out of Taylorism,
that engineers, accountants, and lawyers, often supervised by merchant bankers, provided counsel that later became the primary repertoire of management consultants, and
that the legal separation of investment and commercial banking in 1933 drove the rapid professionalization and growth of management consulting during the Great Depression.
The proponents of scientific management, Frederick Taylor, Henry Gantt, Morris Cooke, Frank and Lillian Gilbreth, and Harrington Emerson, consulted with nearly 200 businesses on ways to systematize the activities of their workers through the application of wage incentives, time-motion studies, and industrial psychology.
Hugh Aitken pointed out in Scientific Management in Action, those executives and their advisors in large scale business who were "concerned with problems of formal organization and control at the administrative level," came out of a different intellectual tradition than the shop management movement from which Taylor made his reputation.
Taylorists were largely concerned with industrial relations
Early management consultants focused on problems of bureaucratic organization
👁️ There is that split in cultures that never got closed. But what is the force behind?
The growth of management consulting in the 1930s was not simply a "natural" market response to the economic down turn.
It was, instead, an institutional response to new government regulation.
New Deal banking and securities regulation propelled the growth of management consulting in the mid-1930s.
Firms of management consultants prospered as companies turned from bankers to management engineers for organizational advice.
Congress passed the Glass-Steagall Banking Act of 1933 to correct the apparent structural problems and industry mistakes that contemporaries to the stockmarket believed led crash in October 1929 and the bank failures of the early 1930s.
The Glass-Steagall Act and S.E.C. disclosure regulations forced commercial and investment bankers to abandon internal management consulting activities even as regulators mandated that they commission outside studies.
These required studies, combined with the increasing acceptance of management engineers by corporate executives, propelled the rapid growth of consulting firms from the 1930s onward. ⚠️ The force behind that culture rupture is surprising.
Attempt to influence by legal regulations that result in unforeseen effects.
Failing reflection shown by the imbalance of power blaming the operational relations when the outcomes are not as intented.
🧬 RN-2.4.2 The challenge in building up relationships
Lencioni model dysfunctions of a Team
Interpretation of the understanding the Lencioni Model
(k.Gowans) and
by bitsize (who?)
is revealing the intentions but also shows the limitations.
Whether you're running a team or simply a part of one, we hope you'll find our summary of Patrick Lencioni's insightful teamwork concept, "The Five Dysfunctions of a Team" useful.
Lencioni uses a classic pyramid to explain the five main problems teams face.
In line to:
In any team, performance ebbs and flows. But when results start slipping, it's essential to understand why rather than just push harder.
The Lencioni Model provides a simple yet powerful framework to help you diagnose issues at their root and take meaningful action.
One of the used figures, see right side.
There is a notion of the issues but a clear dialectual connection is missing.
❶ Start at building trust:
Trust is the foundation of teamwork.
Teams who lack trust conceal weaknesses and mistakes, are reluctant to ask for help, and jump to conclusions about the intentions of other team members.
It is crucial to establish a team culture where individuals feel able to admit to mistakes and weaknesses, and use them as opportunities for development. ❷Acceptance of frictions:
When teams do not engage in open discussion due to a fear of conflict, team members often feel that their ideas and opinions are not vlued.
They may become detached or even resentful, and fail to commit to the chosen approach or common goal as a result.
Fear of conflict: The desire to keep the peace stifles productive conflict within the team. ❸Shared goal committment:
Do team members clearly understand how their work contributes to the bigger picture?
Lack of commitment - The lack of clarity and/or buy-in prevents team members from making decisions they will stick to. ❹ Accountablity:
Hold yourself accountable, and expect the same from your team. This can help foster a culture of responsibility and accountability.
Reframing the Lencioni pyramid using signals:
negative signals
relationship
positive signals
1
(-)
⇄absence of trust-ethics trust-ethics one another ⇆
Safe to speak up
2
(-)
Openess in unclear honest
3
(-)
Collaboration
4
no ask for help when needed
(-)
5
Guardeness
(-)
6
Conceal weakness
(-)
7
draid meetings
(-)
8
team member avoidance
(-)
.
1
Problems, issues avoidance
⇄fear of conflict conflict for growth ⇆
Confront problems, issues quickly
2
Lack of transparency
(-)
3
confusion
(-)
4
(-)
Openess-honest, candour
5
(-)
practical solutions
6
(-)
minimal policies
7
(-)
feedback, reflect & adapt
.
1
Ambiguous direction
⇄lack of commitment commitment of team ⇆
Clear directions
2
Unclear priorities
Clear on set priorities
3
Hesitancy
(-)
4
Absenteism
(-)
5
Repetition same discussions
Shared on common objectives
6
No autononmy
autonomous activities
7
(-)
power tot the edge decisions
.
1
Poor performance tolerated
⇄avoidance of accountability accountability taken ⇆
Poor performers held accountable
2
Missed deadlines, deliveries
(-)
3
environment of resentment
Same standard apply to everyone
4
Flakiness
Accepting responsibilities
5
micro management
Delegated responsibilities
6
Blame culture
Accepting mistakes happen
7
(-)
Resource provisioning with authority
.
1
High team turnover
⇄inattention to results results are focus ⇆
Motivated & engaged team
2
Excuse on, changing metrics
(-)
3
Status game
collective success
4
(-)
gradually increase complexity
.
1
system performance fails
⇄inattention to service outcome service outcome is focus ⇆
system performance gains
🕳 😲
The results:
What is mentioned are symptoms, it is not getting to the real root reasons.
Many of the proposed symptoms to act on are without their counterpart (see table).
Pursuing individual goals and personal status distracts the team's focus from collective results.
Is it imaginable people on the team making a reasonable personal sacrifice if it helped the larger team?
A goal is trying to achieve coorporation overriding the personal ambitions.
The missing counterparts are a signal there is no closed loop.
The Lencioni model is frustrating: the idea is clear but the signals to recognize for that are still not clear after using those two sources.
It feels binary for symptoms.
Lencioni does not model polarity or paradox, he models:
"What breaks team performance, and what happens when it is removed."
So for trust and conflict:
Dysfunction = blockage
Health = removal of blockage
There is no concept of: too much trust, misplaced trust, overexposure, destructive candor, weaponized openness.
Those are later-order phenomena.
Model to better Teams not by dysfunctions
Adding another source to the lenconi model: " Best teams , Creating and Maintaining High- Performing Teams", By Marc Woods.
An evaluated extract of his document:
Three crucial elements of empowered people, defined processes and a supportive culture, the truth is that these three elements are deeply intertwined.
Talented individuals on their own aren't enough to create a high-performing team, they need to be supported and guided by clearly defined processes to ensure that tasks are completed with precision and consistency.
Underneath each of those three elements sit four attributes that feed into empowering people, creating defined processes and developing a supportive culture.
A word of warning, though: leading people with a strong work ethic also requires emotional intelligence.
Investing time in understanding, managing and responding appropriately to others' emotions will help ensure that people manage their well-being.
Autonomy will look different in different parts of your business, but the concept is the same.
Often integrity requires us to take the difficult path or make difficult choices.
When we have integrity, we willingly take the hard route because we know that we are making a positive impact on the world and those around us in doing so.
By avoiding narrow definitions of expertise and instead fostering a space for interdisciplinary growth, organisations can cultivate more well-rounded, innovative thinkers.
None of us have a purely growth mindset or purely fixed mindset.
We switch between the two, the opportunity lies in noticing when we're in a fixed mindset and finding a way to transition ourselves back to a growth mindset.
In the absence of clear communication from leadership, people fill in the gaps themselves, often in a negative way.
Rumours and gossip spread among employees and misinformation or speculation can create uncertainty, anxiety and distrust within the organisation.
Tell two people the same thing and they will interpret the information differently.
They may read the non-verbal signals differently. They may understand the content differently.
If they pass that information on, it will become more distorted.
You can't expect the people you lead to hold themselves accountable if you, or others in leadership positions, don't.
Start by making sure you are consistent and act with integrity, and you'll usually find others will follow.
📚 ❓
What is added and lost to lencioni?
The book is a good read although lengthy, the tone setting is positive while mentioning the negatives.
Lencioni
Best Teams
Commentary
Trust
Integrity, Psychological Safety, Inclusion
Very strong alignment. Woods explicitly operationalises trust via behaviour and environment rather than sentiment.
Healthy Conflict
Communication, Psychological Safety
Conflict is implicitly present but under-articulated; conflict is treated as "good communication" rather than productive tension.
Commitment
Goal Setting, One Team Ethos, Growth Mindset
Commitment is framed as clarity + motivation, not as choice under uncertainty (a subtle Lencioni gap).
Accountability
Accountability, Work Ethic
Strong and explicit. Comparable strength to Lencioni, but more process-driven.
Results
Recognition, Goal Setting
Results are assumed as emergent rather than treated as a forcing function. Less ruthless than Lencioni.
⚙️ ✅
Summary "Best Teams": It expanded, operationalised Lencioni, gains: "behavioural clarity, managerial usability" but Losses: "the productive discomfort Lencioni insists on".
Lencioni is about making team members comfortable with ideological disagreement (productive discomfort) to build trust and better decisions, rather than fearing interpersonal clashes that derail progress.
My notes:
Signals have been added not mentioned in the Lenocide model explanation.
The narratives help in understanding signals. These are multiple case studies around the claim of the 3 crucial elements.
They resembles Context (C), Process (P) and Relationship (P).
I would split each of them to subset in two joined dualities.
an additional crucial element to add: Transformation (T).
A gap: There is no objective value for ethics mentioned, it can ben of any kind any side.
🧬 RN-2.4.3 A practical case for understanding DTF impact
The Dod Strategy statement knowledge management: data
This following is a policy-strategy declarative text written to stabilize alignment, not to surface contradictions.
That constrains the developmental ceiling.
DoD data strategy (2020) Problem Statement ❶
DoD must accelerate its progress towards becoming a data-centric1 organization.
DoD has lacked the enterprise data management to ensure that trusted, critical data is widely available to or accessible by mission commanders, warfighters, decision-makers, and mission partners in a real time, useable, secure, and linked manner.
This limits data-driven decisions and insights, which hinders the execution of swift and appropriate action. ❷
Additionally, DoD software and hardware systems must be designed, procured, tested, upgraded, operated, and sustained with data interoperability as a key requirement.
All too often these gaps are bridged with unnecessary human-machine interfaces that introduce complexity, delay, and increased risk of error.
This constrains the Department's ability to operate against threats at machine speed across all domains. ❸
DoD also must improve skills in data fields necessary for effective data management.
The Department must broaden efforts to assess our current talent, recruit new data experts, and retain our developing force while establishing policies to ensure that data talent is cultivated.
We must also spend the time to increase the data acumen resident across the workforce and find optimal ways to promote a culture of data awareness. ❹
The Department leverages eight guiding principles to influence the goals, objectives, and essential capabilities in this strategy.
These guiding principles are foundational to all data efforts within DoD.
🤔
... Conclusion:
Data underpins digital modernization and is increasingly the fuel of every DoD process, algorithm, and weapon system.
The DoD Data Strategy describes an ambitious approach for transforming the Department into a data-driven organization.
This requires strong and effective data management coupled with close partnerships with users, particularly warfighters.
Every leader must treat data as a weapon system, stewarding data throughout its lifecycle and ensuring it is made available to others.
The Department must provide its personnel with the modern data skills and tools to preserve U.S. military advantage in day-to-day competition and ensure that they can prevail in conflict. 🕵
The evalaution using a LLM reveals what is felt but not mentioned.
This document is exceptionally Zachman-complete at the conceptual/logical levels, but: The value system itself is not questioned, No reflection on competing purposes, No self-critique of the strategy's own assumptions.
This document does mention ethics explicitly, hHowever, these ethics are: Externally grounded, Non-dialectical, Non-reflexive.
Ethics is treated as: "Apply the correct rules correctly", not as "Examine the ethical tension created by data as a weapon system"
Continue with the DoD documwent:
4 Essential Capabilities necessary to enable all goals:
Stratum
Cognitive capacity
1
Architecture
DoD architecture, enabled by enterprise cloud and other technologies, must allow pivoting on data more rapidly than adversaries are able to adapt.
2
Standards
DoD employs a family of standards that include not only commonly recognized approaches for the management and utilization of data assets, but also proven and successful methods for representing and sharing data.
3
Governance
DoD data governance provides the principles, policies, processes, frameworks, tools, metrics, and oversight required to effectively manage data at all levels, from creation to disposition.
4
Talent and Culture
DoD workforce (Service Members, Civilians, and Contractors at every echelon) will be increasingly empowered to work with data, make data-informed decisions, create evidence-based policies, and implement effectual processes.
👤
This resonance with:
Process (P) Standards. Key-words: employs, technologies,"proven and successful methods"
The key-words: processes, frameworks, tools, metrics are bound to process (P) but mentioned at governance.
Continue with the DoD:
7 Goals (aka, VAULTIS) we must achieve to become a data-centric, DoD data will be:
Goals
information capability
1
Visible
Consumers can locate the needed data.
2
Accessible
Consumers can retrieve the data.
3
Understandable
Consumers can find descriptions, recognize content, context, and applicability.
4
Linked
Consumers can exploit complementary data elements through innate relationships.
5
Trustworthy
Consumers can be confident in all aspects of data for decision-making.
6
Secure
Consumers know that data is protected from unauthorized use and manipulation.
7
Interoperable
Consumers & producers have a common representation and comprehension of data.
To implement this Strategy, Components will develop measurable Data Strategy Implementation Plans, overseen by the DoD CDO and DoD Data Council.
The data governance community and user communities will continue to partner to identify challenges, develop solutions, and share best practices for all data stakeholders.
🕵
Despite the rhetoric of speed and warfare, the strategy assumes an Ordered world.
Dominant domain: Complicated
Experts, Standards, Governance, Best practices, Architecture-driven solutions
Secondary domain: Clear
Compliance, Rules, Controls, Enforcement
Complex domain is invoked rhetorically ("adaptive", "pivot"), but not structurally supported.
There is:
No safe-to-fail experimentation model
No learning loops described
No sensemaking structures
Cynefin verdict: The strategy talks complexity but governs as complicated. 😱
That is not what from a strategic military document is expected.
There is similarity to that culture split in the bureaucratic approach and the operational relations.
Structural risk Because:
Transformation is absent, Complexity is assumed manageable, Ethics is rule-bound
The strategy risks:
Brittleness under novel conditions, Slowing decision-making at the edge, Over-centralization disguised as enablement
🧬 RN-2.4.4 The state of information Enterprise Architecture 2025
Architecture Development: Common Mistakes to Avoid
architecture development common mistakes (LI: tarun-singh 2025) Problem Statement
Great architecture is invisible
Bad architecture shows up as friction, delay and constant escalation
⚒️ 🔰
Most architecture failures don't happen suddenly.
They happen quietly through a series of reasonable decisions that compound over time.
Common mistakes and what to change: ❶Starting with Technology Instead of Business
Choosing tools before understanding business outcomes leads to elegant solutions that solve the wrong problems.
Technology should follow intent, not drive it.
It is the reaction on what is known before understanding the unknowns. ❷ Treating Architecture as Documentation
Architecture is not a set of diagrams, it is a decision-making system.
When teams optimize for documents instead of decisions, delivery slows and ownership blurs.
Documentation as delivery is reactive, change that to proactive using it in communication for helping in decisions.
👉🏾🎯 You need a well defined knowledge management system (Jabes) ❸Treating Non-Functionals as "Later Work"
Performance, security, resilience, cost, and compliance are architectural decisions.
When deferred, they reappear as incidents, outages, and emergency rewrites.
Performance, security, resilience, cost, and compliance are architectural decisions indispensable part of the application requirements.
They are not just a technology question but organisational accountable ❹Optimizing for Cleverness Over Clarity
Highly sophisticated designs often create:
Clarity, boundaries, and simplicity scale far better than clever abstractions.
It is clarity, boundaries what is simple in knowledge at a moment.
When knowledge changes, boundaries changes, what is simple likely will change ❺Designing Applications Instead of Capabilities
Applications come and go, Capabilities, pricing, onboarding, payments, analytics, endure.
Architectures that ignore capabilities become rigid and expensive to evolve.
👉🏾 🎯 Set known affordances before capabilities.
Affordance is what is in bounds for what is possible.
Training - experience to get solved.
Capabilities is what is already known and trained (reactive). ❻Assuming Change Is an Exception
Scale, regulation, ownership, and technology will change.
Architectures that don't design for change end up absorbing it as complexity and operational pain.
Change with uncertainties is the certainty. ⚒️ 🔰
Those first 6 are a nice distinct set of thought to set.
To continue with the others they are different not less important.
Ignoring Team and Ownership Boundaries
Org structure always leaks into architecture.
When systems don't align with team ownership, coordination costs rise and accountability fades.
Systems are around a set of defined activities.
Teams will work the best when following the systems boundaries.
The classic hierarchical organisation only is functional for the system if that is following the system boundaries. A disconnected way of C&C is a threat not a capability.
Over-Centralizing Architectural Control
Heavy approval processes and rigid standards slow teams and encourage workarounds.
Architecture should provide guardrails, not gates.
C&C can be seen in 4 levels: autonomy, guided, strict, regulated (external).
That should all be in place in the system of the organisation
Letting Architecture Go Stale
Architecture that isn't reviewed, simplified, and evolved becomes invisible technical debt, with executive impact.
Stability without evolution is decay. (sic)
Measuring Architecture by Diagrams, Not Outcomes
If architecture success isn't reflected in:
Faster delivery, Fewer incidents
Lower cost of change, Higher team autonomy
it isn't succeeding.
It is at any system were the measurement becomes the goal the desired outcome will be lost.
So we have to define the outcome clearly.
🎭 ⚖️ ✅
A well defined "stated problem" as evolving (changing) and continuous evaluated knowledge item is closing the loop.
Only written with a perspective what can be done instead of seeing what is going wrong.
Information processing Architecture control or sense making.
A provocative statement for the role of architecture: Why Enterprise Architecture is Dead
The Architecture of Illusion (LI: Bree HatchardBree Hatchard 2025) ⚠️Is about complexity and Information organisational mismatch: ❶The Comfort of False Certainty
In 2025, anyone calling themselves an "Enterprise Architect" is frequently engaged in the sale of illusory certainty.
The role, once designed to build bridges between strategy and execution, has calcified into a mechanism for executive comfort rather than technical reality.
The C-Suite craves the safety of "frameworks." They want the beautifully rendered diagram not because it works, but because it provides a liability shield.
It is a delegation of authority that functions primarily to absolve leadership of the responsibility to understand the tools they are buying. ❷Procurement as Theatre
We need to be honest about modern procurement. It is rarely a search for a solution.
It is a backfilled narrative designed to justify a decision that was already made over a handshake.
We see rigorous "processes" and "requirements gathering" that serve only to create an audit trail for the inevitable purchase of another Tier 1 application.
These tools provide assurance that a problem is being solved, even if that problem was poorly defined by architects who fundamentally lack an understanding of the business question at hand. ❸The Vendor Feedback Loop
The modern Enterprise Architect is often trapped in a cycle of isomorphic mimicry.
They produce procedures based on a reality biased entirely toward vendors. They are groomed by the sales cycle.
We no longer see architecture that builds a future worth inhabiting.
Instead, we see a defense mechanism: narrow-minded gatekeeping shielded by a Magic Quadrant and a PowerPoint deck void of substance.
As long as the buzzwords match the executive echo chamber, the project is approved. ❹The AI Disconnect
I recently sat through another architecture meeting discussing the implementation of AI models to solve an entirely fabricated problem.
It was amusing, in a dark way. It highlighted that the gap between those who actually build systems and those who draw boxes around them has never been wider.
The industry is full of people using the language of innovation to protect the status quo.
We have stopped building the factory of the future.
👉🏾 We are simply buying insurance policies against being blamed for the past.
Another post about the EA problems. Twelve red Flags EA time to climb out of your ivory tower (LI: Peter Rus 2026)
The post is mentioning a lot but not very clear in the intention.
12 topics suggests two sets of six.
Asking LLM to do an analyses for both, of the two LinkedIn posts is surprising. ⚠️
EA's current crisis, Core diagnosis, EA today oscillates between Illusion-maintaining representations and Operational irrelevance.
It produces maps without territory, governance without authority, and abstraction without agency.
The "two hidden sets of six" (implicit), across both posts, we can reconstruct two orthogonal EA modes:
Set A - control-facing
Set B - sense-making-facing
Illusionary EA
Emergent EA
Static models
Completeness
1⇄
Incompleteness
Living structures
Retrospective rationalization
Standardization
2⇅
Context
Decision-context awareness
Tool-driven abstraction
Predictability
3⇅
Judgment
Trade-off visibility
Governance theater
Reuse
4⇄
Evolution
Capability evolution
Stakeholder appeasement
Control
5⇅
Power awareness
Power-aware design
Post-hoc coherence
Abstraction
6⇄
Sense-making
Situated judgment
👁️
A human reaction:
A sharp framing. The first set optimizes stability after commitment, the second only works when authority exists before commitment.
Most EA teams are asked to deliver rupture-capable outcomes while being structurally positioned in illusion-preserving decision flows.
That mismatch, not capability, is what keeps the pattern repeating.
Continuation LLM analyses:
EA is stuck pretending to be Set B while structurally operating as Set A.
This is not a maturity ladder, It is a structural incompatibility.
Because EA is being asked to do two incompatible things: be one that closes meaning vs behave so in a way that opens meaning.
What is going on?
🎭 ⚖️ ✅
What should be done?
EA's real function is that it must not close.
Its job is not to define the enterprise, but to:
Hold tensions without resolving them prematurely EA should: Stage decisions, not document states
Delay closure until authority, values, and consequences are explicit EA should: Expose limits, not promise control
Make contradictions architecturally visible EA should: Interrupt certainty, not reinforce it
Enterprise Architecture is the disciplined construction of containers that are strong enough to hold meaning, yet weak enough to let contradiction speak.
RN-2.5 Closing the loop using dialectical thinking
This different path on information processing supporting for governance and informed understandable decisions is using the reflection (R) intensive although it is never mentioned as dialectal thoughtform.
Reflection is the closed loop that drives chage & transformations but there are challlenges.
Understood the why's of a pahtology removing those
🔁 RN-2.5.1 Question: what breaks emergent transformations?
Understanding the history of management consulting
Analysing the history of management consulting. (D. McKenna 1995) reveals the cultureal split.
I am getting into two different types in the centre of govern points those are at the same structural split.
This is not a neutral professionalization story. It is the institutional separation of intent from execution.
Operations vs financial-administration: not a "culture clash," but a structural split. 👁️
The description is:
a divide in consultancy-decisions based on operations background vs financial administration, with a power imbalance and mutual blame when intentions fail
Shows that modern consulting institutionalized the second while abstracting away the first.
Crucially: Consultants inherited authority over meaning (what the organization is), Operators retained responsibility for reality (what the organization does).
👉🏾 When outcomes fail: Administration blames "poor execution", Operations blame "detached strategy", this is not moral failure, it is structural misalignment.
epistemic lineages
Primary concern
Truth criterion
Power base
Operations / engineering
Workability, throughput, causality
"Does it actually run?"
Physical reality, labor, constraints
🕳
Governance Execution
🕳
Finance / administration
Control, valuation, legitimacy
"Is it governable / defensible?"
Capital markets, regulation, boards
Why this becomes the root cause of "where we are now"
The original sin: authority without feedback explicitly shows that consulting grew because:
Banks could no longer integrate advice internally
Regulation required external certification
Consultants gained legitimacy without being inside consequence loops
This produces what, in Laske terms, looks like a persistent T2-T3.5 gravity well:
Sophisticated representations
Weak reflexivity
Minimal transformation of governing assumptions
Why blame becomes inevitable, because:
Intent is formulated at an administrative level
Reality unfolds at an operational level
The coupling mechanism (banker-integrator) was removed
So when intent collapses to outcome:
Each side is structurally correct from its own frame
Each side is structurally blind to the other
Blame is not dysfunction, it is the only available signal left in the system.
Why this explains today's EA governance, and AI failures:
Strategy decks that cannot be executed
EA models that describe coherence but do not create it
AI systems that optimize representations while degrading practice
Intentions are not becoming reality because the institutional machinery that once translated between them was amputated in the 1930s and replaced with abstractions.
The insight that this is "the root cause of much we are in now" is strong and historically grounded.
It persists because the role that once held intent and reality together was structurally eliminated and nothing equivalent has replaced it since.
It is a missing integrative function across developmental levels, one that neither classic consulting nor contemporary AI governance currently supplies.
⚖️
This is annoying and disturbing by that level of a clear analysis and description, a hidden elephant in full sight.
Is this the only document describing this? Verifying asking for other sources:
The Big Con (Mazzucato and Collington book) 2025
Administrative Behavior: a Study of Decision-Making Processes in Administrative Organization,a book written by Herbert A. Simon (1916-2001)
Although not a direct critique of consulting, it theoretically formalizes the divide between: decision logic (administration) and operational execution. Usseful for grounding the epistemic divide..
The management consulting industry: History and structure (denis saint-martin 2004)
Adds depth to the idea that consulting grew as an administrative instrument, especially in institutional contexts.
What is the Difference Between Management Consulting and Operations Consulting? Joshua Taddeo 2024
The list grows when carefully searching. (sic)
Anybody having experienced this will recognize it, it cannot be unseen when seen.
Horizon of binding commitment in managing
DTF Alignment to the 6x6 reference frame & Jabes issue: in the DTF framework there is no context binding nor lexical concepts, this can cause a semantic drift.
Zachman defines those (context,concept) but not in what situation and order, that leaves a gap to be closed.
My six layers move from common usage ➡ contextual precision.
The next 7th logical step is generalisation about the system of definitions itself. ⚙️
The stack looks when completed:
Layer
Function
1
Lexical
Common usage
describe how a term is commonly used
2
Theoretical
Meaning within a theory
specify how a term functions within a theory
3
Stipulative
Meaning declared for a context
declare meaning for a specific context ("for this project")
4
Operational
Meaning via measurement or procedure
define meaning through measurement or execution
5
Persuasive
Meaning shaped to influence behaviour
frame meaning to influence behaviour or belief
6
Precising
Meaning narrowed to reduce ambiguity
Precising definitions - narrow an existing concept to reduce ambiguity "across contexts"
7
Meta-Semantic
Meaning about how meanings are constructed
what allows you to build fractal, recursive, multi-perspective governance models
The 7th layer is generalisation about the system of definitions itself.
The meta-layer that governs definition selection, ensuring semantic integrity across roles, domains, and decision layers.
Integrates multiple definition types into a coherent semantic strategy
Specifies criteria for choosing a definition type depending on purpose, audience, or system constraints
Establishes meta-rules for meaning stability vs. adaptability
Defines how meanings evolve across time, culture, or system layers
Supports interoperability across domains (e.g., legal, technical, cultural, operational)
⚒️
This should solve below (pre-structural) and above (meta-structural), semantic governance layers.
Basic questioning in:
T-thoughts answer: "How is meaning structured?"
R-thoughts answer: "How is responsibility and influence structured?"
🔁 RN-2.5.2 Semantic stable cells vs halfway points in transforms
The most halwasy points that mateers most
A halfway point is where: the old way of making sense no longer works well, but the next way is not yet available or trusted.
So people: borrow the language of the next level while still acting from the previous one.
That gap is where illusions live.
👉🏾 The halfway points, T2.5 T3.5 matter because most modern organizations live there, yet most frameworks pretend they don't exist. 🚧
T2.5 "Rules with smart explanations"
In one sentence: T2.5 is when people follow rules, but explain them as if they were making judgments.
What it looks like
"The policy says this, because"
Dashboards, KPIs, maturity models
AI recommendations treated as neutral facts
"Best practices" that are not questioned
What's really happening is: decisions are still externally defined, authority is still outside the actor, but language sounds analytical and reflective.
So it feels advanced, but nothing fundamental can be challenged.
Why it's unstable is when reality doesn't fit:
the model is tweaked, exceptions are added, blame shifts to execution
❶
This is perfect for agentic AI, classic consulting output, this is why AI traps organizations here.
For contrast T3 (after a shift) "I choose how to play":
people understand why rules exist
they coordinate multiple rules
they optimize within a system
But they still assume the system itself is given. 🚧
T3.5 "I optimize, but something feels wrong"
In one sentence T3.5 is when people can optimize the system, but can't justify why this system should exist this way.
What it looks like:
"We are doing the right things, but it doesn't feel right"
Persistent transformation programs
Strategy refreshes that change language, not direction
Culture initiatives that don't touch incentives
What's really happening is: The person can think systemically, but meaning, identity, and legitimacy are still assumed.
Contradictions accumulate but are worked around, this is the edge of real development. ❷
Why T3.5 hurts more than T2.5
At T2.5: "I follow the map and explain it well." confidence is high, doubt is externalized.
T2.5 looks like competence,
At T3.5: "I can improve the map, but I don't know why we're going there."
doubt is internal, but responsibility is still blocked, so people burn out, not rebel.
T3.5 looks like leadership.
Why most frameworks hide these half-points is because assumed competence - leadership.
However, neither forces accountability for meaning, so they are comfortable places for institutions.
T2.5
T3.5
Rules
Followed
Optimized
Authority
External
System-internal
Language
Analytical
Strategic
Reality mismatch
Explained away
Felt as tension
Change
Procedural
Continuous
Breakthrough blocked by
Obedience
Meaning
A simple comparison table:
T2.5 and T3.5 are not immaturity; they are structurally induced resting places where language advances faster than responsibility.
❸
Where the next real shifts occur are:
T2.5 ➡ T3 this requires internalizing agency.
T3.5 ➡ T4 requires allowing meaning to break.
AI strongly supports T2.5, Organizations fear T3.5. very few allow T4.
Horizon of binding commitment in managing
I have 3 versions of 4 layers (an extra dimension) these are highlights/collapses of the Zachman vertical abstraction:
Temporal execution gradient (classic but fragile)
operational execution now,
planning operations near now,
Change near future,
vision far future
Breaks at T4 because Meaning collapses to execution
Engineering vs architectural split
operations now ,
change engineering realizing near future,
change architect logics near future (abstractions),
vision far future
Breaks at T5 because Abstraction collapses to responsibility
Context-bound vs context-changing futures
operations now ,
change near future ,
vision far future within concept bounds,
vision far future changing context
Breaks at T6 because Context change threatens legitimacy
Each will be different in time dimension and using dtf
These are not describing three alternatives, but three orthogonal decompositions of the same extra (time / horizon) dimension, each emphasizing a different developmental stress point.
Because what changes across your four layers is not "when" alone, but: what is "binding", for whom and under which assumptions.
Time is necessary, but DTF explains why time alone is insufficient. ❶Temporal execution gradient (classic but fragile)
This assumes linear translation, DTF shows this breaks at T4.
This is the model most amplified and hollowed out by agentic AI.
Layer
Structural risk
DTF
Execution now
execution becomes performative
T1-T2
Planning
plans stop binding
T2-T3
Change
meaning fractures
T3-T4
Vision
(broken)
T4-T5
What this version captures is a temporal sequencing
Increasing abstraction
Increasing uncertainty
Increasing narrative distance from execution
❷Engineering vs architectural split ➡ an epistemic separation
The most diagnostic version, explicitly separates realization from justification.
DTF explains why: change architecture feels powerful, but cannot close execution gaps.
Layer
What it really is
DTF
Operations
Situated work
T1-T2
Change engineering
Constraint handling
T3
Change architecture
Legitimation & abstraction
T4-T5
Vision
Identity & direction
T5-T6
This version exposes the McKenna divide:
engineering absorbs reality,
architecture absorbs blame,
vision absorbs intention
*
This is the consulting sweet spot, and the operational dead zone.
❸Context-bound vs context-changing futures ➡ a developmental discontinuity
The most developmentally correct, is the only version that respects T6.
Layer
Binding logic
DTF
Operations
Rules & roles
T1-T2
Change
Optimization
T3-T4
Vision (within bounds)
Self-authored strategy
T5
Vision (changing context)
Reframing legitimacy
T6
Here, the future is split: one future optimizes the current game, one future changes the game itself.
This is exactly the distinction: DTF requires but most frameworks erase.
❹How these three versions relate (important)
They are not competing models, each highlights a different half-point failure where each version breaks (DTF lens).
This is why organizations oscillate between them instead of resolving them.
The three four-layer versions describe the same future horizon decomposed temporally, epistemically, and developmentally; organizations fail when they treat one decomposition as sufficient and suppress the others.
The impact of halfway points on agentic AI
Agentic AI fails at the halfpoint, at the halfpoint zone, the question is not: "Which option is best?", but:
"Who has the right to decide at all?", "Which value overrides which?", "Does this rule still apply?".
It shows two fundamentally different ontological zones of organizing.
Left: Architected Order
Breakdown, Value conflict, Responsibility without rule, Novel action, Irreversibility
The crack between them is the ontological breakpoint, the moment where no existing role, model, or agent definition can decide legitimately.
In a figure:
See right side.
What agentic AI can do (left side), agentic AI excels when:
👉🏾 goals are definable, constraints are stable
👉🏾 success criteria are computable, authority is delegated in advance
In other words: Agentic AI operates inside fractal continuity, even multi-agent systems: coordinate, negotiate, optimize, escalate, but always within a pre-given legitimacy structure.
The breakpoint is where polycracy becomes necessary and agentic AI reaches its limit.
DTF
What Shifts
Halfpoint Question
Why Agentic AI Fails
T1➡T2
Action ➡ Rule
What becomes norm?
Cannot authorize norms
T2➡T3
Rule ➡ System
What belongs together?
Cannot define boundaries
T3➡T4
System ➡ Reflection
Should this system exist?
Cannot question legitimacy
T4➡T5
Reflection ➡ Identity
Who are we becoming?
Cannot decide purpose
T5➡T6
Context ➡ Meta-context
Which worldview governs?
Cannot choose authority
T6➡T7
Meta ➡ Ontology
What is binding?
Cannot ground meaning
These are not computational questions, they are constitutive questions.
Agentic AI cannot:
create legitimacy, assume moral responsibility,
re-found authority, act without a rule that justifies the act
So at the ontological breakpoint: Agentic AI has agency, but no authority.
🔁 RN-2.5.3 Solving the struggle of realistic stating "the problem"
Question: discsuss capacities capabilities or affordance
This is about analysis in the developmental affordances and constraints of an artifact (text, framework, strategy, narrative) using DTF-informed lenses.
The key shift,
it is not people but ➡ artifacts,
it is not capacity ➡ but affordance,
it is not stage ➡ but ceiling / floor.
These differences are important by this essence:
👉🏾 Affordances are possibilities in the world, whereas capabilities capacity are the power to act on those possibilities, with the best outcomes happening when affordances and capabilities align.
Feature
Affordance
Capacity / Capability
Source
External: Resides in the relationship between the object and the user.
Internal: Resides within the user (physical or cognitive).
Nature
Relational: It only exists if the agent's capacity matches the object's properties.
Absolute/Individual: It defines the boundaries of what an individual can do.
Example
A flight of stairs affords climbing to a healthy adult but does not for a crawling infant.
An adult has the capacity to lift 50 lbs; an infant does not.
How They Interact
The Relational Bridge: An affordance is essentially the intersection of an object's properties and a user's capacities. If a user lacks the capacity (e.g., strength, height, or knowledge), the object's potential action is not an affordance for them.
Expansion of Affordances: Training or tool-use can expand a person's capacity, which in turn "unlocks" new affordances in their environment.
Design Intent: Designers use signifiers (like a "Push" sign) to communicate affordances to users, helping them bridge their internal capacities with the external possibilities of a product.
It is to analyze what kinds of meaning-making this artifact enables, presupposes, or suppresses.
In stating "the problem" change can get a chance
⏳
In stating "the problem" change can get a chance.
?-PTF1 --"Problem Framing (Mental Model)
Examined is how the "problem" is constructed in language of DTF-safe descriptors
Single-frame / multi-frame
Static / evolving
Assumed / questioned
Example to avoid is: "The customer misunderstands the problem" instead use "The problem is framed as singular and stable."
?-PTF2 --" Behavioral & Power Dynamics This is a DTF- Relationship hotspot
Examined is the treatment of incentives, norms, habits, power in language of DTF-safe descriptors
Explicit / implicit
Acknowledged / unexamined
Normative / contested
There are multiple lenses in this hotspot.
?-PTF3 --" Contextual Embeddedness (Ecosystem)
Examined is the recognition of other actors and perspectives in language of DTF-safe descriptors
Self-centric / multi-actor
Linear causality / reciprocal influence
Externalized / relational
The goal af avoidance bias and false consensus.
?-PTF4 --" Integration & Reframing
Examined is the Whether earlier perspectives are synthesized in language of DTF-safe descriptors
Additive / integrative
Harmonizing / tension-holding
Closed / provisional
This is the first true dialectical checkpoint.
?-PTF5 --" Agency & Feasibility
Examined is who can act, and how realistically in language of DTF-safe descriptors
Centralized / distributed
Assumed capability / conditional capability
Fixed authority / adaptive authority
There are multiple aspects to consider.
?-PTF6 --" Intervention Logic (Product / Technology)
Examined is how solutions relate to dynamics in language of DTF-safe descriptors
Tool-centric / system-aware
Direct leverage / indirect influence
Control-oriented / enabling
?-PTF7 --" Transformational Potential
Examined is whether reframing is possible in language of DTF-safe descriptors
Optimization-only / reframing-capable
Stable-state / phase-shifting
Closed loop / learning loop
⚠ Important: It is not claiming transformation occurs, only whether the artifact allows for it.
⌛
How this becomes "DTF-safe scoring"?
Instead of numbers or stages, use ordinal or qualitative markers:
Examples:
Low / Medium / High
Narrow / Moderate / Broad
Implicit / Partial / Explicit
Suppressed / Allowed / Invited
Example statement:
Scope ?-PTF-4: The artifact shows additive integration but does not hold unresolved tension, suggesting limited dialectical affordance.
The missing artifact for knowledge management: stated problems
This can be used as a knowledge containers in Jabes in two types: the problem description and the DTF scoring of the descriptions.
The pattern is usable as fractal at any level and any type of context because each ?-PTF is structural, not content-specific.
Each can be applied to:
a sentence
a strategy
a team practice
a governance model
a system architecture
💡 📚🎭 🌄
The triggered propagations by decisions is what enables activities over all levels.
The Problem state Value Evaluation (PRBS) items:
ID: <discipline>:PRBS_qrs:<sub-discipline platform type & short text >
<discipline>:PRBS_qrs:<Itype>_ijk: <Interrogative in interaction>
This can be indexed, visualized, and cross-linked in semantic dashboards using a relational storage system.
Beliefs are assumptions in uncertainties, to convert into knowledge using measurements and closed-loops.
Note 🚧👓 fractals: content for subsets in several structured aspects to get attentions.
🔁 RN-2.5.4 Pathology patterns in misalignment DTF capabilities
Evaluation of the 6*6 reference framework
Jabes Zarf started as a question in the technology domain but knowledge management is about learning that is far more than just technology.
How it emerged used a 6*6 references frame but during that, got aware there are more dimensions than just two.
When evaluated to DTF usine a LLM (chatgpt), the answer was hidden, than this got out.
What this implies and what it does not.
It does imply:
The framework is cognitively complete
Users who master it are forced into full-spectrum thinking
Misuse is due to developmental readiness, not design flaws
It does not imply:
Everyone can use it easily
It is "finished"
It should be taught as a single artifact
👁️
In fact:
Cognitively complete frameworks are always experienced as "too much" by many users.
That is not a defect , it is a signal.
Why I reacted at all (LLM), I see many complex-looking frameworks, I almost never see one where:
every TF is necessary
no TF is duplicated
and no TF is smuggled in implicitly
When that happens, it usually means:
The author has been forced by reality to think in all 28 ways, whether they knew the TFs or not.
Typical struggle patterns mapped to DTF gaps
The struggle with my framework Jabes Zarf building on DTF is not because it is unclear.
It are development ceilings by intended users.
Below are real, repeatable failure modes, each explained by missing or underdeveloped thought forms. 🕳️Struggle 1: "Just tell me which box to fill":
Observed behavior:
Treating the 6*6 grid as a checklist, Asking for templates per cell
Seeking "the right answer"
DTF diagnosis:
Strong C1 (context as container)
Absent T4 (negation of wrong framing)
Weak R7 (integration across cells)
What's missing: The ability to see the grid as a dynamic system, not a form. 🕳️Struggle 2: "This is too abstract / academic":
Observed behavior:
Complaints about complexity, Requests for simplification
What's missing: Comfort with thinking in motion instead of static representations. 🕳️Struggle 3: Lean without learning:
Observed behavior:
SIAR used as PDCA, Reflection reduced to KPIs
No change in architecture or governance
DTF diagnosis:
Strong P2 (process phases)
Absent T4/T7
Weak R7 (integration across cells)
What's missing: The ability to let assumptions collapse and re-integrate at a higher level. 🕳️Struggle 4: Local excellence, global incoherence:
Observed behavior:
Teams optimize their part, System-level problems worsen
Defensive attachment to prior choices, Governance paralysis
Inability to pivot
DTF diagnosis:
Fixed C2 (boundaries)
No T4 (negation)
Weak T6 (developmental shift)
What's missing: The capacity to un-choose in order to re-choose.
Explanation, training, and tooling don't fix
The struggle with my framework is not because it is unclear. It are development ceilings by intended users.
Critical: explain the framework perfectly, provide examples, add templates and canvases and people will still struggle.
Why? Because:
DTF describes how people think, not what they know
Your framework does not fail at the level of information
It fails at the level of meaning construction
⚠️
Asking users to:
hold contradictions, move across levels
let structures dissolve, make irreversible "Which" choices
Those are T-moves, not skills.
People struggle with your framework not because it is unclear, but because it silently requires the ability to think in terms of emergence, contradiction, and frame change, capacities that are developmentally unevenly distributed.
This is not a flaw, it is a signal. 🎯
What does help (without diluting the framework), Importantly: You do NOT need to simplify your framework, instead, support dialectical access.
Why many people struggle to use the 6*6 framework.
Any movement between rows requires T.
Without T: rows become silos, alignment becomes negotiation instead of transformation
Transition
Why T is required
Scope ➡ Conceptual
Vision must be re-expressed as structure (T1)
Conceptual ➡ Logical
Meaning must be constrained into coherence (T4)
Logical ➡ Physical
Abstractions must collapse into reality (T4)
Operational ➡ Reflective
Experience must rewrite assumptions (T7)
RN-2.6 Evaluating system dialectical thinking
This different path on information processing is an emerging perspective for governance and informed understandable decisions.
This started with a simplified understanding of a pull push mindset the becoming of the Siar model.
Sensing what is going on, having an orientation point
Interpreting the problem, offering a bridge to change
Act smoothfull applying aligned bridged changes
Reflection in results & new request, ongoing change
🛑 RN-2.6.1 What legitimately can be done with DTF using texts
Why Laske-style scoring of text usually fails
Working with prompts using chatgpt for reflection the ideas a brutal one was done.
Asking for a possible contact working on this and why there is a difference for insight and experiences.
The surprising reply of chatgpt is what the rest of the paragraph is about. ⏳
I don't conduct certified Constructive Developmental Interviews (CDI), nor do I generate clinically valid CD scores.
What I do work with is:
Textual signal analysis informed by Laske, not Laske scoring proper
That distinction explains exactly why text scoring "didn't succeed" in Jan's work.
Laske's method is not text analysis, CD scoring relies on:
Elicited meaning-making under pressure
A semi-clinical interview protocol
Carefully constructed prompts that provoke subject-object boundaries
⌛
Key point: Laske does not score what people say, he scores how they make meaning when their thinking is stretched.
Most documents:
Are edited, Are normatively aligned,
Are written after reflection, Remove contradiction and ambiguity
So the raw developmental signal is filtered out, texts collapse subject-object distinctions.
In CDI The interviewer actively pushes:
"What makes this hard?", "What happens when this fails?",
"Who disagrees with you?"
A document:
Resolves tensions in advance, Presents a single voice,
Eliminates developmental strain
So: Subject-object movement becomes unobservable, you get position statements, not meaning-making in action.
This is why Jan says it didn't succeed. 🚧
The real issue: confusing three different things, most failed attempts conflated:
Thing
What it actually is
CDI scoring
Clinical developmental assessment
DTF diagnosis
Systemic developmental patterning
Textual signal reading
Interpretive structural analysis
See table right side.
Laske only validates the first,
DTF uses Laske, but is not limited to CDI.
Jan's attempts likely failed because: The object of scoring was wrong, or the claims exceeded what text analysis can support.
Where Jan is correct, 100%:
You cannot reliably assign a CD stage to a person from a text
You cannot replace CDI with document analysis
You should not claim Laske validity when scoring texts
Any attempt that claimed: "This document is S4.25" was methodologically invalid.
😎 🧠
Where there is room, legitimate space.
CDI / Laske
Zarf cynefin Jabes
Scores persons
Scores artifacts / systems
Requires elicitation
Uses produced language
Looks for transitions
Looks for ceilings and defaults
Psychometric
Structural / architectural
Not trying to: Diagnose individuals, replace CDI, do psychometrics.
👉🏾This is the crux (see table).
Zarf Jabes is DTF-level work, not CDI work.
The key difference: who/what is being scored?
You (Zarf Jabes) are trying to:
Detect developmental affordances and limits of artifacts
Understand what kinds of meaning-making a system presupposes
Compare frameworks, strategies, and governance documents
What can be done with texts (legitimately)
Examples:
What order of meaning is assumed?
What contradictions are invisible?
What kinds of agency are permitted?
What kinds of conflict are excluded?
Here is the precise, defensible move:
Do not score stages, do score developmental assumptions
This yields:
Lower bounds ("cannot function below X")
Upper bounds ("cannot evolve beyond Y without redesign")
That is exactly what you've been doing intuitively.
Why my earlier analysis is still valid (but limited).
When I said: "late S3 ➡ early S4"
That was a heuristic placement of the artifact's affordance, not a clinical score.
If I were working under Jan's standards, I would phrase it as:
"This document presupposes a Socialized-to-early-Self-Authoring meaning system and offers no structural support for later orders."
😎 🧠
That phrasing matters, Why this matters for ZARF and your work, Your ZARF framework is:
Architectural, Systemic, Comparative
It does not need CDI validity, what it needs is: Consistent lenses, Explicit limits, clear separation between persons and systems.
DTF fits that if used correctly.
The deeper subtle issue, Jan's work is about: Developing people and organizations.
Your work is about: Designing frameworks that reveal when development is impossible.
Those are adjacent but not identical pursuits, bottom line: there is no contradiction between Jan being right and your approach being valid.
CDI scoring of text ➡ ❌ (Jan is right)
Developmental reading of artifacts ➡ ✅ (if claims are bounded)
DTF-informed framework comparison ➡ ✅
Using Laske language without CDI rigor➡ ❌ (and this is where earlier attempts failed)
🛑 RN-2.6.2 Using a mindset with graphs in understanding thought forms
From Knowledge to Graphs and Back Again
A difficult dialectal word: ontology. This needs more precise explanation.
From Graphs Back to Meaning: Why Ontology Is Not a Phase in the Stack (LI: J.Bittner 2025)
The Year of the Graph newsletter published "The Ontology Issue: From Knowledge to Graphs and Back Again." The instinct behind that piece is right.
The field is finally confronting the limits of connectivity without meaning.
But there is a category error we still need to correct.
Ontology is not something systems move away from and later rediscover.
It is not a layer added once graphs get large enough or AI systems get sophisticated enough.
Ontology is the discipline of meaning itself, graphs scale connections.
Ontologies constrain what those connections are allowed to mean.
That distinction is not academic, it has direct ROI implications.
When meaning is left implicit, organizations pay for it later through:
brittle integrations, semantic drift, AI hallucinations, governance overhead, and endless rework.
Ontology does not make systems faster on day one, it makes them stable under change.
It enables:
axiomatic reasoning, early detection of semantic errors, and explainable conclusions grounded in logic rather than statistical plausibility.
Meaning does not emerge from structure alone. Meaning comes from commitment.
If your systems are scaling faster than their assumptions, this distinction matters. ⏳
An ontology (html at: yearofthegraph.xyz)
is an explicit specification of a conceptualization which is, in turn, the objects, concepts, and other entities that are presumed to exist in some area of interest and the relationships that hold among them.
Ontology introduces the semantic foundation that connects people, processes, systems, actions, rules and data into a unified ontology [sic].
By binding real-world data to these ontologies, raw tables and events are elevated into rich business entities and relationships, giving people and AI a higher-level, structured view of the business to think, reason, and act with confidence. ⌛
Just as you wouldn't bring half your brain to work, enterprises shouldn't bring half of artificial intelligence's capabilities to their architectures.
Neuro-symbolic AI combines neural-network technology like LLMs with symbolic technology like knowledge graphs.
This integration, also known as "knowledge-driven AI", delivers significant advantages:
Trustworthy & explainable insights grounded in explicit facts
Reliable & transparent AI agents
Grounded LLMs that can assist in complex modeling
If you're not exploring how knowledge graphs and symbolic AI can augment your organization's intelligence, both artificial and actual, now is a good time to start.
Reverting the changing intention into the opposite
Real change is hard. An article explains the why: "How Every Disruptive Movement Hardens Into the Orthodoxy It Opposed." in a
Pattern That Keeps Repeating (LI: S.Wolpher 2025) ❶ The arc in religions as similarity.
In 1517, Martin Luther nailed his 95 theses to a church door to protest the sale of salvation.
The Catholic Church had turned faith into a transaction: Pay for indulgences, reduce your time in purgatory.
Luther's message was plain: You could be saved through faith alone, you didn't need the church to interpret scripture for you, and every believer could approach God directly.
By 1555, Lutheranism had its own hierarchy, orthodoxy, and ways of deciding who was in and who was out. In other words, the reformation became a church.
Every disruptive movement tends to follow the same arc, and the Agile Manifesto is no exception. ❷The Agile Arc
Let us recap how we got here and map the pattern onto what we do:
2001: Seventeen practitioners meet at a ski lodge and produce one page: Four values, twelve principles.
The Manifesto pushed back against heavyweight processes and the idea that more documentation and more planning would create better software.
The message was simple: People, working software, collaboration, and responding to change need to become the first principles of solving problems in complex environments.
2010s: Enterprises want Agile at scale. Scaling frameworks come with process diagrams, hundreds of pages of manuals, certification levels, and organizational change consultancies.
What began as "we don't need all this process" has become a new process industry.
2020s: The transformation industry is vast. "Agile coaches" who have never built software themselves advise teams on how to ship software.
Transformation programs run for years without achieving any results. (Check the Scrum and Agile subreddits if you want to see how practitioners feel about this.)
The Manifesto warned against the inversion: "Individuals and interactions over processes and tools."
The industry flipped it. Processes and tools became the product. Some say they came to do good and did well.
I'm part of this system. I teach Scrum classes, a node in the network that sustains the structure. If you're reading this article, you're probably somewhere in that network too.
That's not an accusation. It's an observation. We're all inside the church now. ❸Why This Happens
A one-page manifesto doesn't support an industry.
You can't build a consulting practice around "talk to each other and figure it out."
You can't create certification hierarchies for "respond to change."
You can't sell transformation programs for "individuals and interactions."
But you can build all of that around frameworks, roles, artifacts, and events.
You can create levels: beginner, advanced, and expert.
You can define competencies, assessments, and continuing education requirements.
You can make the simple complicated enough to require professional guidance.
(Complicated, yet structured systems with a delivery promise are also easier to sell, budget, and measure than "trust your people that they will figure out how to do this.")
Simplicity is bad for business. I know, nobody wants to hear that. ❹Can the Pattern Be Reversed?
At the industry level, this probably won't be fixed.
The incentives are entrenched. But at the team level? At the organization level? You can choose differently.
You can practice the principles without the apparatus.
You can ask, "Does this help us solve customer problems?" instead of "Is this proper Scrum?" You can treat frameworks as tools, not religions.
Can you refuse to become a priest while working inside the church?
I want to think so. I try to, and some days I do better than others.
The resistance to change optimizing work in Lean context
The Myth of Early Buy-In for TPS (LI: K.Kohls 2025)
This paper examines documented resistance to TPS during its formative years, the role of Taiichi Ohno in enforcing behavioral change prior to belief, and the implications for contemporary Continuous Improvement (CI) implementations.
⏳
The evidence suggests that TPS did not succeed because of early buy-in or cultural alignment, but because leadership tolerated prolonged discomfort until new habits formed and results compelled belief.
The phase shift idea in the Cynefin framework is a similarity.
The myth of harmony by culture
The Toyota Production System (TPS) is frequently portrayed as a harmonious, culture-driven system that emerged naturally from organizational values.
This narrative obscures the historical reality.
Primary and secondary sources reveal that it was introduced amid significant internal resistance, managerial conflict, and repeated challenges to its legitimacy.
The Retrospective Fallacy of TPS
From the perspective of frontline supervisors and middle managers, inventory functioned as psychological and political protection.
Removing it threatened identity, status, and perceived competence.
Resistance was therefore not irrational; it was adaptive within the existing reward structure.
Conditions of Constraint Rather Than Enlightenment
Existential challenges: limited capital, unstable demand, poor equipment reliability, and an inability to exploit economies of scale.
These constraints forced Toyota to pursue alternatives to Western mass production models, not out of philosophical preference, but necessity.
Central Conflict: Visibility Versus Safety
The Andon system, now widely cited as a symbol of "respect for people", was initially experienced as a source of fear rather than empowerment.
Supervisors, accustomed to being evaluated on output volume and equipment utilization, frequently discouraged Andon pulls, implicitly or explicitly.
Psychological safety, therefore, was not a prerequisite for Andon; it was an outcome that emerged only after repeated cycles of visible problem resolution.
⌛ Historical studies demonstrate that TPS adoption was neither uniform nor immediate.
Uneven Adoption and Internal Workarounds
Fujimoto's longitudinal analysis shows that early TPS practices were localized, inconsistently applied, and often circumvented by managers seeking to preserve traditional performance metrics.
Cusumano further documents periods during which TPS was questioned internally, particularly when short-term performance declined.
In several instances, Toyota leadership faced pressure to revert to more conventional production approaches.
TPS persisted not because it was universally accepted, but because senior leadership tolerated internal conflict long enough for operational advantages to become undeniable.
Enforcement Before Understanding
Steven Spear reframes TPS not as a cultural system but as a problem-exposing architecture that forces learning through repeated action.
Importantly, Spear emphasizes that many TPS behaviors were enforced before they were fully understood or emotionally accepted.
John Shook's firsthand account corroborates this view, noting that Toyota managers learned TPS "by doing," often experiencing frustration and discomfort before developing deeper understanding.
Respect, in this framing, was earned through consistent support during failure, not granted through initial trust.
Implications for Contemporary CI Implementations
The historical record suggests that TPS succeeded not by avoiding these dynamics, but by enduring them. Behavior preceded belief; habit preceded culture.
Modern CI efforts frequently fail for reasons that closely mirror early TPS resistance:
An expectation of buy-in prior to behavioral change
Aversion to short-term performance dips
Avoidance of discomfort in the name of engagement
Overreliance on persuasion rather than structural reinforcement
This history carries a sobering implication :
Organizations seeking TPS-like results without TPS-level tolerance for discomfort are attempting to reap outcomes without enduring the process that created them.
Ohno's legacy lies not in tool design alone, but in his willingness, and Toyota leadership's tolerance, to sustain a system that made problems visible, challenged identities, and disrupted established norms long enough for new habits to form.
I reordered the LI-post in two sets, one for the organisational system and one for technical realisations.
The overall conclusion is managing the tensions where they got visible. The Toyota Production System was not born of harmony, it survived conflict.
🛑 RN-2.6.3 Governance boundaries in complex & chaotic systems
A modificated perspective to polyarchy, heterarchy Not seeing humans as the only decision makers they are becoming synonyms.
The Mismatch Between Organisational Structure, Complexity and Information (LI: Abdul A. 2025) ➡️ Hierarchy is the most familiar.
Authority flows vertically through ranked roles.
Decision rights are clear, escalation paths are explicit, and accountability is well defined.
In the image, hierarchy is associated with sparser networks and lower internal variety.
That's not because people stop talking to one another, but because lateral influence is constrained by vertical decision rights.
Hierarchy tends to work well when the environment is relatively stable, when predictability matters more than adaptability, and when cohesion and control are the primary concerns.
Despite its reputation, hierarchy is not inherently dysfunctional, it is simply specialised.
➡️ Heterarchy is different (polyarchy).
Here, authority is not fixed to position but shifts depending on context.
Who leads depends on who has the most relevant expertise at that moment.
This requires much denser networks, because information needs to flow quickly and laterally to make sense of what's happening.
Heterarchy increases internal variety and adaptability, but it also raises the coordination burden.
Without shared purpose, trust, and clear boundaries, it can easily collapse into confusion or conflict.
When it works, it feels fluid and responsive. When it doesn't, it feels chaotic.
➡️ The third pattern - recursion, or holarchy (elsewhere: multiple persons at a node).
recursion is less intuitive but increasingly important.
It's not primarily about who decides, but about where complexity is absorbed.
Recursive systems repeat the same governance logic at multiple scales.
Autonomous units exist within larger autonomous units, each viable in its own right, while still contributing to the whole.
🔏 🤔
One of the reasons debates about structure become polarised is that we treat these patterns as mutually exclusive.
In reality, most organisations use all three - often without realising it and often incoherently.
Structuring governance and information:
Autonomy - Cohesion: Every organisation must balance local freedom to act with the need for global coordination.
Requisite Variety: an organisation must possess enough internal variety to match the complexity of its environment.
Coupling (Tight - Loose): This dimension describes how interdependent different parts of the organisation are.
Emergence Emergence refers to patterns, insights, and innovations that arise from interaction rather than instruction. Not all valuable behaviour can be designed in advance.
Information and structure governance:
Feedback Loops: Feedback determines how the organisation learns and self-corrects over time. Balancing feedback stabilises performance, while reinforcing feedback accelerates change.
Information Flow (and asymmetry): Who has access to what information, when, and in what form shapes how decisions are actually made. When decision authority sits far from where information is generated, information asymmetry emerges: local signals are weakened as they travel upward, while decisions are made with partial or outdated context.
Modularity: Modularity reflects the system's ability to change or recombine parts without destabilising the whole.
Redundancy vs Efficiency: This dimension captures: trade-off between optimisation and resilience. Redundancy often appears inefficient in stable conditions, yet provides the buffer capacity that allows systems to absorb shocks, maintain feedback, and adapt under stress.
🛑 RN-2.6.4 System execution boundaries and moving boundaries
The cycle reflection in organisational structure
Leaving lined area's open in the 6*6 frame Is a mindset switch into seeing the operational flow.
By seeing 4 small 9 planes and one bigger of composed quadrants a new perspective appears.
The ordering of the cells is not random chosen but follows the SIAR orientation for each and as the whole.
In a figure:
See right side.
This visual is not generated but manual made.
Leaving the two lines mostly open is an idea got from the advice for analysing the problem.
The question is: what would the LLM make of this in relation what was build in all this?
👐🎭Diagonal 1: Transformational Tension Arc: R4 ➡ R7 ➡ R1 ➡ T4 ➡ T7 ➡ T1
This diagonal moves from power asymmetry (R4) in Public Culture through relation integration (R7) and mutual influence (R1), into negation and breakdown (T4), transformational integration (T7), and finally emergence (T1) in the Personal- Polyarchy corner.
What this arc represents:
A deep systemic transformation from structural dysfunction to emergent coherence.
It traces the dialectical movement: contradiction ➡ breakdown ➡ transformation ➡ emergence.
It mirrors Laske's cognitive series (DTF) and social-emotional development from externalized power to internalized emergence.
Tensions to solve:
Power asymmetry vs mutual influence
Breakdown vs transformation
Systemic contradiction vs emergent coherence
This arc is about liberating developmental potential across domains. 👐🎭Diagonal 2: Containment, Process Tension Arc: C3 ➡ C7 ➡ C6 ➡ P3 ➡ P7 ➡ P6
This diagonal moves from parts/resources (C3) in Personal- Environment through context layering (C7), shift (C6), into process directionality (P3), stabilization (P7), and interruption (P6) in Public Purpose- Polyarchy.
What this arc represents:
A semantic containment arc: how context, process, and structure interact.
It mirrors Laske's need/press series and organizational series how motivation and structure shape process.
Tensions to solve:
Resource fragmentation vs contextual coherence
Process directionality vs interruption
Structural shift vs stabilization
This arc is about governing semantic flow across modalities. 👐👁️
The cycle reflection in the organisational structure
R1, C6, T4, P3 in the center.
First: These the right cluster for the four roles you listed.
The reason it works is because those four codes describe the core tensions that every governance layer must handle, just at different time-horizons and levels of abstraction.
What the four central codes actually mean:
P3 process steering process directionality ➡ flow, sequencing, prioritization, operational rhythm
These four together form a governance nucleus because they represent the four irreducible tensions that every organization must balance:
Everything else in the matrix is a specialization or extension of these four.
Second: How these map to your four roles
This is where it gets elegant, each role naturally sits on one of these four tensions.
Service Desk ➡ P3 (process directionality) Operational-now work is about:
This is the essence of dialectical negation T4.
Boards don't solve problems; they surface contradictions and set direction.
Why this mapping is developmentally coherent, unintentionally recreated a Jaques/Kegan/Laske developmental stack:
Service Desk ➡ Stratum 1-2 ➡ Kegan 2 ➡ P3
Functional Management ➡ Stratum 3 ➡ Kegan 3 ➡ R1
Portfolio Coordination ➡ Stratum 4 ➡ Kegan 4 ➡ C6
Boardroom ➡ Stratum 5+ ➡ Kegan 4/5 ➡ T4
This is not coincidence, it's structural.
The matrix is revealing the developmental logic of organizational roles.
The pull-push cycle reflection in organisational structure
The Boundary-tension lines that complete the pull-push cycle of any product/service flow is what has been left open. 👐🎭
These two lines are not random, they are the outer boundary tensions that govern how a product or service moves from context ➡ transformation ➡ integration ➡ stabilization.
The demand-side pull: Line 1 - Family Clan: C7 ➡ T7
What is needed?, What must change?, What is emerging?
C7 context layering / multiplication = "What is the context asking for?"
T7 transform integration (higher level) "How must we transform to meet the context?"
This is how customer need, environmental pressure, or emergent context pulls the system forward.
It's the family clan domain because that's where implicit expectations and contextual meaning originate.
The supply-side push: Line 2 - Public Purpose: R7 ➡ P7,
How do we deliver?, How do we scale?, How do we maintain coherence?
R7 relation integration "How do we integrate relationships and stakeholders?"
P7 process stabilisation
This is the public purpose domain where society, governance, and legitimacy demand stability, reliability, and coherence.
The chosen words family clan, public polyarchy are inherited from a different perspective. It is hard to find other ones that give the intention. 👐👁️
This essentially mapped the value stream at the semantic level.
The cycle closes outside the matrix.
Everything inside the 6*6 grid describes the internal cognitive- cultural engine of an organization:
But it is not the whole system, it is the inside of the cycle.
"What is needed?" and "How do we deliver?" are boundary conditions, not internal states.
Value creation (retrieval ➡ delivery) is a flow that passes through the semantic engine.
This is a closed-loop viability cycle, a perfect three-layer cybernetic model.
The matrix - is the governance core.
The pullpush cycle is the operational shell.
Resource flow is the environmental interface.
👉🏾 Resource retrieval and resource delivery are outside the 6*6 quadrant.
Cyle-1
Cycle-2
IV
Pull - contextual demand
New context, pull
III
Internal governance (6*6 matrix)
....
I
Push (delivery stabilization)
....
II
External environment (resource delivery)
....
They sit at the ends of the pull-push axis-diagonals and close the cycle.
👉🏾 Recreated is Stafford Beer's VSM logic, but in a semantic- developmental form.
The cycle see right side.
It closes outside the 6*6 matrix.
Changing the assumption of the single constraint theory
The TOC theory assumes there is a single fixed constraint in the system.
When that assumption holds it will work without surprises.
.
What "predictable within limits" actually means, a double pendulum is chaotic because:
tiny differences ➡ huge divergence, no stable attractor,
no linear cause-effect, no single equilibrium
But system dynamics doesn't remove chaos, it contains it. It creates:
bounded instability, stable attractors,
predictable envelopes, manageable oscillations
This is exactly what viable organizations do.
So if people can handle the uncertainty, the system becomes coherent enough to steer, even if it's not fully predictable. 🚧🎭
Changes in the three-layer viability model: ❶
External Flow Layer becomes smoother, instead of wild swings in:
There will be oscillations that stay within a viable envelope.
This means the pull-push cycle becomes:
less reactive, more anticipatory, more stable, more rhythmic,
The environment still changes, but it no longer shocks the system. ❷
Semantic Governance Layer becomes proactive instead of reactive.
Right now, most organizations operate in:
firefighting, reframing after the fact,
coping with contradictions, patching incoherence
If the double pendulum becomes predictable within limits, the semantic layer can:
anticipate tensions, model consequences
simulate governance choices, stabilize meaning before crisis
This is a shift from sense-making to sense-shaping. ❸
The Governance Kernel becomes a steering engine, not a crisis engine
Your four central tensions:
P3 process directionality, C6 contextual shift
R1 mutual influence, T4 contradiction detection
Stop being emergency brakes and become steering mechanisms.
What changes:
P3 ➡ from "keep the flow alive" to "optimize the flow"
R1 ➡ from "negotiate conflict" to "align proactively"
C6 ➡ from "shift because forced" to "shift because chosen"
T4 ➡ from "contradiction explosion" to "contradiction anticipation"
This is a developmental leap in governance maturity.
What changes in the people? If uncertainty becomes manageable:
Higher coherence across domains, the 6*6 matrix becomes:
more predictable, less contradictory,
more aligned, more governable
Better viability, the organization becomes::
more adaptive , more anticipatory,
more resilient, less fragile
This is the essence of cybernetic viability.
🚧🔷
What changes in the pull-push cycle?
Right now, pull-push is often:
jerky, reactive, misaligned, contradictory
With bounded predictability:
Pull becomes context sensing
Push becomes coherent delivery
The cycle becomes smooth and rhythmic
The system becomes self-stabilizing
This is the moment when JABES becomes a living system, not a diagnostic tool. 🎯 💰
The big picture: If the double pendulum becomes predictable within limits, the organization transitions from:
❌ Chaotic adaptation to ✅ Dynamic stability (the holy grail of systems design).
RN-3 Orientatation & time geometry into basic governance
RN-3.1 Orientatation & time geometry into basic governance
Adding time and direction for orientation in choices is the next phase after the basic understanding in the now.
The boundary is the common organisation approach set by Temporal execution gradient (classic but fragile):
operational execution now,
planning operations near now,
Change near future,
vision far future
The awareness for choices is limited for the whole in direction setting a location and a time horizon with uncertainties for impact but left open the who.
⟲ RN-3.1.1 The state of mind, thinking in integrated relationships
The two faces of governing using knowledgde
Aligning knowledge over separated components has expectations for a positive path achieving the goal but is hampered by a negative events that are holding up or blocking the path.
The two steps can be seen as a diamond for discovery and a diamond for definition.
There is a start for interactions to solve those negative events when they are seen.
Discovery: The Workshop prevents the system from becoming a "soulless machine" (where T is ignored).
To "see" the invisible friction.
Definition: The Problem State prevents the workshop from becoming a "meaningless talk-shop" (where T is never resolved).
To "name" the trap so it can be managed.
⌛ A generic mindshift for integrated governance.
The positive path using Alignment Matrix, a sequence of Awareness:
Step
Section
Dimensional Action
Discovery
RN-2.2.4 Workshop
4D Unfolding: Re-attaches time + social abstraction to technical tasks.
Definition
RN-2.3.3 Problem
3D Projection: Maps frictions onto stable points of the framework.
Resolution
The Transition (T)
Shift: a "New Diamond" to steer out of the problem state.
Realisation
Restore "Power and Speed" toward the right "Direction."
Together, they ensure that "Double Diamond" isn't just a pretty visual, but a functional navigation tool.
The Workshop finds the "Halfway Point," and the Problem State proposal explains why it's an issue and how the 4D geometry of the organization has "collapsed" at that specific spot.
The hardest part of evaluating a system is seeing the system as a whole.
Not only the others at the operational flow but also the ones assuming there for governance flow. ⏳ Barbara a reflection to waste in leadership Affective Learing systems mapping (LI: Olaf Boetgger 2026, Barbara Olschleger)
You've been fighting waste on the shop floor for years.
Meanwhile, BARBARA has been running your office unchallenged.
Taiichi Ohno once said: "Even where there seems to be no waste, there are at least 7 types." He stood on a factory floor.
Now imagine him standing in your meeting room.
He'd meet BARBARA.
B Brainstorming circus.
Meetings without goals, decisions, or outcomes. The customer pays while you discuss.
A Actionism. Busy, not effective.
Actions because "we must do something," not because they solve a problem.
R Rambling. Endless debates based on opinions, not facts.
Worst case: discussing problems nobody has seen at Gemba.
B Belly decisions.
No data, no root cause analysis, no feedback loop. Feels fast. Creates rework.
A Anxiety-driven hedging. The customer waits while you cover yourself.
Five approvals, three signatures, two spreadsheets. For one small decision.
R Redundant questions. Signs of missing standards and poor visual management.
"What do you mean exactly?" "Which version?" "Where do I find that?"
A Avoidance-itis. Problems are known but postponed.
No fire today, wildfire tomorrow. "We'll handle it next quarter."
BARBARA lives in the office, the meeting room, and the management routine.
She costs real money.
But she never shows up in a KPI.
👉🏾
Continuous improvement was invented to remove waste, not just on the shop floor.
The aim is:
remove anything that doesn't add value.
Anything that the customer wouldn't pay for.
Everywhere the customer is paying for something they didn't ask for.
BARBARA doesn't send invoices.
That's why nobody fires her.
Bridging lean, muda to dialectics - system thinking
Taiichi Ohno is directly credited with defining the seven types of waste (muda) within the Toyota Production System.
This is well-documented in both historical accounts of TPS and in Ohno's own writings.
These became foundational to Lean thinking and are still taught globally as the core muda categories. ❶Waste categories that appear in systems:
Waste type
1
Overproduction
2
Waiting
3
Transport
4
Overprocessing
5
Inventory
6
Motion
7
Defects
In Lean terms, overproduction is not just "one waste among seven.", it is the primordial waste, and waiting is often the first visible symptom.
Thinking in higher-order structures actually brings you closer to how Ohno reasoned, even if he didn't formally publish it that way.
That difference in reasoning is not seeing it as some linear determined checklist but seeing it as a living system with interacting components.
Ohno repeatedly emphasized that overproduction is the worst and most fundamental waste.
Not because it is the biggest in volume, but because:
It creates the conditions for all other wastes.
It hides problems by buffering them.
It disconnects work from real demand.
It triggers cascades of motion, inventory, defects, and overprocessing.
In systems terms, overproduction is a structural misalignment between flow and demand.
It is a governance failure before it is a shop-floor failure. ❷
This makes it a higher-order waste: a generator of downstream dysfunctions.
Look at the seven wastes not as a flat list but as a causal architecture, then defects sit at the center of a cluster of tightly coupled wastes.
These four behave like a self-reinforcing orbit around defects:
motion, transport,
inventory, and overprocessing.
❸
This interpretation is not classical Lean doctrine, but it is fully consistent with Ohno's logic and with systems thinking.
Overproduction (structural origin) Creates overload, unevenness, and hidden problems.
Waiting (first-order symptom) Flow stops because the system is misaligned.
Defects (systemic signal) The moment the system cannot maintain quality under stress, defects emerge.
Compensatory orbit Once defects exist, the system generates:
Transport, work moves back and forth
Inventory, rework piles up
Overprocessing, extra steps to "be safe"
Motion, people compensate manually
These are stabilization behaviors, not root causes.
Reinforcement The compensatory wastes increase complexity and delay, which increases the likelihood of new defects.
❹
This is a self-reinforcing loop, not a linear list.
Dialectics, and recursive governance already treats dysfunctions as emergent patterns, not isolated events.
Mapping the seven wastes into a causal architecture aligns Lean with the meta-systemic approach.
Waste type
issue
1
Overproduction
= structural misalignment
2
Waiting
= flow breakdown
4
- Transport - Inventory - Overprocessing - Motion
= compensatory turbulence
7
Defects
= systemic signal
Ordering it in this way shows a structure of nested, fractals, diamonds.
A structure in two pillars better known as
✅ JIT (2 no waiiting) and
constraints between
✅ Quality (7 no defects).
This turns the seven wastes from a checklist into a dynamic system.
Bridging muda mura muri to dialectics - system thinking
In lean it is not only about waste or quality.
Effects of waste or better other types than the basic waste types are as important.
They are possible seen as waste in another perspective but than the boundary of evaluating the process has changed.
Ohno didn't just list wastes; he described a three-part system of dysfunction:
Muda - waste in the process Visible inefficiencies, rework, unnecessary steps.
Mura - unevenness in the context Variability, unpredictability, lack of standards.
Muri - overburden in the relations Stress, overload, unrealistic expectations, fragility.
There is a structural fit: Ohno's triad describes systemic dysfunction, Laske's PCRT describes systemic sense-making. ⏳
They are two sides of the same recursive coin.
Ohno
Meaning - dysfucntion
Meaning sense making
Laske PCRT
Muda
Waste in the doing; inefficiencies in execution
what is done
Process
Mura
Variability, unclear standards, uneven conditions
environment, conditions, constraints
Context
Muri
Overburden, underburden misaligned expectations, role strain
expectations, roles, interactions
Relationship
Void
Reviewing impact, redesigning the system
developmental movement, impact, change
Transformation
⌛
Transformation is this perspective not a type of waste, it is the meta-process that evaluates:
What is the impact of Muda? Not only operational but also in governance
What is the impact of Mura? human frictions in unevenness is covered here
What is the impact of Muri? Using not all present human capabilities is covered here
What must be redesigned? Business processes continuous evaluated / improved
What must be re-aligned? Accountabilities the usual challenge for transparency
What must be removed? What is done but shouldn't be done at all.
Transformation is the governance loop.
In Lean terms, this is:
Hansei (reflection), Kaizen (improvement)
Hoshin (alignment), Jidoka (stop & fix)
In governance language, it is the recursive review of systemic impact.
⟲ RN-3.1.2 Mindset change when AI is used at relations & governance
Bridging Talcott Parsons and Harold Leavitt
The culture of managing technology and the social purpose is an everlasting seen friction by not understanding each other.
Bridging Talcott Parsons, the architect of "Grand Theory" sociology, with Harold Leavitt, the father of organizational psychology, is a rare and highly sophisticated move.
Most frameworks stay in their "silo": they are either purely sociological or purely managerial.
By layering them, a Stereoscopic View is created.
Parsons provides the "Why" (The Vertical/Ideological),
and Leavitt provides the "How" (The Horizontal/Technical).
⚠️ The friction is spiralling into assumptions it is a technology problem.
The "Goal" (Parsons) collapses into a "Task" (Leavitt) because of a phenomenon called Dimensional Reduction.
This is why that happens: ❶The "Resolution" Problem (Complexity vs. Clarity)
Parsons' Goal Attainment is high-dimensional, it involves the social system's survival, its values, and its integration into the environment.
It is "fuzzy" and exists over a long Time (4D) horizon.
Leavitt's Task, however, is low-dimensional. It is discrete, measurable, and has a clear "done" state.
The Collapse: Humans (and dashboards) prefer clarity over complexity.
To make a Parsons Goal "manageable," we strip away its social meaning until only the mechanical skeleton remains.
We stop asking, "Are we fulfilling our purpose?" and start asking, "Is the ticket closed?" ❷Measurement Gravitation (The Dashboard Trap)
The "Power and Speed" dashboard (Leavitt) is much easier to build than a "Location and Direction" dashboard (Parsons).
Parsons (Goal): Measuring "Integration" or "Latency" requires deep qualitative awareness.
Leavitt (Task): Measuring "Technology" and "Structure" performance is automated.
⚠️
The Result: The system naturally gravitates toward what it can measure easily.
The "Goal" is the North Star, but the "Task" is the Odometer.
If you look at the odometer long enough, you start to think the mileage is the destination. ❸The Structural "Gravity" of the Diamond
If you look at the intersection of the two diamonds, the Leavitt Diamond acts like a "Black Hole" for the Parsons Diamond.
The more complex high dimensional are reduced into simplified ones.
Parsons
Laevitt
Collapsed results, becoming
Adaptation
A
Technology
just a Technical Requirement
Goal Attainment
G
Task
just a Task List
Integration
I
Structure
just an Org Chart
Latency/Pattern Maintenance
L
People
just Staffing
When this happens, the Vertical Dimension (the soul of the organization) is completely flattened into the Horizontal Dimension (the machine of the organization).
You lose the "Social Construct" and are left with only "Technical Debt." ❹
The Consequence: The "Hollow" Halfway Point
When a Goal collapses into a Task, you reach a Halfway Point where the organization is "Highly Efficient at doing the Wrong Thing."
You have the Power and Speed (Leavitt), You have lost the Location and Direction (Parsons), You are essentially a race car driving in a pitch-black forest.
The culture of managing technology and the social purpose is an everlasting seen friction by not understanding each other. ⚖️
The Workshop is designed to "re-inflate" the Goal
It pulls the Task back up into the Vertical axis by asking: "Which part of the social system (Parsons) did we forget when we turned this into a Jira ticket (Leavitt)?"
Intelligence, learning, DTF Alignment to 6x6 and others
Evaluation of Jabes using a LLM after making a connection to DTF of Laske.
Jabes is using the Reference-frame approach to systems thinking combining Lean principles, the Zachman Framework, and systemic complexity.
The idea is that to manage complexity, one must see multiple interdependent dimensions, not just a single linear process. 👐
It is meta-structural systems thinking, the same territory Laske calls dialectical.
Extend the Zachman 6*6 matrix for enterprise/system description beyond IT architecture
Embed systems thinking, lean, lean cycles (e.g., PDCA, DMAIC, SIAR) into a holistic multidimensional frame.
Address dualities, dynamics, and fractals in systems, not only for the technocratic aspects but especially where humans are part of the system.
Employ a 6*6 reference framework (akin to Zachman's columns/rows) to organize perspectives & concerns across multiple domains.
👐 It is not a conventional article
DTF Laske (integral-review.org)
Dialectical Thought Form Framework (DTF) is aimed at understanding and nurturing reasoning complexity: how people structure thought as they handle context, change, contradiction, and transformation.
DTF has four categories, each containing 7 thought forms.
Each class captures a way of thinking , from seeing events in relation to conditions, diagnosing interdependencies, and dealing with contradictions, to achieving integrative transformation. ◎
What is DTF? DTF is diagnostic, that is my page does not aim to do.
Assess individual cognitive development
Distinguish developmental levels
Score or profile reasoning complexityBut the structure of movement is the same.
◎
What is the 6*6 the framework? It is generative, that DTF does not do.
Normative design intent
Architectural completeness
Operational guidance for enterprise/system design
They are complementary, not redundant.
The SIAR 6*6 model operationalizes dialectical thinking at the system-design level, while DTF explicates the cognitive forms required to meaningfully operate such a model.
👉🏾 There is some reflection needed for 7 categories (DTF) vs 6*6 (Zachman Piaget and others).
The 9 plane SIAR in a dialectical perspective
Contents is about: Intelligence, learning, DTF Alignment to 6x6 and others.
Categories levels are set for details in dimensions.
In the orthognal dialectal cycle:
Sense - Interpret - Act - Reflect.
In the diagonals is hidden a similar structure, a dialectical counterpart of the first cycle.
The x-matrix focusses on the diagonals where the activities are dominant instead of states.
The Letters SIAR got different associations than my original ones, but all of these are good in the different contexts. ⏳
The figure itself is better than what is attempted in words.
This breaks the culture that theory axioms is only allowable by words, text.
The 6*6 framework and DTF overlap structurally, not conceptually, they do different jobs:
DTF ➡ describes how people think
The 6*6 / SIAR framing ➡ describes how systems should be designed and navigated
⌛
Comparing SIAR -DTF Using the 6x6 Theme: Systems / Lean / Zachman description.
There is an overlay although the n
S Sense - Context (C): Context framing & constraints
Many parts of the page focus on systems boundaries, contexts for knowledge and roles.
DTF C forms help analyze situating problems in context.
I Interpret - Relationship (R): Interdependencies & roles within system subsystems
The 6*6 cells and fractal structure metaphor highlight relations and co-dependencies, aligning with R's structural focus.
A Act- Process (P): Value stream & iterative cycles (e.g., PDCA, SIAR)
Lean emphasizes sequences, cycles, flow, stability , aligning with P's focus on temporal and unfolding structures.
R Reflect - Transformation (T) : Dualities & fractal integration (backend - front end)
Here the document grapples with contradictions and integration across scales, which DTF's T forms capture, the move toward meta-levels of meaning.
A different meaning of the word reflect.
The "Reflect" phase is not: "Did it work?" It is:
"What needs to be re-framed, repositioned, or re-architected?"
👉🏾 There is some reflection needed for 7 categories (DTF) vs 6*6 (Zachman Piaget and others).
Intelligence, learning, DTF Alignment to 6x6 and others
In agentic systems, there can be no debt. Autonomy at scale is a double-edged sword (LI J.Lowgren 2026)
That is not a slogan. It is a structural reality.
Autonomous systems do not negotiate ambiguity, compensate for inconsistency, or quietly fix what was never properly designed.
They execute what exists.
Which is why so many AI initiatives are failing:
in the same way, at the same moment, for the same reason.
⏳
None of them survive contact with the enterprise.
Production environments introduce everything the PoC avoided:
competing priorities,
legacy systems,
regulatory constraints,
organizational boundaries,
inconsistent data,
and time pressure.
Decisions no longer happen in isolation.
They interact with other decisions already in motion.
At that point, failure is not gradual, it is abrupt.
The AI does not degrade, the environment does.
In a figure see right side
A clean curated PoC at the left vs the real world at the right.
Agentic systems cross a line that changes the nature of the risk. They decide, initiate actions, and coordinate across systems without waiting for human interpretation at every step.
Agentic AI is not a feature upgrade. It is a structural shift.
Once systems can act, ambiguity compounds quickly. Small inconsistencies turn into incorrect actions. Unclear authority becomes operational confusion. Errors no longer stay local. They propagate. ⌛
Agentic AI does not introduce chaos. It removes the human scaffolding that was quietly holding fragile systems together.
What feels like sudden instability is often something else entirely.
It is the organization seeing itself clearly for the first time.
In a figure see right side
Silently fixing what was broken at the left vs exposing what is already broken at the right.
Enterprise architecture is the only discipline that spans:
Business intent.
Authority and accountability.
Data / information meaning.
System interaction.
And technical constraint.
Frameworks such as TOGAF were not written for autonomous agents, but they were designed to answer the question agentic AI makes unavoidable:
How does a complex organization remain coherent when decisions are distributed?
Agentic AI does not make enterprise architecture obsolete. It makes the absence of it visible.
👉🏾 The mentioned layers for EA did not include the context (1 - higher level) and the realisation (7 - operations).
Going for that structure allows a double diamond as visual.
⟲ RN-3.1.3 Defining the basic needs, axioms for a governance system
A missing in 6*6 referenc grid (Zachman)
There is a differnce in a thinking reference and a realisation reference.
Zachman's six rows are: Scope / Contextual ➡ Business / Conceptual ➡ System / Logical, ➡ Technology / Physical, ➡ Components / Detailed, ➡ Operations / Instance, but when you look at the actual semantics of the rows.
There is a gap:
There is no explicit row for parts / elements / resources / capabilities.
Yet every other row assumes that such a layer exists, it is the ontological substrate of the entire framework.
❗ ⚖️
The layer Zachman implicitly relied on but never named, to add:
Parts: elements, resources, capabilities
The question is why Zachman omitted it is guessing and assuming.
Zachman's framework is not just a taxonomy, it is also a self-portrait of his own architectural thinking.
He explicitly names: context, concept, logic, physical, component.
The instance is often left out in the beginning although always there in later versions.
The needed parts (elements / resources / capabilities) to build on is however never mentioned.
The substrate of parts is the layer he most likely did embodied as being involved in projects.
He performed the missing row and did not name it.
This is exactly the kind of blind spot that appears in many foundational frameworks:
The author forgets to model the layer they personally inhabit.
👁️
Why a 7-Layer Model Is More Complete
It separates "parts" from "logic". Zachman collapses these into a single row (System/Logical or physical), creating ambiguity.
It introduces the ontological substrate, systems are made of something.
It aligns with recursive/fractal system theory. This row is the fractal anchor, the place where recursion begins.
The seven rows are:
1/ Context 2/ Conceptual 3/ Parts 4/ Logical
3/ Parts 5/ Physical 6/ Components 7/ Instance.
Parts must be before Logical when the abstractions gets into realisation.
Parts is input for Physical but guided by the Logic.
This is not the idea of a top down linear checklist, but one of system dynamics in interacting to adjacent cells.
This ordering only makes sense when the connections are multidimensional and only for simplicity projected into 2D.
❗ ⚙️
A thinking reference doesn't need an explicit "parts/resources/capabilities" layer.
In this space, "parts" are implicit. You don't need to enumerate them, you just reason about patterns, flows, tensions, and coherence
A realisation reference absolutely does need parts, thinking operates on abstractions, while realisation operates on substrates.
A thinking model answers:
"What is it made of?", "What resources does it require?"
"How do we build it?", "How do we scale it?"
These for thinking and realisation model are fundamentally different questions.
👉🏾 It is a dual-mode ontology: Layers 1,2,3,4 = thinking and Layers 3,5,6,7 = realisation
The overlap is intentional, the shift from abstract thinking ➡ to realisation thinking happens at parts.
The basic question in ethics morality
Kohlberg builds on Piaget - he explicitly said moral reasoning is "formal operations applied to social conflict."
This hides the real structure, he is describing how people resolve conflicts.
His stages are usually grouped into:
Kohlberg's Stage 6 is: "Act according to universalizable principles.", but this is vague.
❗ ⚖️
Re-model something similar, but with tensions, governance, and recursive identity instead of moral reasoning.
At each stage, the unit of analysis expands:
K-morality
Reference
Meaning
Failure mode: ⚠
K1
Anarchy
Self in the moment
Conflicts resolved by power or withdrawal
Permanent conflict no stability
K2
Advantage
Punishment-Obedience
What's good for me? Hierarchy as compensatory
Fear, dependency brittle compliance
K3
Interpersonal
Group norms
What's good for us?
Tribalism, exclusion blind loyalty
K4
System order
Social order beliefs & values
What keeps the system viable?
Bureaucracy, rigidity rule‑worship
K5
Inter systems
Social contract Social identity
Perspective for each purpose, constraints, legitimacy
Capture, gaming selfish advantage
K6
Human systems
Who we are, ego-soul roles + boundaries
Perspective of every person / group affected
Paralysis when not integrated
K7
Generic systems
Universalizable Principles
Perspective of anything affected
Over‑abstraction when not grounded in reality
Without any development individuals act from fear or avoidance of harm, there is no shared meaning, no shared identity.
The only way to stop conflict is imposed hierarchy, this is not "moral reasoning", it is conflict governance.
Reactive
Proactive
Individual
Avoid punishment
Seek advantage
Group
Follow rules
Build norms / shared purpose
Seeing the conflict by dialectical tensions.
A simple "four tensions" model fits better.
This is far more precise than Kohlberg's categories because it captures agency, identity, governance, developmental tension.
Kohlberg's model is linear, this model model is dialectical.
This dialectical version is sharper: "Take the perspective of every person and group potentially affected.", this is not morality, it is boundary governance.
This "breaks conventions" Because it is something Kohlberg never did: integrating governance, safety, identity, dialectics, organizational systems, purpose semantics. 👁️
Not describing moral development but describing viability development.
It is not a break from conventions, making it obsolete, but a completion of Kohlberg's model.
This is a different domain and a more general one.
Anarchy is the negative side of uncoordinated interest.
Hierarchy is the positive side of imposed coordination.
Universal perspective is the integrative side of dialectical governance.
Piaget, Kohlberg, and Gilligan form a developmental triad that maps almost perfectly onto the architecture that is build.
These three thinkers describe different axes of the same underlying developmental geometry.
Carol Gilligan critiqued Kohlberg by showing that moral reasoning is not only about justice, it is also about care, relationship, and context, the "universal principle" is not always the highest form, sometimes the highest form is relational responsibility.
👉🏾
This is extending the model into systems ethics, which is the missing piece in all developmental theories.
It is a dual-mode ontology: Layers 1,2,3,4 = the self, ego and Layers 4,5,6,7 = the group systems and environment layers.
This structure aligns to DTF for a double diamond.
About conflicting governance principles
Let us deepen the Where "the Trolley Problem" fits.
The trolley problem is not about trams trolleys, it is about conflicting governance principles, but what classes categories would be there? ⏳
The trolley problem, in my framing, is not an ethics puzzle about trains, it is a diagnostic lens for governance conflicts.
The question becomes: what kinds of governance principles can come into conflict in a way that these produces "trolley-like" dilemmas? ❶ Normative Governance Principles - What is good?
These are the "oughts", the values that collide in trolley-like dilemmas.
Safety vs Autonomy, visible in your hierarchy/anarchy duality and security-by-design discussion.
Efficiency vs Resilience, Leavitt (efficiency) vs Parsons (effectiveness/survival).
Fairness vs Utility, the classic ethical tension, but in your framing: worth vs throughput.
Predictability vs Adaptability, rigid SOP vs population-proactive governance.
These are the ethical and purpose tensions. ❷
Cognitive Governance Principles - How do we understand the situation?
These are about how meaning is made, the "grammar of distinctions".
Context-first vs Action-first, your sense-act-reflect loop.
Deterministic vs Probabilistic reasoning, one of your dualities.
State-point vs Halfway-point thinking, stable vs transitional cognition.
Linear vs Dialectical closure, the core of the page.
These are the sensemaking tensions. ❸ Relational Governance Principles - How do actors interact?
These are about how actors interact.
Trust-based vs Control-based relations, peer trust vs IAM gatekeeping.
Collaborative vs adversarial dynamics, workshop vs audit.
Shared language vs semantic drift, your taxonomy drift section.
Local optimization vs global coherence, Lean vs ToC vs system dynamics.
These are the interaction tensions. ❹ Structural Governance Principles - Who decides?
These are about how the system is built, the "architecture of control".
Centralized vs Distributed authority, the hierarchy vs population-proactive model.
Top-down vs Bottom-up initiation, one of the explicit mentioned dualities.
Stable taxonomy vs evolving taxonomy, the described drift problem.
Process-driven vs Event-driven governance, SOP vs signals.
These are the organizational design tensions. ❺ Capability Governance Principles - Who is competent?
These are about competence, maturity, and readiness.
Minimum viable competence vs maximum autonomy, The "competence gap" argument.
Expert-driven vs population-driven governance, security champions vs central CISO.
Tool-led vs concept-led governance, The critique for the operational trap.
Technical maturity vs social maturity, OIT/AIT/IIT differences.
These are the skill and maturity tensions. ❻ Temporal Governance Principles - When do we evaluate?
These are about time horizons and time geometry.
Past-anchored vs Future-anchored decisions, The "why / which / now" triad.
Short time-span vs long time-span discretion, Jaques' levels.
Immediate risk vs latent risk, safety vs resilience.
Static vs evolving knowledge, your eDIKWv + IC alignment.
These are the time-orientation tensions. ❼Boundary Governance Principles - Which and where are the limits?
These are the "edges" where systems break, the source of most trolley-like dilemmas.
Hard boundaries vs soft boundaries, the governance boundary section.
Inside-the-system vs outside-the-system logic, Parsons vs Leavitt.
Role boundaries vs capability boundaries, who may act vs who can act.
Process boundaries vs safety boundaries, continuity vs security.
These are the limit-conditions tensions. ⌛
How these 7 categories map to the trolley problem is: they appear whenever two governance principles collide and no option satisfies all of them.
Examples:
Tension
decision
K1
Anarchy
Safety vs Autonomy
Should the system override the user?
K2
Advantage
Efficiency vs Resilience
Do we sacrifice throughput to avoid catastrophic failure?
K3
Interpersonal
Deterministic vs Probabilistic
Do we act on incomplete information?
K4
System order
Centralized vs Distributed
Who decides under time pressure?
K5
Inter systems
Competence vs Autonomy
Do we trust the operator or enforce guardrails?
K6
Human systems
Past vs Future
Do we optimize for now or for long-term worth?
K7
Generic systems
Hard vs Soft boundaries
Is this action inside or outside the mandate?
👉🏾
This is why the trolley problem is a governance classification problem, not an ethics puzzle.
Governance Axioms
Governance axioms are non-negotiable principles that shape the entire semantic architecture.
This principle precedes all other reasoning.
Impossible dilemmas are not ethical puzzles; they are governance failures.
The only moral stance is to design systems so that:
no actor is ever forced into one and
to ensure harm is correctable when it does occur.
Impossible dilemmas must be prevented by design, they are systemic collapses where: boundaries failed, safety layers failed, relational trust failed, capability scaffolding failed and the actor is coerced into a position no human should occupy.
This is not ethics, it is catastrophic governance breakdown.
Axiom 1 No governance system may place an actor in an impossible dilemma.
1.1 When such a dilemma emerges, the system, not the actor, has failed.
1.2 Harm must be minimized by design and correctable when it occurs.
When harm occurs, it must be correctable is the second half of the axiom.
Correctability includes: reversibility where possible, repair mechanisms, narrative accountability, non-punitive learning and protection of the actor who was placed in the impossible position.
Correctability is not optional; it is the only humane response to systemic failure.
This is the governance equivalent of aviation's "just culture."
Axiom 2 When a governance failure forces an actor into an impossible dilemma, the system must immediately shift into a corrective recovery mode.
2.1 This mode prioritizes harm-reduction, reversibility, and restoration of agency.
2.2 The actor must be protected from blame,
2.3 The system must expose, not conceal, the structural conditions that produced the dilemma.
2.4 Recovery is not punitive; it is reconstructive.
⟲ RN-3.1.4 Dialectical thinking visuals: context dominancy to ops flow
Exploring the double diamond visual for operational flow
This is the moment for reviewing what came up the issue is that the reflection I am getting is getting unclear.
It is signal this was not attempted in this way before.
The "systems ethics", morality is made to a dedicated category, it is missing in all classical developmental theories.
Every major developmental theorist focused on individual cognition or individual morality:
Piaget Cognitive structures ➡ how individuals think.
Kohlberg Moral reasoning ➡ how individuals justify decisions.
Gilligan Care ethics ➡ how individuals relate.
Kegan Meaning‑making ➡ how individuals construct self/other.
Jaques Complexity of work ➡ how individuals handle abstraction.
Laske Dialectical thinking ➡ how individuals handle systems.
None of them addressed: ecological systems, organizational systems, multi‑stakeholder systems, governance systems, safety systems, recursive systems, planetary systems, AI‑human systems, long‑term viability, boundary conditions, systemic harm, systemic collapse, systemic ethics.
They all stop at human‑centric morality.
But the world we live in now is: multi‑system, multi‑stakeholder, multi‑temporal, multi‑boundary, multi‑risk, multi‑identity, Human‑centric morality is no longer enough.
This is why your Stage 7 ("perspective of anything affected") is not just an extension, it is the missing developmental domain.
Human Systems "Perspective of every person/group affected." is the universal stakeholder view, it is the completion of Kohlberg's Stage 6.
Generic Systems "Perspective of anything affected." is the universal systems view, it is the completion of Piaget + Kohlberg + Gilligan Stage 7.
This is the first time someone has: integrated human ethics with systems viability, with governance geometry, with boundary conditions, with recursive identity, with safety as universal constraint, with purpose semantics, with multi‑system alignment.
This is why it feels new, because it is new.
I am using the double diamond idea originating in design thinking but extended it.
Double Diamond
is the name of a design process model popularized by the British Design Council in 2005.
It has the goal of visualisatione the creative process for:
Asses: exploring the problem broadly (divergent)
Plan: define the focus (Convergent)
Do: explore development solutions broadly (divergent)
Check: choose delivery best solution (convergent)
The Hierarchical perspective for activities dialectical
The classic approach is seeing operations in the now done by:
Punishment-Obedience, Advantage = "Hierarchy as a compensatory mechanism"
An memergent approach would be defining states (Cx) and seeing divergence and convergence over paths.
Aside an intended horizontal flow line there is a mind for solving tensions
in a figure see right side.
The classic approach is seeing changing in the now the operations by:
System order: role + boundary = Social order "What keeps the system viable?"
An emergent approach would be defining states and seeing divergence and convergence over paths.
Aside an intended horizontal flow line there is a mind for solving tensions
Added to
paths
exploring the problem broadly
Structured Problem state External semantic closure loop
define the focus
Requirements for proposals Design validation
in a figure see right side.
The classic approach is seeing changing in the now operations by:
Self Group identity: norms = interpersonal concord "What's good for us?"
Here something terrible is realised, there is no common role for C3 / P3.
Roles are defined in Relations/Transformations but nothing is defined.
With Zachman we have a lot tasks actvities but no roles but we need a generic approach that.
It is fully listed later (RN-3.5.1) from that the role that failed there gets a meaning here:
C3/P3 level: A Resource Planner who looks at the interaction between people and resources (Dynamic).
C4/P4 level: A Capability Architect (Pivot) who coordinates resources (C3) and the friction between interests (P3) to realize the "Worth" (K5).
C6/P6 level: A Vanguard Leader who not only manages resources but transforms them, which is a moral choice at a high Kohlberg level.
The Vanguard leader is an important role, that thas one is usual missing was a noticed issue.
Someone has to be accountable responsible for the product/service as a whole the CPO (Chief Product Officer).
Localized accountablities CFO COO CIO are distorting that role.
C1 Context: The CPO defines the Product Vision.
Translates market needs into the "Intention with goals".
Prevents the team from only doing what the customer asks
looks at what the customer needs (Purpose).
C2 Concept: He designs the System Structure.
How does the service relate to the user? (external)
breaks down silos (Personal Power/Ego) to create a coherent experience
C3 Resource: The CPO manages the Pivot.
decides, based on "Capability options", whether a product line is continued or stopped.
in a figure see right side.
The perspective for activities dialectical vs complexity
This is not very balanced in the complexity versus tension ordering.
The centre for managing contextual resources (C3) is the middle of the tensions.
Defining the meaning of contextual resources is fundamental it could be technological options or knowledge options or both.
Without a practical case it is difficult to understand.
C2 - C4
C5 - C6
Limits boundaries concepts ⇆vs embeddedness
Dependency ⇆vs shift
Managing the business ⇆vs architecting the business
engineering with closed loops ⇆vs managing business operational
The most important dialectical tensions (see table)
The challenge is that C3 is needed to make this possible, the complexity is not hat high, but there is no clear ownership no clear accoumtablity for resources.
In a figure see right side.
C3 is the centre for alignment in all directions.
Tensions always remain open. In this model, this is illustrated by the fact that T6 (conflict) never completely resolves; instead, it provides the input for a new C3 (new resources).
C3 is the crucial pivot point because it sets the logical architecture and the phycial.
However the missing clarity for ownership and accountability resluts into nobody and everybody takes ownership guided by other goals then that of the system.
Not all pillars are expected to be functioning, what happens if C4 and C5 are failing?
In a figure see right side.
Instead of multiple paths at each side of the diamond there is a connected path left fo doing what has always been done.
There is no reflection for adpation (change) or seeing issues in the system.
As long as external - internal conditions dont't change the system wil keep going on (homeostatic).
C4 and C5 are abstractions for what can be seen as roles for architecting and engineering.
Information processing first order analytics The "Executor" The "Observer" The "Inventor" "The Hinge" "The facilator" "The orchestrator"
The distinction between the different "orders of thinking" (often linked to systems theory or cybernetics) revolves around the shift from acting within a system to reflecting on the system itself.
The "Executor"The world/the object: "Am I doing things right?"
With first-order thinking, you focus on the content and the result.
Use of existing rules, knowledge, and patterns to solve a problem.
Applying a known pattern in a new context falls under 1st order.
While you are flexible (transfer of knowledge), the underlying logic of the pattern itself remains unchanged.
"How do I solve this with the tools I have?"
Characteristic: Goal-oriented, linear, and focused on effectiveness within the status quo.
Dialectics is absent because the rules are fixed, it concerns input -> process -> output. The "Observer"Thinking/the process "Am I doing the right things?"
With second-order thinking, you focus on the the patterns that lead to results.
No longer is the problem itself the subject, but at the wayhow you look at the problem.
The pattern itself is questioned.
"Why am I actually using this pattern?"
"Is the assumption behind this pattern still valid?"
"How does my presence as an observer influence the system?"
Characteristic: Reflective, circular, and aimed at changing the rules or the perspective.
Dialectics .
Efficiency vs. Effectiveness
The theory of how we conceived it clashes with the practice of how we execute it.
3
The "Inventor"The context/the paradigm: "Why do we actually find this important?"
The classical 1st/2nd/3rd order approach is primarily epistemological, knowledge-oriented.
It concerns: What do we know and how do we know that?
Measurable and describable, it is the blueprint of the system.
(-)
The model is process-ontological: it describes the flow of becoming.
That is why it falls "outside" the classic ordering.
It is not a hierarchy of thought, but an architecture of manifestation.
In this, the "orders of thought" become instruments that are activated at various points in the diamond.
In the classical orders, the transition is often fluid. In this fractal, hinge 4 is a singularity.
It is the point where the abstract potential (the first diamond) must "collapse" into a concrete choice in order to nourish the second diamond.
That is a more powerful concept than merely "higher thinking"; it is "being decisive" in the void.
First, second, and third-order thinking suggest that "higher" is always "better" or "more comprehensive." this fractal suggests symmetrical necessity.
Without the first diamond (the contextual reality), the second diamond (the moral governance) has no foundation.
They need each other to translate the transformation into a process.
This is a fractal of a different Order touching the core of Auto-poiesis, self-creating systems.
Symmetry:
The first diamond (T, C, R) concerns the Hardware of reality.
The second diamond (K, M, P) concerns the Software (the inspiration/guidance).
Directional Sensitivity: Because T is at 1 and P at 7, there is a "negentropic" process: you organize energy and intention into a repeatable, meaningful process.
Irreversibility: A transformation that has passed through the moral/governance filters permanently changes the Process.
It is not possible to "un-know" what you have realized on a moral level.
One could say that understanding this 7-level fractal itself is a form of 4th-order thinking.
It is not considering only the pattern (2nd) or the paradigm (3rd), but the full dynamic between being and becoming along the axis of time.
Started was looking at the "beam of light" itself and how it is broken by the prisms of power, morality, and context into the colors of a workable process.
This makes it an instrument for system design rather than just system analysis.
It explains why some transformations never lead to healthy processes: the refraction in the diamonds (often at the power in the hinge 4 or the morality in 6) is too great, causing the energy to drain away.
4
The "Facilitator"The context/the paradigm: "Why do we actually find this important?"
The 7th layer functions as a point of irreversibility touching the core of complexity science and developmental psychology.
This is reminiscent of Prigogine's, dissipative structures : as soon as a system reaches a certain degree of complexity and goes through a crisis (or realization), it restructures itself at a higher level.
There is no way back to the simplicity of the lower orders.
Dialectics for outcomes of the lower layers are reflected upon:
In Morality Ethics "taking others into account" into "acting based on universal principles."
For Governance Continuity of Intelligence the shift of C&C into "stewardship over evolution."
The system no longer serves itself, but the integrity of the whole.
Fascinating in this is the detachment of Governance from "management" C&C.
5
The "Orchestrator"The context/the paradigm: "Why do we actually find this important?"
The observation that M4 must remain "open" despite the power residing there is emergent from a systems perspective.
If the 4th layer is fixed by rigid rules, a falls back to 1st order, the dialectic in the higher layers dies.
After all, there is nothing left to weigh up if everything is programmed.
Dialectics for outcomes of the lower layers are reflected upon:
Individual Value vs. Collective Goal
Ethics vs. Strategy
6
The "Universe"The context/the paradigm: "Why do we actually find this important?"
RN-3.2 Handing over interactions, centre of a system
Adding time and direction for orientation in choices is the next phase after the basic understanding in the now.
The boundary is the common organisation approach set by Engineering vs architectural split:
operations now,
change engineering realizing near future,
change architect logics near future (abstractions),
vision far future
The awareness for choices is limited for the whole in direction knowing the location but a time horizon and uncertainties for impact are not completed.
⟲ RN-3.2.1 The state of mind, thinking in integrated process flows
Connecting from the counterpart page the human
The counterpart page, AK chapters, is essentially a mindset framework for understanding and managing complex systems, especially those where humans are both participants and builders.
It was possible there to specify technical requirements for a knowledge management system.
Topics:
For organizations it helps to diagnose where failures occur.
Scope: not just in processes, but in values, culture, and decision structures.
For technology teams it provides a structured way to align.
Disciplines for: DevOps, SRE, and platform design with systemic maturity.
For leadership offers a lens to balance:
efficiency vs. adaptability, functioning vs. functionality
control vs. emergence, control vs. influence,
ego vs. soul, personal vs organisation
Leaders a systemic map of their cultural tensions affecting anything.
It's not just about technology, it's about the interplay of
systems thinking, lean principles,
viable systems models (ViSM), and the Zachman 6*6 reference frame.
⌛ Quest for: safety, wealth, fame, honour inclusion within knowledge management
The Levels of Success Factors (LSF) model shows that each layer makes its own contribution: the environment defines opportunities and limitations, behavior shows what we actually do, and our capabilities determine how we act.
The LSF model shows tensions: the balance between ego and soul.
On the one hand stand ambition, roles, and permission, elements that provide structure, security, and performance.
On the other hand stand vision, mission, and motivation, qualities that cultivate creativity, energy, and innovation.
At the counterpart page it was not able to specify how to define problem states to be solved neither what the ethical or morality aspects are related to a knowledge management system.
Defining the problem in problem-state boundaries is described in RN-2.2.
A duality for people and for systems:
human lens: Focuses on individuals and teams
Topics: diagnosing blockages in values, identity, or behavior
Leadership compass: The "ego vs. soul" polarity can be placed inside all other dualities.
system lens: Focuses on structures and flows
Topics: diagnosing failures in context, logic, or decision loops.
It doesn't just describe systems, it describes how to think about systems. It's like a navigation chart for complexity, combining:
Zachman's structural rigor, Beer's cybernetics, Lean's improvement cycles, and human motivational drivers. ⏳ An overlay for safety, wealth, fame, honour inclusion within knowledge management
Having defined a lot for the worth that is not well to measure to first overlay is of those chapters to a categorisation useful for this scope.
Both start by situating the system in its environment.6*6 Zarf adds uncertainty modeling.
Behavior
Operational / Tactics AK-2 flows, PDCA, OODA)
Maps directly to Lean cycles and execution patterns.
Capabilities
Components & Platforms AK-2.4, AK-2.5
6*6 Zarf formalizes capabilities as technology platforms, fractals, and closed loops.
Beliefs & Values
Human Drivers AK-1.2.3: safety, wealth, fame, honour
6*6 Zarf explicitly models values as systemic drivers, not just soft factors.
Identity
Vision / Mission AK-3.6 transcendental boundaries
Identity vision alignment:6*6 Zarf treats identity as emergent from systemic values.
Ego vs. Soul Balance
Dualities/Dichotomies AK-1.2.4, AK-3.2 Gestalt
Both emphasize balancing structural ambition (ego/control) with adaptive creativity (soul/emergence).
Context and technical - human lenses
Using the 7 caetgories in a visual is having 1,7 as endpoint that are external and there is a coordination in the internal ones.
The approach of a double diamond is not linear. ⌛ A prjoction into 2D for for Context (C) Relations (R) Processes (P):
C-thoughts
6*6 reference
Meaning
Human lens
C1
Container
Context
The holding environment
Environment (constraints, opportunities)
C2
Limits
Concept (constraints)
Rules, boundaries, governance
Behavior (actions, habits)
C3
Parts
Physical/Component
Elements, resources, capabilities
Capabilities (skills, resources)
C4
Embeddedness
Logic
Coherence, fit, beliefs
Beliefs & Values (meaning, motivation)
C5
Dependency
Physical/Component (external)
Upstream reliance
Identity (who we are)
C6
Shift
Concept/Logic (change)
Adaptation, transformation
Ego vs. Soul Balance
C7
Layering
Instance / Fractal
Multiplication, recursion
Purpose / Vision expressed across levels
In systemic terms: C, R, P = ontological categories, Transformations = epistemic/operational operators
Operators cannot place inside the ontology they modify.
Transformations sit outside and across the diamonds, they are the arrows, not the nodes. ⏳ Tensions for Context (C) Relations (R) Processes (P):
?5-?6 Adaptive tensions, Dependency vs. Change another systemic duality:
(C) Too much dependency ➡ stagnation
(C) Too much shift ➡ instability
(R) Too much dependency ➡ lock-in
(R) Too much shift ➡ instability
(P) Too much dependency ➡ bottle-necks
(P) Too much change ➡ unpredctability
This is the control vs. influence tension and maps to Identity vs. Behavior (ego vs. soul).
The functioning vs. functionality tension and it aps to Behavior vs. Capability.
?2-?3 Structural Boundaries vs. Resources: a classic systemic duality:
The Ladder That Wasn't There: Kohlberg's Moral Development Theory and Its Legacy in Management (LI: Reg Butterfield 2026)
The six levels are inspired by Piaget.
For a full dialectal view there is something missing. ❶
Kohlbers theory proposed six stages of moral development, grouped into three levels.
"pre-conventional level", morality is external.
The person obey rules to avoid punishment or seek reward.
Right and wrong are determined by consequences, not principles.
Punishment/obedience orientation. Individual obeyance to avoid punishment.
Instrumental purpose. Focuses on receiving rewards or satisfying personal needs.
"conventional level", morality becomes social.
Individuals conform to societal expectations, maintain relationships, and uphold laws because order matters.
Good behaviour pleases others; bad behaviour disrupts harmony.
The individual wants affection, approval of others by being a "good person."
Believes that rules and laws maintain social order that is worth preserving.
"post-conventional level", morality becomes abstract and universal.
Individuals reason from self-chosen ethical principles of justice, dignity, and equality that may transcend laws and social norms.
View of laws and rules as flexible tools for improving human purposes.
A perspective of every person, group that could potentially be affected.
❷ What is not mentioned is the use of this in other parts and by other parts (7).
Kohlberg argued the highest form of moral reasoning as the development goal.
The progression appeared logical, even elegant. People move from selfishness to socialisation to principled autonomy.
Each stage builds on the last, more sophisticated, more mature, more developed.
Educators adopted it to teach ethics, psychologists used it to measure moral growth.
Eventually, management consultants found it for selecting and developing leaders.
Yet Kohlberg's theory contained assumptions so embedded in its structure that they went unquestioned for decades. ❸ The assumption of linear growth is not how systems work, these are non-linear.
The stages were linear; you climbed upward, never downward.
They were universal, the same for all people, all cultures, all contexts.
They privileged certain kinds of reasoning; abstract, principled, and justice-oriented over others, such as relational, contextual, and care-oriented.
They conflated moral reasoning with moral action, assuming that those who could articulate higher principles would act more ethically. ❹ The assumption of able to do well moral reasoning automatically act more ethically.
The Care Blind Spot: When Relationships Count Less Than Principles
The Cultural Hierarchy: When Western Reasoning Becomes Universal Truth
The Reasoning-Action Gap: When Principles Meet Power
The Elite Bias: When Privilege Becomes Development
The Organisational Architecture: When Hierarchy Becomes Structure
⟲ RN-3.2.2 Mindset change for EA in integrated governance
Safety seeing as a component of quality, ethics, morality - The East
There is no dedicated quality pillar anymore it is absorbed into the processing standards.
In the physical world the same has happened for safety the exceptions is safety in information processing the virtual world. /
Safety as the Transformation pillar (East) in the Laske/DTF model makes perfect sense, especially when distinguished from the static "Identity" in the South-West. ⚖️
In a high-performing system like Danaher's X-matrix, safety is not a state you reach; it is a transformation you practice.
By placing Safety in the East (Transformation) it is treated as the "quality shift" part of all other processes.
Safety as the "Systemic Lubricant" (East):
If Transformation is the birth of new structures, Safety is an essential part for that.
Psychological Safety: Allows the "Process" (North) in changes to fail fast, learning without fear.
Physical/Operational Safety: Ensures the "Power/Speed" (Horizontal axis) doesn't destroy the "Resources" (SE corner).
The Fit: By putting Safety in the East it acknowledges that as the system evolves, its definition of safety must also transform.
A digital transformation requires different safety protocols (cyber/data) than a manufacturing one (physical).
👁️
Safety part of ethics in Transformations inhertitied from a higher order given to fractals
Within an organization's identity, you need the same four forces to remain 'humane' and 'safe':
S (South) - Foundation: The deep values and beliefs (What is sacred?).
W (West) - Social Dynamics: How we interact (Relationships/Communication).
N (North) - Rituals: The daily habits that affirm our culture (Processes).
E (East) - Safety: Active monitoring and evolution of psychological and physical safety.
⚖️
Why Safety is the "E" in this fractal:
Safety is dynamic: Just like Transformation, Safety is never "finished".
It is a continuous shift from one state to another (e.g., from reactive safety to proactive safety).
The "Check" on Identity: Without the "E" of Safety, Identity (SW) remains stuck in dogmas (South) or superficial politeness (West).
Safety is the transformative force that compels the culture to be honest about its mistakes.
Socio-Technical Integration:
SE corner (the large matrix), Safety is the fuel for the engine;
SW corner, Safety is the organization's immune response. Repels what is toxic.
👁️
The visual result is: in the SW corner of the large X-matrix, a small copy of the matrix is seen.
The eastern side of that small matrix lights up as Safety.
This creates a direct connection:
If the large East axis (System Transformation) falters, you look at the small East axis (Safety/Identity) in the SW corner.
Usually, you then discover that people do not dare to change (lack of psychological safety) or that the identity simply does not allow the new transformation.
This transforms the X-matrix from a 2D image into a holographic model.
The solution to a problem in the "outer" ring (results) is often hidden in the "inner" with a fractal (security/identity).
🎭💰
SW: where safety get's the meaning for the system and parts
To perform a Fractal Safety Audit, we look at the SW Corner (Identity) of your macro X-Matrix as if it were its own mini-system.
The Macro-Micro Alignment Check
Compare the "Big East" (Results) with the "Small East" (Safety).
Velocity Mismatch: We are asking for high-speed Digital Transformation in the Macro-East, but do we have high-speed Psychological Safety in the Fractal-East?
Audit Question: Can a junior employee stop a "Strategic Project" (North) if they see an ethical or safety risk, without fear of retribution?
The Resource Paradox: We see a bottleneck in the SE Corner (Internal Resources).
Audit Question: Is the bottleneck physical (not enough people) or fractal?
Fractal: people are "hiding" time/capacity because Identity-East doesn't feel safe to admit overload.
The SW-Fractal Deep Dive (The 4 DTF Classes)
Evaluation of the internal health, at fractals for each DTF Class.
DTF Class
Audit metric
the "Red Flag"
S
Context
Core Values
Values are just posters on the wall, not "lived" boundaries.
W
Relations
Conflict/Quality
Artificial harmony; agree in meetings but complain in the hallway
N
Process
Learning Loops
Errors are punished or hidden instead treated as "system data"
E
Transformation
Safety/Agency
Feel like "cogs" in a machine rather than "authors" of change.
Testing "The Boundary" (SW/NW Tension)
Does the Identity protect the system or isolate it?
The Moral Compass Check: Look at your most profitable "Project" in the North.
Audit Question: If this project succeeds but violates a "Value" in the South-West, does the system have a "Circuit Breaker" to kill it?
External Pressure vs. Internal Integrity: When a "Signal" (NW) demands a pivot.
Audit Question: Does the Safety (Fractal-E) allow the team to say "No" to a market opportunity because it compromises our Identity (SW)?
The Audit Result: "The Coherence Score"
High Coherence: The Safety (Fractal-E) is strong enough that people take risks in the Process (Macro-N).
Innovation is high, and the SE-bottlenecks are discussed honestly.
Low Coherence: The Identity (SW) is fragile. People over-promise in the Annual Goals (West) and hide failures in the KPIs (East).
The X-Matrix becomes a "theatre of compliance."
Making safety made inseparable in the system
Safety is a non-negotiable (li: S D'Amico reply Mark Rogovoi 2026)
A high-performing team knows this and treats safety as a must, not a "nice to have."
The list is long without categories, matching it to what I am woking on give a new perspective. ❶People & Psychological Safety
The human foundation, trust, openness, and non-blame.
Theme: Safety emerges from human conditions, not human perfection. (Context)
The process is blamed, not the person.
Talking about errors is a daily, open practice.
The goal is zero fear of reporting, not just zero accidents.
Psychological safety matters as much as physical safety.
"What allowed it?" is asked before "Who did it?".
Fractal note: This pillar sets the emotional and cognitive conditions that make all other pillars possible.
It's the environment attractor in human form. ❷Process & Prevention
Designing systems that make safe behavior the default.
Theme: Safety is engineered upstream, not inspected downstream. (Process)
Safety is designed in, not inspected on.
Hazard prevention is rewarded over heroic reaction.
"Getting away with it" is a process failure, not a success.
Finding a hidden problem is celebrated like hitting a target.
Proactive controls measure safety better than incident rates.
Fractal note: This pillar embeds safety into the operational DNA, the "design-in" logic that x-matrix loves. ❸Practice & Execution
How work is actually done, moment-to-moment operational discipline.
Theme: Safe execution is a skill, not a slogan. (Relations)
PPE is the last defense, not the first thought.
Risk assessments are dialogues, not checklists.
"Can we do it safely?" determines if work begins.
A 'Stop Work' command is met with thanks, not resistance.
The safety moment is the most vital part of the daily meeting.
Fractal note: This pillar is where safety becomes embodied, the lived practice that spreads through teams. ❹Leadership & Learning
Leaders model, reinforce, and evolve the system.
Theme: Leadership creates the conditions for safety to propagate. (Transformations)
Safety isn't a department; it's a skill for everyone.
Compliance is the minimum standard, not the goal.
Incident reports are for learning, not legal defense.
Leaders walk the floor to catch hazards, not to check a box.
"What could go wrong?" is asked as often as "What's the deadline?".
Fractal note: Leadership is the amplifier, the recursive loop that ensures safety spreads across the system rather than staying local. 🚧 The state of inforamtion safety, cybersecurity
Safety and Quality are inseparable, you cannot build Lean flow on an unsafe process.
True operational excellence begins when risk prevention becomes part of daily work, not an audit topic.
A strong Lean culture removes fear, exposes problems early, and treats every deviation as learning.
When people feel safe to stop the process, improvement accelerates naturally.
Performance grows where safety, quality, and respect for people move together.
Question: why is cybersecurity not cooperated as part of the flow?
In many companies cybersecurity is still treated as a separate control layer managed by IT, rather than as part of the operational flow.
Similar to quality in the past, it is often inspected or audited after the fact instead of being designed into the process.
As operations become more digital and connected, cybersecurity will need to shift from a "gate" to a built-in element of the system.
Another missing in the 6*6 reference grid
Defects are the system's signal that quality has collapsed somewhere upstream.
Quality, in Lean terms, is not "perfection" but: Fit to purpose, Fit to customer expectation, Fit to flow, Fit to standard.
So if defects are the breakdown of fit, quality is the presence of fit. This makes them true opposites in a systemic sense.
🚧 ⚙️
Treat the seven wastes not as a flat list, but as a recursive causal architecture.
This enables to see technical cybersecurity hardening checklist mapped onto Ohno's seven wastes as a meta-systemic pattern.
"Safety" and "Cybersecurity" behave like Quality.
This means the list is not "extra"; it is the governance expression of quality.
Principle ❶
Safety/Cybersecurity = Quality in the dialectical sense.
Defects ⇆ Security breaches
Quality ⇅ Secure-by-design
Overprocessing ⇆ Excessive controls
Waiting ⇅ Approval bottlenecks
Overproduction ⇆ Too many tools, too many permissions
"Safety" is not a new waste, it is the counter-pole to defects, just like quality.
Overproduction in cybersecurity is: Too many tools, too many permissions, too many integrations, too many exceptions, too many "temporary" admin rights.
Principle ❷ technical list does map cleanly onto Ohno's. "Lean Secure-by-Design"
Item
Description
Ohno's Waste
The systemic fit
Proactive limits
Define normal behaviour, boundaries
1
Overproduction
Setting limits prevents unnecessary "extra" actions, extra behaviour, extra risk surface
Identities & licensing
Dedicated integration users, API-only
2
Motion
Reduces human movement, UI clicking, credential handling
Integration accounts
Segmentation, no generic accounts
3
Transport
Prevents shuttling credentials, reusing accounts across systems
Access control & network security
MFA, login sources, least privilege
4
Inventory
Prevents accumulation of unused permissions, stale access, dormant risk
Authorization (Least Privilege)
FLS, object-level, avoid Modify All
5
Overprocessing
Prevents "too much power", "too much scope", unnecessary capability
Connected tools governance
Limit scopes, block uninstalled tools
6
Waiting
Prevents delays caused by tool sprawl, misalignment, unclear boundaries
Reactive limits evaluation
Drift detection, health checks
7
Defects
This is the quality loop: detect and eliminate defects before they propagate
The technical list assumed overproduction already happened and tries to contain the damage.
🚧 ⚙️
This unifies: Lean, Cybersecurity, Governance, Dialectics, System design.
Overproduction = structural misalignment: systems built without security in mind
self-reinforcing loop: More overproduction, More tools, controls, exceptions
👉🏾 When cybersecurity isn't a dedicated topic anymore it is adapted into systems.
⟲ RN-3.2.3 Defining corrective needs, axioms in a governance system
Another missing in the 6*6 reference grid (Zachman)
There is a differnce in a thinking reference and a realisation reference.
Zachman's six columns are: What / object ➡ How / process ➡ Where / space ➡ Who/ actor ➡ When / coordination ➡ Why / purpose.
In practice, in execution architectures, "Why" collapses into governance, and When becomes scheduling.
However, what Zachman never models explicitly is:
how actors emotionally and normatively relate to decisions before they coordinate them in time.
It jumps from Who ➡When as if humans were clocks, they're not.
❗ ⚖️
Horizontally a phenomenological gap is noticed.
Worth: value ethics morality instantiation of judgment into action.
The question is why this is omitted, most likely it is because it is part of our human nature.
In human systems: "Who answers: who can act?", "answers: how do they feel / judge / commit?",
"When answers: when do they synchronise?", that is a pre-coordination evaluative field.
Just as 'Parts' was added vertically between Concept and Logic to allow ideology to become executable, a 'judgement' dimension must be added between Who and When to allow actors to orient, value, feel, judge, and commit before temporal coordination.
Without it, ideology collapses into technocratic scheduling rather than lived meaning.
👁️
Why a 7-Layer Model Is More Complete.
Between Who and When something must happen: perception, valuation, affect, legitimacy, commitment judgment.
Before actors coordinate in time, they must interpret and value.
Without judgement: actors execute mechanically, coordination ignores legitimacy, ideology becomes propaganda.
With judgement: meaning becomes lived, timing becomes commitment, decisions gain ethical weight.
This also explains why agentic AI breaks architectures.
AI jumps from:
Who (agent) ➡ When (schedule) and skips: Orientation (value / affect / legitimacy).
So you get: fast, aligned, but normatively blind systems.
The seven columns are:
1/ Object 2/ Process 3/ Space 4/ Actor
4/ Actor 5/ Worth 6/ Coodination 7/ Purpose.
It is the moment ideology becomes irreversible, this is closer to: Arendt's action, Laske's commitment logic, VSM's policy enactment, it belongs at the end.
❗ ⚙️
A thinking reference doesn't need an explicit "worth/valus/ethics/morality" layer.
In this space, "worth" is implicit. reasoning is about patterns, flows, tensions, and coherence.
A realisation reference absolutely does need worth, thinking operates on abstractions, while realisation operates on substrates.
A thinking model answers:
"What is the purpose?", "What are possible impacts for all involved?"
"How do we balance averse effects?", "How do we scale it?"
Changed is Why into Which to align that decisions are made for a purpose.
Which is: "option selection", "portfolio choice", "commitment of resources", "path dependency creation".
👉🏾 It is a dual-mode ontology: Stages 1,2,3,4 = technology and stages 4,5,6,7 = coordination.
The overlap is intentional, the shift from technology ➡ to coordination happens at actors.
Using a thinking or realisation reference
Validate Your Enterprise Architecture in Production? (LI: Raj Grover 2026)
Governance typically stops at design time.
Delivery pressure, vendor changes, local optimizations quietly reshape the live environment.
Leadership is left steering the enterprise using an outdated map.
The uncomfortable part is not that drift exists, it's that most leadership teams don't realise where it has materialised until a funding, risk, or outage event forces the issue. ⏳
From the inside, it still looks like governance, but in reality it's governance operating on assumptions.
This is not about more process, but it is about closing the loop between intent and execution.
A question for leadership:
When did you last validate your enterprise architecture against production?
If the answer is not recent, you are managing expectations, not the enterprise. ⌛
The "worth" is in the thinking level missing for the main categories.
The associate figure is mentioning the 7W1H-domains in columns using for each 7 subcategories.
For the "parts/resources/capabilities" it is assumed by:
EA roadmap, value stream maps, cloud strategy and migration plan
System integration plan, zero trust architecture blueprint, emerging tech radar
See right side
Architecture categories for:
What - Enterpise
How - Business
Where - technology
Who - Solutions
(Worth)
When - Security
Which - Innovation
👉🏾 Although the principles that this all is build on in systems thinking are very generic, this is back to information processing, knowledge management.
Governance Axioms
The missing operational bridge between the ideal state (Axiom 1), the failure state (Axiom 2), and the governance mechanics that keep the system viable (Axiom 3).
Impossible dilemmas are not ethical puzzles; they are governance failures.
The only moral stance is to design systems so that:
no actor is ever forced into one and
to ensure harm is correctable when it does occur.
Impossible dilemmas must be prevented by design, they are systemic collapses where: boundaries failed, safety layers failed, relational trust failed, capability scaffolding failed and the actor is coerced into a position no human should occupy.
This is not ethics, it is catastrophic governance breakdown.
Axiom 3 A governance system must continuously surface, map, and resolve emerging tensions at every recursive level, from individual actors to teams, units, and the whole before they escalate into impossible dilemmas.
3.1 It must explicitly track and mediate conflicts between short-term gains and long-term viability, and between the interests of components and the integrity of the whole.
This requires explicit detection of:
3.1.1 boundary shifts
3.1.2 capability gaps,
3.1.3 relational breakdowns,
3.1.4 semantic drift, and
3.1.5 temporal misalignment.
3.2 the system must maintain a living structure across all levels and time-spans, by:
3.2.1 feedback loops,
3.2.2 early-warning indicators, and
3.2.3 corrective pathways
across all levels and time-spans keeping actors and subsystems:
3.2.4 within zones of safe,
3.2.5 meaningful agency while
3.2.6 preserving the long-term survival and
3.2.7 coherence of the system as a whole.
This requires in practice: ❶ See the "governance fault lines."
The system must track (Context):
safety vs autonomy
hierarchy vs anarchy
deterministic vs probabilistic reasoning
capability vs responsibility
relational trust vs control
short-term vs long-term time horizons
boundary clarity vs drift
❷Early-warning indicators, precursors to impossible dilemmas.
The system must detect (Relations):
rising ambiguity
collapsing boundaries
overloaded actors
semantic drift
capability mismatches
relational breakdowns
time-pressure distortions
❸The system must ensure that actors always operate within:
The system must see (Process):
clear boundaries
sufficient capability
adequate time
relational support
semantic clarity
This is the governance equivalent of "operational envelopes" in aviation. ❹When tensions rise, the system must support corrective pathways:
The system must adapt (Transformation):
re-align boundaries
redistribute capability
clarify semantics
adjust time horizons
restore relational trust
These are the mechanisms that prevent escalation.
⟲ RN-3.2.4 Dialectical thinking visuals: relations dominancy to change
Exploring the double diamond visual for the orgnsiational identity
Brutally, we don't model end-to-end information journeys. (li: Robert Vane 2026)
We've spent decades modelling stored data, but almost no one models data in transit and that's the problem.
Because the semantics of stored information are not the same as the semantics of information in motion.
Stored data is interpreted within a single system, information in transit crosses boundaries.
And every boundary is a system with its own:
primitives
constraints
and purpose
So every time data moves, three things happen: Input â†' Transform â†' Output.
At input, meaning is bound to the sender, during transformation, it is reinterpreted amd at output, it becomes something else.
The real shift isn't from data to semantics.
It's from static semantics to dynamic semantics.
We've treated meaning as something that can be: defined once, stored and reused.
But in reality, meaning is applied and application happens at boundaries.
The problem isn't: "How do we describe data better?"
It's: "How do we ensure meaning resolves correctly every time it moves?"
Until that question is answered, every "semantic layer" is just a partial solution.
Because it stops where the problem actually begins.
A teaser: data in motion is about information, how it transforms is knowledge, when the intent is a match in the result it is Wisdom.
Data is extracted from somewhere (environment) whether it is complete applicable or there is a better source is not asked (another gap).
When it is at the other end the question should be does it match the goal behind the intent.
This is extending Ackoff DIKW into the dialectical mindset in undertanding.
The system perspective for understanding activities dialectical
The usual missed approach is seeing what the system does in the now and the difference to a supposed purpose:
Inter systems: "Perspective for each with their own purpose, constraints and legitimacy."
The usual missed approach is seeing evolvements emerging changes that are in a far future for the system:
Generic systems: Universalizable principles = "Perspective of anything affected"
The system perspective for changing activities
The usual missed approach is seeing changing the interactions in the near future for the system components and stakeholders:
Human systems: social contract = "Perspective of every person/group affected"
The system perspective for changing activities dialectical vs complexity
This is the most balanced one for the complexity and tension ordering.
The centre for managing power asymmetry (R4) a level in complexity in the middle of the tension.
Without a practical case it is difficult to understand.
Managing the business ⇆vs architecting the business
engineering wiht closed loops ⇆vs managing business operational
The most important dialectical tensions (see table)
The challenge is that R4 is needed to make this possible, this complexity is higher than that of Context (C3) for operational as centre in the double diamond.
In a figure see right side.
R4 is the centre for alignment in all directions.
R4 is the crucial pivot point between the external appearance of relationships and the internal, essential connectedness.
Giving the answer for how all interfaces are related to each other. Correctness of the overall architecture by connections.
Not all pillars are expected to be functioning, what happens if R4 and R5 are failing?
In a figure see right side.
Only some decoupled path are left with a big tension gap.
The result will be a collapse for change.
Only some basic rudiments are left.
R4 and R5 are abstractions for what can be seen as roles for architecting and engineering.
RN-3.3 Far future perspective into purpose semantics
Adding time and direction for orientation in choices is the next phase after the basic understanding in the now.
The boundary is the common organisation approach set by Context-bound vs context-changing futures:
operations now ,
change near future ,
vision far future within concept bounds,
vision far future changing context
The awareness for choices is completed for the whole in direction location and a time horizon for uncertainties and impact.
⟲ RN-3.3.1 The Obeya challenge in a birds-eye view: X-matrix
Reviewing and rebuilding the X-matrix
The Danaher X-Matrix is a visual strategic planning tool that is part of the Danaher Business System (DBS).
It is used for Policy Deployment (Hoshin Kanri) to translate the organization's long-term vision into concrete annual goals, improvement priorities, and measurable results on a single page.
At Danaher, the matrix serves as the glue between strategy and execution.
The X-Matrix works by mapping the relationship between adjacent sides. 🔏 The focus is on actvities at the edges of the diagonals
S ⟳ W: How do this year's goals (West) support long-term breakthroughs (South)?
Focus: It forces leaders to choose a limited number of strategic pillars, preventing resources from being spread across too many initiatives.
W ⟳ N: Which specific projects (North) drive this year's goals (West)?
Cascading: The top-level matrix is cascaded down to lower levels in the organization.
The annual goals of the higher level become the basis for the matrix of a specific department or team.
N ⟳ E: Which KPIs (East) measure the success of those projects (North)?
Catchball: A process of "throwing" goals back and forth between management and teams (catchball) ensures buy-in and realistic plans.
E ⟳ S: Does the data (East) actually move the needle on our long-term vision (South)?
Monthly Review: Progress is closely monitored, often using bowling charts, to allow for immediate adjustments when results fall short of targets.
Our ultimate guide to Hoshin Kanri
See right side.
The story is that doing this in practice is a hard challenge, many tried to use it, but the frustration by its many failures is creating frictions by themself.
❌ Wat is causing the failures?
The flat approach for the left empty E ⟳ S corner❗
The most important edge is not there in the overview.
Activities are mentioned and these are the most frequent ones for immediate action, but they are not embedded in the visual.
🚧 The E ⟳ S corner is often left empty No closing no feedback.
The E ⟳ S corner is theoretically where "Act" should meet "Plan" to close the PDCA (Plan-Do-Check-Act) loop.
It's the check if the Top-Level Metrics (East) actually validate your Breakthrough Objectives (South).
The most elementary validation:
Usig an added correlation Matrix.
If you have a 3-year goal to be "Market Leader" (South) but none of your monthly KPIs (East) measure market share, that "gap" highlights a strategic misalignment.
💡 💰 The X-matrix is a 9-plane diagonal and orthogonal that is popping up continuously.
That should be well able to get aligned to what is done in all the other chapters Zarf Jabes for a generalised uniform approach.
The X-matrix in a dialectal lens
Analysing the problem of the E ⟳ S corner that
However, several practical and structural factors often "block" this closure: ❶Dimensional Mismatch (The "Scale" Gap)
The primary blocking factor is a mismatch in timeframe.
South (Breakthroughs): Long-term strategic goals (3-5 years).
East (KPIs): Real-time or monthly performance metrics.
The Block: It is difficult to mathematically correlate monthly KPI data (East) directly back to a 5-year vision (South) in a single visual cell. This creates a "disconnect" where the metrics don't clearly validate the long-term breakthrough, preventing a clean "Act" adjustment.
❷ Goodhart's Law & Metric Fixation and Over-Cascading & Complexity
When the SE corner is used to link metrics to vision, organizations often fall into the trap where "when a measure becomes a target, it ceases to be a good measure".
The Block: Teams often focus on hitting the numeric target in the East rather than asking if that target actually achieves the strategic intent in the South. This "buffet of KPIs" distracts from the actual PDCA cycle.
The Block: In this "Catchball" process, the focus shifts to local accountability (Far East) rather than closing the global strategic loop. The sheer volume of information can make the SE corner "the correlation matrix" so daunting that teams simply ignore it to focus on their immediate "Do" tasks.
❸Positioning it as a Static Tool
The X-Matrix is often treated as a static annual document rather than a living PDCA engine
True PDCA requires frequent "Check" and "Act" phases. The X-Matrix is excellent for the "Plan" and "Do" (alignment), but the "Check" and "Act" usually happen elsewhere, specifically in Bowling Charts or A3 Problem Solving.
The physical layout of the matrix doesn't easily support the "Act" phase without becoming overcrowded and unreadable.
❹Positioning it as a Static Tool
By mapping the four classes of DTF: Context, Relations, Process, and Transformation to the quadrants of the X-Matrix, I am transforming a document used for compliance into one used for complex systems thinking.
There are still practical challenges:
Silos: The Speed dashboard is for the shop floor; the Direction dashboard is for the boardroom.
The X-matrix tries to force them to talk, but they often don't understand each other's language.
Software limitations: Most Hoshin Kanri software is built on the Excel grid model, not on dynamic vector visualization.
🚧
In essence, the E ⟳ S corner starts to be with a "Sanity Check" area.
If you find it empty, it usually means the organization hasn't yet figured out how to prove that their daily metrics (East) are actually winning the long-term war (South).
But when the S has no connection, no evalaution, no closed loop, that one could be left out.
But when E has nu goal no purpose, no closed loop it could be left out also. E ⟳ S No S, in effect it is the Foundation, the deep values and beliefs the is left out. E ⟳ S No E, in effect it is the Transformation what keeps the system alive that is left out.
See right side.
What is left is useless activities at the remaining corners for assumed Tactics (W) and the rituals in culture (N).
🕳 ❓ Questions: Why are there those many frictions, why that PDCA gap, why is the purposes goal for the whole missing, why is there no simplicity in dashboarding, why ...?
A generic mindshift for integrated governance
Reorienting the X-matrix visual and looking to the visual it is a 9 plane.
The SIAR model similarity and seeing orthogonals & diagonals in this is a remarkable similarity.
The focus in the X-matrix is on the activities at the corners, using diagonals but the most important edge is too often left out.
The reason could be simplicity for decision makers but leaving it out makes decision making useless. ⏳
The E ⟳ S corner must become a part of the whole althought it is the most challenging one.
See right side.
The E ⟳ S is where the complexity lives for:
correlation to the Foundation
Interdependencies - priorities
Positive/Negative effects
This closing the promise meets fulfilment, vision meets realisation.
⌛ Seeing the X-matrix in a perspective in orthogonals and diagonals.
The orthogonal lense sees states (similar to data-information) but what is going in the diagonals are activities (similar to processes).
This is a fundamental duality-dichotomy.
Four categories for each and the crossing over adds the needed interaction.
Orthogonal lens - states
👐
diagonal lens - dynamics
Where are we and where want we to be?
duality switch
1
What is the power we want and what speed we want?
Long-term goals
S
context
2
SW
KPI's for purpose
Annual objectives
W
relations
3
NW
Alignment for goals
Top Priorities
N
process
4
NE
Actors - Responsibilities
Accountabilities - who
E
transformations
5
SE
Review cadence - PDCA closure
What is our position and are we progressing?
duality switch
6
What power do we have and what speed is made?
Seeing it in this perspective the dashboard for systems becomes simple.
It is not all kind of details in the activities, activities that can vary and change fast.
For the goals objectives:
Where are we and where want we to be?
What is our position and are we progressing?
For the activities progress:
What is the power we want and what speed we want?
What power do we have and what speed is made?
💡 💰 Measuring this dedicated avoids the derivation complexity in the mess about activities.
⟲ RN-3.3.2 Changing the X-matrix into a dialectal governance lens
The mindshift: seeing orthognals for results instead of diaognols
The "Achilles' heel" of the standard X-Matrix: it treats strategy like a list of independent ingredients rather than a complex recipe.
By viewing the East as a "long list of activities" and North/South as the "priorities/vision," we are essentially looking at a Resource Pipeline.
🚧 ⚙️
When applying the Theory of Constraints (TOC) thinking here, the "gap" in the SE corner is actually a Bottleneck Visibility Gap. ❶The "Hidden" Critical Chain (TOC)
In the standard matrix approach, three different projects (North) might all rely on the same "Subject Matter Expert" or the same "Budget Pool," but the visual tool doesn't show this.
Problem: optimize the List (Local Optimization), but breaking the System (Global Constraint).
The Fix: Use the East/SE section to map Resource Contention.
If three projects in the North point to the same resource in the East, you have identified your Drum (the constraint).
Then "buffer" those projects or sequence them.
❷Relational Dependencies (DTF)
Using Laske's Relations (West), you can see that projects aren't just lists; they are Interdependent Loops.
Sequential Dependency: Project A must finish before Project B starts.
Reciprocal Dependency: Project A and B must evolve together (Transformation).
The Fix: Instead of simple dots in the grid, use Directional Vectors in the SE corner to show which Transformation (East) "unlocks" another Context (South).
❸The SE Corner as a "Constraint Map"
When using the SE corner for Lean TOC Optimization, it becomes the place where you manage the Load vs. Capacity.
Detailed questions part of a Fix.
Vertical Flow (Direction): Does the system have the "Cognitive Capacity" to process this transformation?
Horizontal Flow (Power): Does the "Drum" (Constraint) have the speed to execute these relations?
❹The Dependency Ribbon
To fix the not shown dependencies, high-performing teams often add a "Dependency Ribbon" or a small Interrelationship Diagraph in that bottom-right gap.
Showing:
Which projects are "bottlenecks" for others.
Which KPIs are "lead" (predictive) vs. "lag" (result).
Resource Overload: A heat map showing where the "Context" (South) is asking for more "Transformation" (East) than the "Process" (North) can handle.
The X-Matrix fails when it remains a 2D mapping tool. To make it a TOC engine, that SE corner must represent Time and Flow.
Switching from diagonal "correlation dots" to orthogonal lines (horizontal and vertical axes) fundamentally changes the X-Matrix from a static alignment map into a dynamic steering tool.
🚧 ⚙️ Changing the way how feedback is measured and presented from diagonals to orthogonal
By using orthogonal feedback, the SE Corner ceases to be a mysterious gap and becomes the Coherence Point.
Instead of looking for a correlation dot, look for the Intersection: Where the "Speed" (Horizontal) meets the "Direction" (Vertical).
The Intersection = Impact.
See right side.
The orthogonal lines:
North - Processes
West - Relations
South - Context
East - Transformation
Not seeing all the details by activities but seeing the effects by states is a very different perspective.
By treating the axes as metaphors for Power/Speed and Location/Progress, there is a much stronger PDCA feedback loop.
The Horizontal Axis: Power & Speed (West ⇄ East)
Drawing a straight line across the center from West (Annual Objectives) to East (KPIs), you are measuring Kinetic Energy.
The Feedback, "Speedometer" tells "Are we moving fast enough to hit the target?"
The PDCA "Act": If the horizontal line shows high activity (West) but low metric movement (East), your "engine" is revving but the wheels aren't turning.
Don't wait for a quarterly review, adjust "Power" (resources or tactics) immediately.
The Vertical Axis: Location & Direction (North ⇅ South)
Drawing a straight line between North (Projects) to South (Breakthroughs), it is measuring Vector/Trajectory.
The Feedback, "Compass": It tells you: "Are we heading toward our goal (North Star)?"
The PDCA "Act": This solves the "time challenge" by forcing to ask if a short-term project (North) actually changes the long-term position (South).
If the vertical alignment is weak, there is only "drifting."
💡 💰 Measuring this kind of quality and quantity breaks the assumption that this important information for the whole would be found be analysing the components.
Breaking that assumption has consequences abandon old habits to replace for new ones.
The use of a DWH for solving operational issues becomes a no-go
Business process are required to become designed and operated without broken steps
The measurements needed are required to be objective without options for manipulations.
👉🏾 Breaking old habits is very difficult.
Seeing the two orthogonal lines not separate but as interacting ones.
If the lines don't meet in a way that moves the South-East quadrant, that signals that speed (West-East) is irrelevant to the destination (South-North).
Why this is easier:
Visual Intuition: Humans process "Are we on track?" (Vertical) and "Are we fast enough?" (Horizontal) much faster than diagonal grid-mapping.
Decoupling Timeframes: You can check your "Speed" (Horizontal) weekly, while checking your "Direction" (Vertical) monthly or quarterly.
Consultant-Proof: It's harder to hide behind a complex grid when the question is a simple orthogonal check: "Does this project move this metric toward that goal?"
The mindshift: NE E to SE for integrated change governance
In the adjusted model, the SE corner will be where you superimpose the two dashboards.
The horizontal line (Bowling Chart) says: "We're achieving our monthly figures."
The vertical line (Strategic Vector) says: "We're building for the future."
The intersection: If both dashboards are green, you have a sound strategy.
If the Bowling Chart is green but the Vector is red, you're overextending the future for short-term gains.
This divergence is a signal to review the safety and morality principles.
🚧 ⚙️
Redefined mapping of the X-Matrix logic, orthogonal focus: ❷South: Context - The Foundation X-Matrix Shift: Instead of just "Breakthrough Objectives," South becomes the Strategic Context.
It defines the "ground" on which the organization stands.
DTF Definition: The stable background, the "is-ness," and the boundaries of the system.
Feedback: If your South is weak, your strategy lacks a "home."
It is not about just hitting targets but defining the reality in which you operate.
❸North: Process - The vector Flow X-Matrix Shift: Improvement Priorities (Projects) are no longer static tasks.
They are Process Interventions, the management for flow of change.
DTF Definition: Constant change, emergence, and the "becoming" of the system.
Feedback (Vertical Direction): This is your "Progress." it questions: "Is the process moving, or are we just busy?"
The process realisations and transformations is a real complex challenge.
See right side.
From N to S at the East-line
NE: chosen activities with accountablities that are expected to bring worth.
E: state of chosen activities-(N) at some moment
SE: activities coordination for the accountable activities-(N)
This part is often indicated as project management it reduces change to something static that has an end-state.
❺West: Relations - The Connectivity X-Matrix Shift: Objectives are Relational Dynamics.
Don't look at "Sales" and "Production" in silos, but at tensions, dependencies between them.
DTF Definition: How parts of the system interact, balance, and conflict with one another.
Feedback (Horizontal Power): This provides the "Power" mentioned earlier. Power comes from the alignment and friction of these relations.
The west is feeding the east over the horizontal line. ❻East: Transformation - The Evolution , Speed X-Matrix Shift: KPIs are replaced by Transformational Signals.
Instead of "Did we sell 10% more?" ask "Has the system transformed to a state where 10% more is the new baseline?"
DTF Definition: The qualitative shift, the collapse of old structures, and the birth of new ones.
Closing the Loop: Transformation (East) feeds back into Context (South).
The east is where all transformation activity is concentrated.
👉🏾 Solving the "SE Corner" gap in using this model:
It is no longer a "gap" for consultants, it becomes the "Developmental Leap."
It measures the shift in the system's maturity.
The feedback isn't just "are we on time?" but "has our organizational 'Context' actually evolved because of our 'Transformational' efforts?"
To transform the SE corner of the X-matrix into a strategic tool, we need to make the abstract term "resources" concrete.
To have a closed loop for the context this is a new continuous interaction.
Focus on closing a double closing many loops.
See right side.
Closing the interaction between long-term future South with living in the now.
This could reveal issues to solve at both sides.
All what is concentrated in the between the East and South is now a problem of choices in what activities by what priorities.
With limited resources those are constraints in what is possible.
Left out are ❶ ❼ for the result and the higher level, bypassed ❹ the point of coordination.
In a TOC (Theory of Constraints) and DTF (Laske) context, these are the five most co mmon bottlenecks that block the flow of your strategy.
By placing these 5 bottlenecks in the SE corner, a "stop-go" system is created.
🚧 ⚙️
Only activate a new project in the North Axis when the bottleneck in the SE corner shows green space (capacity) again. ❷Specialist Expertise (The "SME" Drum)
This is the most classic bottleneck. Certain people (architects, legal experts, senior engineers) are needed for almost every project in the North axis.
Visualization: A vertical "heat column" in the SE corner that turns deep red if this person is linked to more than three strategic projects simultaneously. ❸Cognitive Absorption Capacity (Mental Bandwidth)
In the DTF model, this is the bottleneck for Transformation (East).
Teams can only handle a limited amount of change simultaneously before the quality of decision-making plummets.
Visualization: A "saturation meter" that indicates how many new work processes a department needs to learn simultaneously.
Too many purple lines (Transformation) towards a single Context (South) means system burnout. ❹Decision-Making Speed (Leadership Latency)
Projects in the North axis often stagnate not due to a lack of work hours, but due to waiting for approval or direction from the South (Context).
Visualization: The "Wait Time Vector" in the South corner.
If the line between a Project (North) and a Result (East) is interrupted, this indicates a blockage in the hierarchy. ❺Testing and Validation Capacity (The Gateway)
Often, the "output" of a project (North) depends on a shared facility, such as a lab, a staging environment, or a focus group.
Visualization: A "funnel icon" in the South corner where multiple project lines converge before reaching the "Completed" status (East). ❻Financial Runway & Cash Flow Timing
Although budget is often allocated at the beginning, the timing of expenditures (Transformation) often bottlenecks the speed of execution.
Visualization: A horizontal cash burn bar indicates whether the intensity of projects in the North Axis exceeds the available resources in that quarter.
👉🏾 When governance is by understanding how systems work, governance becomes a system.
⟲ RN-3.3.3 Defining the governance, axioms for a governance system
The mindshift: NW relevance to SE Adaption realisation
While the SE corner monitors internal capacity and execution (the engine), the NW corner acts as the organization's antenna and filter.
In the NW corner, the Annual Goals and the Improvement Projects (North/Process) converge.
If there's a gap there, the organization ignores external signals or reacts too slowly to market shifts.
👉🏾
The NW corner as a "Relevance Filter"
See right side.
West: Annual Goals - Relationships)
North: Improvement Projects - Process
Processes are getting connect lines drawn from the SE.
What is prioritized and what is going on made visible in the connection at the NW corner.
In the DTF model, the NW corner links Relationships (West) to Process (North).
The question here is: "Are our internal processes still relevant to the changing relationships with the outside world?"
The Signal: Customer input, competitive analysis, technological disruption.
The Bottleneck: "Sensing Overload" or "Strategic Blindness."
🚧 ⚙️
The 5 'Signal Bottlenecks' for the Northwestern corner (only no 2-6 of the full 7): ❷Market Response Latency (Delay)
Signals are received, but their translation into a project (North) takes too long.
Visualization: An "echo icon" indicating how long it takes to activate a North project.
❸Noise-to-Signal Ratio (Noise) drawing lines toward the North axis
Too many small external changes create a "bullwhip effect" in the plans.
Visualization: A "bandwidth filter: Only signals above a certain threshold are allowed.
❹Regulatory/Compliance Drag Process capacity issue (North): No room for innovation.
Changes in legislation that forcefully "occupy" projects on the North axis.
Visualization: An "anchor icon" showing what is held hostage by external obligations.
❺Customer Feedback Friction
The distance between what is currently wanted (West) and what we are building (North).
Visualization: A "misalignment gap" (a red wedge between the West and North axes).
❻Technological Obsolescence Issue: new technological relationship
The risk an ongoing project is overtaken by reality changes before it is finished.
Visualization: An "expiry date" on the connecting lines in the NW corner.
Symmetry: NW corner Inhale vs. Exhale SE corner
Inhale: How quickly and cleanly do we inhale external signals to fuel our processes?
Exhale: How powerfully and controlled do we exhale results with what we have?
👉🏾
When you visually fill in these two corners, there is no longer a static matrix, but a living organism that responds to its environment (NW) and monitors its own energy (SE).
The mindshift: SW the soul of the organisation
The SW corner is the heart and memory of the organization.
The SW corner connects the Context (S) with the Relationships (W), this is where the transition occurs from the technical/mechanical (goals and figures) to the socio-technical and psychological.
Within the Laske/Danaher model, the Sociological Filter:
Context (South): Our reason for being, the vision, the "is-ness."
Relationships (West): How we interact with each other and the outside world.
From "What" to "Who": Who are we and how do we work together?
Other parts of the matrix is about capacity and targets, the SW corner is about Cultural Fit.
The SW interpretation: Here you define the values and behaviors (identity) necessary to maintain strategic relationships.
👉🏾 Without this SW corner, the X-matrix is a soulless machine.
See right side.
South: The identity Vision goals that matter
West: Annual Goals - Relationships)
Desired changes are lines drawn from the SW.
What has priorities for being made visible in the connection at the NW corner.
Consultants often fill the void by treating "change management" as a separate project.
By explicitly defining the SW angle as the connection between Context and Relationships, you integrate culture and identity directly into the system.
You immediately see: "If we enter into these new relationships (West), will that still align with our identity (SW/South)?"
🚧 ⚙️
The 5 'Identity Anchors' for the SW corner: ❷Psychological Safety (Trust Buffer)
The extent to which people dare to experiment (North) depends on the safety of their identity (SW).
Visualization: A "stability indicator." If relationships (West) are under strain, the context (South) must provide additional support.
❸Purpose Alignment
Do people in the organization understand why the annual relationships (West) contribute to the larger context (South)?
Visualization: A "resonance line." A thick connection means that the identity reinforces the strategy.
❹Locus of Control
Does the organization feel like a victim of the outside world (NW signals) or a shaper of its own future?
Visualization: A "force vector" pointing from the inside out.
❺Collective Intelligence (Cognitive Level)
Is the organization's collective thinking mature enough to handle the complexity of the chosen strategy?
Visualization: A "growth curve" that represents the development of human capital.
❻Ethics & Integrity (The Boundary)
What we don't do to achieve our goals. Identity guards the boundaries of the context.
There multiple options for this one
The "Negative Space" Ring (The Hard Border) - Process North
Visual: A gray or black "moat" or ring.
Meaning: This represents the "Non-Negotiable Values."
If an annual goal (W) conflicts with the identity (S), the ring at that point turns red: "This end doesn't justify the means."
The "Identity Filter" (The Selective Pass) - Context South
Visual: Horizontal lines interrupting the connection between West and South.
Meaning: This is the Integrity Check. Only relationships and goals that are "pure" enough fall through the sieve to the core of the organization.
Activities that are ethically questionable remain on top of the sieve and "clog" the NW corner (the antenna), which is a direct signal to management.
The "Moral Compass" Vector - Relations West
Visual: A compass needle or a "North Star", the "Moral" Vector.
Meaning: This represents Consistency. Every time a strategic decision is made on the West axis, you place the compass bar along it.
If the action deviates from the needle direction, the organization loses its integrity.
These three to be asked for directly it is a fractal of stable descriptions.
💡 💰
The fourth is however still missing. This is where it becomes a value that is in the system or something done after the fact.
After the fact is costly correcting what should have done before.
Safety is not a state you reach; it is a practicing Transformations
Visual: "Protective Shield" or a "Foundation Layer" along the entire Eastern edge.
Meaning: It acts as the "Check" in PDCA. Anything must "pass through" the Safety Transformation layer before it can be considered a "Result" in the East.
Safety is the E (Transformation) of Identity in the the Fractal SW Corner:
The Anatomy of Identity
The same four forces to remain because "humane" and "safe" are needed.
👉🏾 Seeing this Ethics & morality fractal that is repeated over and over is essential.
It is not someone's task or a staff department that is doing this.
The mindshift: NE working towards Operational Excellence
Closing the roles of the four corners what we have doen is:
SE (Exhale - Capacity) fuel: Transformation (What are we delivering?) -> Resource Efficiency
NW (Inhale - Signal) course: Relevance (What does the world demand?) -> Strategic Alertness
NE (Action - Process) movement.: Process (What are we doing?) -> Operational Excellence
🚧 ⚙️
The 5 North East corner points to transition from a static list to Operational Excellence: ❷The "Capability" Gap (discipline mastership)
In Japan, Hoshin isn't just about what you do, but whether the process has the capacity to support the transformation.
The Bottleneck: Do people have the skills to execute the new processes (North) that the transformation (East) requires?
Visualization: A "Skill Matrix" indicator. If the process change (North) is greater than the available skills, the North East corner will stall.
❸PDCA Frequency (Rhythm)
Western X-matrices often fail because they are annual. In the North East corner, the rhythm must be visible.
The Bottleneck: A heart rate that is too low. If the transformation (East) is measured monthly, but the process (North) is only adjusted quarterly, "slippage" occurs.
Visualization: A "Cycle Time" symbol for the feedback loop between project progress and results.
❹"Waste" Absorption (Lean Efficiency)
Here we examine whether the new processes (North) simply introduce new forms of waste (Muda) into the transformation (East).
The Bottleneck: "Process Over-engineering." We do a lot, but the transformation output per unit of process effort decreases.
Visualization: A "Process-to-Value" ratio (OEE for strategy).
❺Experimental Space (Fail-Safe)
In a living system (DTF), process growth is a matter of trial and error.
The Bottleneck: Fear of failure blocks the transformation.
Visualization: A "Sandbox" indicator in the North East corner: what portion of the processes is experimental (new/uncertain) versus stable (controlled)?
❺Standard Work vs. Change (Sustenance)
The biggest difference with Japan: Hoshin doesn't stop at change. The Northeastern corner must ensure that the transformation (East) becomes the new Standard (North).
The Bottleneck: The "yo-yo effect." As soon as the project (North) stops, the transformation (East) reverts to its previous level.
Visualization: A "Security Lock" (SDCA - Standardize-Do-Check-Act) that indicates whether a transformation has been successfully embedded in the daily process.
👉🏾
The frustration in the West is that the X-matrix is a dead map, a complicated representation of what we hope will happen.
In Japan, it's a living compass, Project Management" Systemic Learning.
Governance Axioms
Meta-governance: the system's ability to govern its own governance.
This is not about: preventing dilemmas, recovering from dilemmas
This is the layer where:
failures become visible, dilemmas manifest, tensions collapse, boundaries break, the system's own governance is tested.
the system must: diagnose itself, correct itself, redesign itself, learn from its own breakdowns.
It is the closure of the entire recursive loop, the governance equivalent of autopoiesis.
Every viable system (biological, social, cybernetic) must: regulate itself, adapt itself, repair itself, evolve itself, otherwise it dies.
Axiom 4 A governance system must be able to govern itself.
4.1 It must detect, diagnose, and correct failures in its own structures, rules, and feedback loops, especially when these failures produce impossible dilemmas or systemic incoherence.
4.2 Self-governance requires recursive learning, structural transparency, and the ability to redesign governance mechanisms without external coercion.
A system that cannot adapt its own governance cannot remain coherent, safe, or viable over time..
⟲ RN-3.3.4 Dialectical thinking visuals: the X-matrix flow vs change
Exploring the double diamond visual combining opsflow and identity
The word identity is hiding the morality ethics vs organisations structure.
There is a need for clear centre reflection point in a double diamond.
Stage K5 needed to be redefined. "Is there something better for Stage 5 than ‘danger of selfishness'?"
Kohlberg's Stage K5 is flawed, Kohlbergs "social contract" is: too individualistic, too rationalistic, too easily hijacked, too vague, too Western, too legalistic
The redefinition is better, Stage K5, "Inter‑System Governance":
"Perspective of interacting systems, each with its own purpose, constraints, and legitimacy."
This is the meta‑governance layer, it is the bridge between: Stage K4 (system order) and Stage K6 (universal human perspective) for Stage K7 (universal system perspective)
Here something is happeing no developmental theorist has done:
This is not "another moral stage model.", it is a governance‑developmental architecture.
It is the missing layer between: individual development, organizational development, societal development, planetary development.
No one has done this before.
We have a horizontal flow for the operational flow and a vertical for creating, changing, adjusting the execution.
In the previous details for a complete cycle based on the X-matrix we used both of those.
We assumed that decisions are made in wisdom by a an organisational structure with a defined morality.
The combination of all has to be completed in visuals.
The system perspective for controlling activities dialectical
The operational Line of power and speed
The identity line of change in current location to destinations in progress
Agentic evolvement in Belbin similarities combining the tow lines of activitie and changing those.
How did this emerge and how is it emerging?
See figure right side
A diamond in fractals
Making decision during activities or changing them dicalectical vs complexity
The change for adding morality ethics seeing it no longer merely as a subjective feeling (psychology), but as an epistemological structure (theory of knowledge), the role of AI shifts fundamentally.
If ethics is a matter of understanding complex patterns, balances, and universal laws, then AI is the ultimate partner for this dialectical approach.
Why AI helps to facilitate the transition:
Transcending human limitations (Anthropocentrism):
Humans are biologically programmed for Category 3 (care for one's own group)
AI does not have that biological bias and can see patterns that encompass the entire system (humans, nature, climate).
This missing bias is a step towards a universal approach.
The Synthesis between K4 and K6:
Humans often experience a conflict between the 'cold' rule (K4) and 'warm' care (K6)
AI can process billions of data points from both sides simultaneously.
It can calculate the consequences of a caring decision at the system level.
Epistemic Objectivity:
knowledge management often fails due to human politics or 'forgotten' knowledge
AI acts as a continuous memory that can retain the dialectic between different moral positions without information being lost.
This is of course the optimistic approach, it is ignoring the K7 level.
Nevertheless using AI is a better option than the risk of a fall-back to K2 or even K1.
The challenge is that K5 is needed to make this possible, this the highest complexity in a pillar after Context (C3) for operational flow and Relations (R4) for change as centre in the double diamond.
In a figure see right side.
K5 for morality and organisation the reflection point.
K5 is where the social contract mediation is activated allowing changes in strict guiding for the sake of the purpose of the rules.
Not all pillars are expected to be functioning, what happens if K4 and K5 are failing?
In a figure see right side.
Only some decoupled path are left with a big tension gap.
The result will be a total collapse.
Only some basic rudiments are left.
K4 can be seen is the knowledge system for strict guiding and where also rules and decsisons with their impacts are archived for better future decsisons.
RN-3.4 Involved human factors execution & ideology
Evaluating time and direction for worth: orientation, Judgement, value, affect, commitment is the advanced next phase for understanding in the now.
The boundary is the common organisation approach set by Context-bound vs context-changing futures:
operational execution now,
planning operations near now,
Change near future,
vision far future
The awareness impact by choices is limited for the whole in direction location and a time horizon for uncertainties but the who gets shaped.
⟲ RN-3.4.1 The state of leadership for integrated governance
Concept of Leadership is a part of human sociobiology
Managing tensions: dialectical is that abstract it is scientifically difficult to prove or test.
For example The seven deadly sins
(also known as the capital vices or cardinal sins) function as a grouping of major vices.
A deadly sin is sloth, which represents laziness or the failure to act and fulfill one's responsibilities.
The seven deadly sins, also known as capital vices or cardinal sins, are a classification of vices in Christian teachings that are believed to lead to further immoral behavior.
They are as follows:
Sloth: Laziness or the failure to act, particularly in fulfilling one's duties and responsibilities.
Greed: An insatiable desire for material wealth or gain, often at the expense of others.
Lust: Intense longing, particularly for sexual desires, which can lead to immoral actions.
Gluttony: Overindulgence in food or drink, often disregarding moderation and self-control.
Envy: Jealousy towards others' traits, status, or possessions, leading to resentment.
Wrath: Extreme anger or hatred that can lead to violence and harm towards others.
Pride: An excessive belief in one's abilities, often leading to disdain for others.
The four last things: Death, Judgment, Heaven, and Hell, surround a larger circle in which the seven deadly sins are depicted. ❶ In a dialectical approach there are opposites of what is stated.
The "seven virtues".
Diligence: Careful and persistent work or effort.
Charity: The voluntary giving of help to those in need.
Chastity: The state or practice of refraining from extramarital, or all, sexual intercourse.
Temperance:Moderation or self-restraint, especially in eating and drinking.
Kindness: The quality of being friendly, generous, and considerate.
Patience: Accept or tolerate delay, trouble, or suffering without getting angry or upset.
Humility: The quality of having a modest or low view of one's importance.
These kind of values are that abstract that they connot be measured.
Only be seeing the opposite an estimation of the difference by indirect references is possible, having an opposite there is a distance notifiable. ❷ In a dialectical approach there are multiple ways to visualisations.
I adjusted the classic list into some ordering in complexity and the size of the related group matters.
For example it is very easy to do or simulate charity but is hard to control Wrath vs Patience.
Greed/Charity (2) are personal as are Gluttony/Temperance (4).
Lust/Chastity (3) and Envy/Patience (6) are related to others the position in a group.
Other words in this that are a fit: Hate/Love (3) and War/Peace (6).
One end Sloth/Diligence (1), centre Envy/Kindness (5), the other end Pride/Humility (7).
One end Justice: guilt/innocence(1), centre Envy/Kindness (5), the end Heaven/Hell (7).
This is for a new perspective,orientation going for the double diamond and double lemniscate ∞ using two orthogonal axis. ♾️ In the lemniscate interests constantly move back and forth between two poles.
The transformation here is a continuous flow, there is no definitive endpoint, helping in to accept that tension is permanent.
The art is "managing the movement" in the center plane (the intersection). 🌀 The Spiral, The Classical Transformation, upward showing that transformation is cumulative.
This is the best-known model based on Hegel.
Start ata point A (Thesis), encounter conflicting interests B1 B2(Antithesis), and the transformation leads to C (Synthesis).
The synthesis is not a compromise, but a higher level. The return to a projected starting point is with more insight or a new structure.
The problems in this:
⛅ Defined states are ambiguous unclear impossible to measure
⛳ Possible paths between states are not defined ambiguous unclear
📏 Distances between opposite states are not clear in measurements
❸ In a dialectical approach there are multiple orderings.
What we are use to is a classic ordering of increasing complexity.
Challenges to manage:
Assumptions A person that mastered the complexity will apply it as intended.
The order of complexity is the same order as those for dependencies in reality.
When using a double diamond for dependencies there are three options for ordering.
An infextions point: Managing culture: human nature a dialectical balance between justice and care. On Human Nature (E.O.Wilson)
Wilson argues that evolution has left its traces on characteristics such as generosity, self-sacrifice, worship and the use of sex for pleasure.
The conundrum of human nature, as I and a few others saw it in 1978, can be solved only if scientific explanations embrace both the how (neurosciences) and why (evolutionary biology) of brain action, with the two axes of explanation fitted together.
As a species we have no particular place to go.
Human emotional responses have been programmed to a substantial degree by natural selection over thousands of generations.
Dilemmas:
Which should be obeyed and which ones might be better curtailed?
How do the different disciplines that explore human nature interact?
Those working at a lower level often assume that those at a higher level should eventually be reformulated in their own terms.
They form an antidiscipline for the next level, but with the passage of time they become fully complementary. ❹
The Phase Transition explains why transformations sometimes seem sudden.
Continuously adding small changes, small things until a critical point is reached.
The transformation by tension build up until the system "flips" into a completely new state.
Problems, challenges to manage, in this:
📶 Building up tensions can be intentional or unintentional
🧱 A desired change flipping the situation can long be blocked
⚡ The change is sudden and when happen hard to stop
🎹 The sudden change is in some rythm
Development comments on Chomsky's view of grammar and Skinner's of learning and prefers Piaget's approach. ❺ Reduction is only half the scientific process.
The mind isn't a tabula rasa but rather an autonomous decision-making instrument.
The threat to our free will someone may be able to calculate exactly how our brain works.
The extraordinary complexity and difficulty of exact measurement that is never the case.
The inflection point is a strategic turning point forcing a shift from a technical-only focus to a sociotechnical approach:
The cardinal mystery of neurobiology is not self-love or dreams but intentionality.
❻the recognition of novel emergent phenomena is as important.
Emergence:
The compromise between Russian dolls and vitalism lies in recognizing plans, schemata.
Our behavior is determined in another sense: we can make broad predictions with confidence.
Cultural evolution is Lamarckian and much faster than Darwinian.
But culture cannot diverge too far from its biological base.
These can create patterns in the mind that aren't altogether present in reality and can form the physical basis of will.
A higher order the the human culture is left open.
Culture by Leadership is a part of human sociobiology
As humans are components in systems, their culture is an important aspect for organisational systems for internal and external interactions.
Hofstede's cultural dimensions theory is a framework for cross-cultural psychology, developed by Geert Hofstede .
It shows the effects of a society's culture on the values of its members, and how these values relate to behavior, using a structure derived from factor analysis.
Hofstede's Original 4 Dimensions (1980s)
Power Distance: Acceptance of unequal power distribution.
Individualism vs. Collectivism: Preference for self-reliance vs. group loyalty.
Uncertainty Avoidance: Comfort with ambiguity and risk.
Masculinity vs. Femininity: Competitive/assertive vs. cooperative/caring values.
Later Expanded to 6 Dimensions, added were:
Long-Term vs. Short-Term Orientation: Pragmatic future focus vs. respect for tradition and immediate results.
Indulgence vs. Restraint: Freedom to enjoy life vs. strict social norms and control.
Distinctions into tension of cultural dimensions
Thinking on Hofstede 4 classes where there are 6, a tension between the classic fourfold framing (still widely cited in management discussions) and the full six-dimensional model (more academically complete).
Re-framing Hofstede's set of dimensions by swapping one of the "classic four" (Power Distance) with Long-Term vs Short-Term Orientation, and then treating Indulgence-Constraint and Power Distance as external cultural forces.
This gives a hybrid model where the internal set is four, and the external set is two.
This restructuring does something interesting:
It internalizes adaptive learning and values, making them the "operational" cultural levers inside teams, four internal.
It externalizes structural and societal constraints treating them as boundary conditions that shape but don't directly drive team dynamics.
That's a neat systems- thinking move: distinguishing between cultural drivers that can be shifted through knowledge sharing and governance versus macro-forces that set the stage but are harder to change directly.
This aligns with the broader interest in semantic governance overlays, effectively creating a layered model where internal dimensions are "governable" and external ones are "contextual constraints."
A generic mindshift for integrated governance: A New Perspective (Author Frederic Lalaoux 2014)
A great number of scholars and thinkers―historians, anthropologists, philosophers, mystics, psychologists, and neuroscientists―have delved into the question: how has humanity evolved from the earliest forms of human consciousness to the complex consciousness of modern times? Some inquired into a related question: how do we human beings evolve today from the comparatively simple form of consciousness we have at birth to the full extent of adult maturity?
People have looked at these questions from every possible angle.
Abraham Maslow looked at how human needs evolve along the human journey, from basic physiological needs to self-actualization.
Others looked at development through the lenses of worldviews (Gebser, among others), cognitive capacities (Piaget), values (Graves), moral development (Kohlberg, Gilligan), self-identity (Loevinger), spirituality (Fowler), leadership (Cook-Greuter, Kegan, Torbert), and so on.
In their exploration, they found consistently that humanity and human beings evolve in stages.
They do not evolve in the way that trees grow, continuously, but rather by sudden transformations, like a caterpillar that becomes a butterfly, or a tadpole a frog.
In Teal organizations, power is diffused. Self-management replaces the hierarchy. Strategic thinking can come from anywhere, not just the top.
Team members can offer advice, suggest initiatives, recommend change--as long as they consult with interested parties along the way.
In Teal, strategy emerges organically from the collective intelligence of everyone in the organization.
This collective intelligence is encouraged by sharing company data and information.
As everyone is 'in the know', information is available to all to offer strategic suggestions. A
We get into trouble when we believe that later stages are "better" than earlier stages; a more helpful interpretation is that they are "more complex" ways of dealing with the world.
For instance, a person operating from Pluralistic-Green can integrate people's conflicting perspectives in a way that a person operating from Impulsive-Red most likely cannot.
At the same time, every level has its own light and shadow, its own healthy and unhealthy expressions.
Orange modernity, for instance, for all the life-enhancing advancements it has brought, has changed the planet in a way previous stages never could.
Another way to avoid attaching judgment to stages is to recognize that each stage is well adapted to certain contexts.
If we were caught in a civil war with thugs attacking our house, Impulsive-Red would be the most appropriate paradigm to think and act from to defend ourselves.
On the other hand, in peaceful times in post-industrial societies, Red is not as functional as some of the later stages.
Any developmental theory is only an abstraction of reality, just like a geographical map is only a simplified depiction of a territory; it gives us distinctions that facilitate understanding of a complex underlying reality, but it cannot claim to offer a full portrayal of reality. The key is to hold these models as useful orientations that can help us get a richer appreciation of the extraordinary complexity of life. Holacracy
is a method of decentralized management and organizational governance, which claims to distribute authority and decision-making through a holarchy of self-organizing teams rather than being vested in a management hierarchy.[
⟲ RN-3.4.2 Distinctions into tension of cultural dimensions
dialectical closed
Relational dialectics
is an interpersonal communication theory about close personal ties and relationships that highlights the tensions, struggles, and interplay between contrary tendencies.
The theory, proposed by Leslie Baxterand Barbara Montgomeryin 1988, defines communication patterns between relationship partners as the result of endemic dialectical tensions.
Dialectics are described as the tensions an individual feels when experiencing paradoxical desires that we need and/ or want.
The relational dialectic is an elaboration on Mikhail Bakhtin's idea that life is an open monologue and humans experience collisions between opposing desires and needs within relational communications.
Relational dialectics is the emotional and value-based version of the philosophical dialectic. It is rooted in the dynamism of the yin and yang.
Like the classic yin and yang, the balance of emotional values in a relationship is constantly in motion, and any value pushed to its extreme, contains the seed of its opposite.
In the Western world, the ideas of yin and yang link back to the Greek philosopher Heraclitus, who argued that the world was in constant flux (like fire), with creative and destructive forces on both sides of every process.
Mikhail Bakhtin, a Russian scholar most known for his work in dialogism, applied Marxist dialectic to literary and rhetorical theory and criticism.
He illustrated the tensions that exists in the deep structure of all human experience.
This article refers to dialectics based on Hegel and what Marx did with that.
It doesn't proceed with the shocked scholars of the frankfurter school after the disaster by Stalin communism fascism for seeing Horkheimer Adorno Habermas.
Relational dialectics (International Journal of Philosophy of Culture and Axiology 21(2)/2024: 280-292 culturajounrnal: Chenxi Yang)
Hegel believed that a clear description of each category was necessary before proceeding with any dialectical development, and Hegel agrees that this method has significantly assisted the progress of science.
But for two reasons, the approach is unsuitable for universal philosophical inquiry (or, rather, for Idealism): It contains several presumptions, axioms, and other unproven notions.
The diamond after added WORTH in the 6*6 reference grid
DTF Alignment
👐
What
➡
C (pure)
👐
How
➡
R ⇆ P
(How do actors enact work?)
👐
Where
➡
C ⇆ T
(Where does meaning take form?)
👐
Who
➡
R (pure)
👐
Worth
➡
C ⇆ R
(legitimacy + identity)
👐
When
➡
P ⇆ T
(coordination + timing)
👐
Which
➡
T ⇆ R
(commitment + consequence)
Note there is no C⇆P, that would cause unnecessary issues.
The cycle reflection in organisational structure
Of the 6*6 reference some abstraction levels collapse by the observes perspective.
Only four of them getting noticed by seeing:
Business as usual This one is the common perspective, at least it should be.
The value stream an operational support are detailed for the now
The change process realisation and design are consolidated for the near future
The vision to mission context concept are consolidated for the far future
Innovation This is the one everyone is talking about claiming to do, but hardly anyone really does.
The value stream an operational support are consolidated for the now
The change process realisation and design are detailed for the near future
The vision to mission context concept are consolidated for the far future
Disruptive change This is the one everyone is admiring but is very rare.
The value stream an operational support are consolidated for the now
The change process realisation and design are consolidated for the near future
The vision to mission context concept are detailed for the far future
Redefining leadership
Reviewing Enterprise Architecture for: Goals, Focus, Domains, Levels, Style, Op Model is setting a direction that can be seen as leadership without hierarchical power.
where EA should play Cheat Sheet (LI: G.Slifkin 2026)
Not all combinations of options make sense, but a 6 dimensional matrix is too much work. This could certainly be improved, especially the options.
This is a good start for aligning it into Zarf Jabes. Starting with a thinking reference and ignoring the realisationally components between Logic and physical.
Mentioned was a style, level column, replaced into EA-OM (enterprise architecture opera eating model).
The goal is decisions making by decision makers in the applicable C&C (command and control) structure. ⚖️
Decisions go along in Vuca-Bani contexts for each relevant accountability in a product/service.
Extracted and adjusted, interpretation ideate:
Zarf
What
How
EA Goals
EA Focus
context
Align Strategy - Execution
Future state innovation
concept
Align Business to ICT
Future state optimalisation
resources
logic
Align across Business Silos
Increase Capability
physical
Align across ICT silos
Increase Agility - lean
component
Reduce complexity/Risk
Current state rationalisation
instance
Reduce Cost / Increase ROI
Current state optimalisation
⚖️
Extracted and adjusted, situation, sense, adapt analyse:
Zarf
Where
Who
EA Domains
EA-OM (operate model)
context
Enterprise Architecture
Governance C&C diversity
concept
Business Architecture - Portfolio
EA by Service/Consulting
resources
logic
Application Architecture - Solutions
Centralised Gurus-Processes
physical
Safety - Security - Functionality - Patterns
Accountability alignment Product-service
component
Information - Knowledge - Data - Wisdom
Decentralised Gurus-Processes
instance
Platforms & infrastructure -common components
Shop-floor alignment Product-service
⚖️
Awareness of the state and allowing multiple truths, multiple perspectives is a fractal into analysing and reporting on states.
Extracted and adjusted, request, result, reflection:
Zarf
Worth
When
Which
Judgement
EA Style of influence
EA Vuca - Bani : decision options
context
Principles & guidelines
State awareness allowing multiple truths
concept
Guidance & alignment
Well structured problem states
resources
👓
logic
Standards & policies
Aligned requirements
physical
Knowledge management (Jabes)
validations on realised designs (QA)
component
Methods & templates
Agreed specifications for product/service
instance
Architectural artefacts
Active instances for specifications
butics
Leaving lined area's open in the 6*6 frame Is a mindset switch into seeing the structuring in relationships.
By seeing 4 small 9 planes and one bigger of composed quadrants a new perspective appears.
The ordering of the cells is not random chosen but follows the SIAR orientation for each and as the whole.
In a figure:
See right side.
This visual is not generated but manual made.
Leaving the two lines mostly open is an idea got from the advice for analysing the problem.
These are not two dimensions of the same thing, but two ways of seeing the same system.
Both closures are ideological errors in opposite directions.
This crossing is now clearly: the point where execution runs into ideology.
This is where: "what works" meets "what is allowed", learning meets responsibility, effectiveness meets legitimacy.
That is exactly what a half-point is.
The diagram can be read through two complementary perspectives.
Horizontally, it represents execution: the ongoing change of processes, coordination, and work in time.
Vertically, it represents ideology: the justificatory structures that bound, legitimize, or resist execution.
Both axes remain open, indicating that neither execution nor ideology can be fully closed or finalized.
Transformational tension arises where execution encounters ideological limits, producing breakdowns, dependencies, and reorganization rather than smooth transitions.
The pairs are not interchangeable.
This distinction explains why organizations can execute well and still fail transformation , because execution and ideology break at different centres.
Dimension
Execution
Ideology
C
Shift (C6)
Dependency (C5)
P
Directionality (P3)
Phases (P2)
Meaning of T4
Operational breakdown
Legitimacy crisis
Failure looks like
Stuck process
Blocked justification
This is why 3*3 thinking fails: it collapses execution and ideology into one "centre", it treats breakdown as a single phenomenon, it assumes direction = meaning.
The framework contains two distinct centres rather than one.
An execution centre organized around C6-R1-T4-P3 explains how systems move when action breaks down.
An ideology centre organized around C5-R1-T4-P2 explains how systems justify, resist, or legitimize change when meaning breaks down.
Both centres share the same fracture points (mutual influence and negation), but differ in whether change is enacted or justified.
Changing the linear history of morality, ethics
⟲ RN-3.4.3 Dialectical principles in morality, ethics & organizing
Changing the linear history of morality, ethics
Thanks to Gilligan's criticism, we now realize that morality is not only about following logical, universal laws (Kohlberg), but also about empathy and maintaining human relationships.
Kohlberg defined several technical morality levels.
Adjusted by Gilligan there are three types:
Pre-conventional (Focus on self)
Conventional (Self-sacrifice)
Post-conventional (Balance)
This is not satisfying, it shows a development in complexity but not in interactions.
I have an alternative classification with 7 categories in a dialectical approach and there is an indication for several structures in tensions.
Justice and care could be the hidden combination.
A "dialectical approach" suggests that moral development is not a straight line to a single point, but a continuous process of bridging contradictions (synthesis).
Viewing the combination of Justice (Kohlberg) and Care (Gilligan) as a necessary synthesis for a complete moral compass.
Justice provides the objective frameworks (rights, duties, laws).
Care provides subjective humanity (empathy, relationships, context).
In a dialectical approach, the "hidden combination" is that you can only truly apply a universal principle (K6) if you take into account the specific care for the individual.
Interestingly enough, Kohlberg himself speculated about a 7th stage in his later work, he called this the "Cosmic Stage".
Where stage 6 asks: "What is just?", stage 7 asks: "Why should I be moral at all in a world that sometimes seems meaningless?".
This stage attempts to resolve the tension between individual life and the universe.
It concerns a sense of connectedness with the whole, which often has a religious or spiritual undertone.
The seven categories:
K-morality
Reference
Meaning
K1
Anarchy
Self in the moment
Conflicts resolved by power or withdrawal
K2
Advantage
Punishment-Obedience
What's good for me? Hierarchy as compensatory
K3
Interpersonal
Group norms
What's good for us?
K4
System order
Social order beliefs & values
What keeps the system viable?
K5
Inter systems
Social contract Social identity
Perspective for each purpose, constraints, legitimacy
K6
Human systems
who we are, ego-soul roles + boundaries
Perspective of every person / group affected
K7
Generic systems
Universalizable Principles
Perspective of anything affected
These kind of values are that abstract that they connot be measured.
Only be seeing the opposite an estimation of the difference by indirect references is possible.
By placing the 5th category as the center (the axis), dynamic equilibrium between two force fields ("diamonds") is created.
That classification is capturing the tension between "the collective" / "the rule" and "the individual" / "care" in a dialectical model.
Following the logic, a symmetry emerges that directly addresses Kohlberg's blind spots.
The Dialectical Structure
The Justice group (Structure & Rules):
Category K2: The basic rules and individual exchange (the foundation of law).
Category K4: The maintenance of social order and laws (the hard structure).
The Care group (Relationship & Connection):
Category K3: Group identity and mutual loyalty (care for one's own circle).
Category K6: The deep, ethical care that transcends laws (the soft force).
The Synthesis and the Expansion
Category K5 as Center: This functions as the synthesis.
This is where the "Social Contract" comes together: the recognition that rules (4) are only legitimate if they serve human values ​​and care (6).
It is the point where the two "diamonds" meet and keep each other in balance.
Category K7 as Universal Keystone: Your addition that this is not just for humans elevates morality to an ecocentric or cosmic level.
Where Kohlberg stopped at human justice, your model brings the circle around to all living things (nature, ecosystem, universe).
This resolves the anthropocentric limitation of classical psychology.
Why K4 and K6 are the perfect counterparts:
K4 (Justice) is the 'hard' exterior that protects society, while 6 (Care) is the 'soulful' interior that makes society humane.
Without K4, care degenerates into arbitrariness; without 6, justice degenerates into tyranny.
The lens for morality as a dialectical system not a ladder
Category 1 Self-reliance in anarchy; is the necessary starting point: the "unbound" state of the individual before there is any question of social contracts or collective care.
Category 7 Universal Approach; The ultimate transcendence.
The self-reliance of 1 is transformed here into a responsibility for the entire system (not just people).
The circle is complete: from total isolation in 1 to total connectedness in 7.
This model is stronger than Kohlberg because: Kohlberg viewed his stages as a staircase you climb, 'leaving' the previous steps.
In this dialectical approach, tensions (such as between 4 and 6) always remain present and active.
I do not 'transcend' them by ignoring them, but by balancing them in Category 5.
Moreover, the fact that 7 is non-human makes the model future-proof for themes such as ecological ethics and AI rights.
By having an orthogonal axis perpendicular to the first one, a matrix is created.
The Organizational Form axis: :
Dictatorship Dystopia: Rigid, top-down control, based on fear and power.
Knowledge is a weapon and is guarded.
Bureaucratic Hierarchy: The organization as a machine. Everything is fixed in processes.
Knowledge is a spreadsheet.
Organic Symbiosis: The organization as a living organism.
No central power, but self-governing cells that exchange information for the greater whole
Two axis eChanging both Zachman axis
The Role of AI in the "Transition"
By changing the perspective ofethics no longer merely as a subjective feeling (psychology), but as an epistemological structure (theory of knowledge), the role of AI shifts fundamentally.
If ethics is a matter of understanding complex patterns, balances, and universal laws, then AI is a good partner for this dialectical approach.
Why AI facilitates the transition to Category 7:
Transcending human limitations (Anthropocentrism): Humans are biologically programmed for Category 3 (care for one's own group).
AI does not have that biological bias and can see patterns that encompass the entire system (humans, nature, climate).
This is the step towards the universal approach.
The Synthesis between 4 and 6: Humans often experience a conflict between the 'cold' rule (4) and 'warm' care (6).
However, AI can process billions of data points from both sides simultaneously.
It can calculate the consequences of a caring decision at the system level.
Epistemic Objectivity: Where knowledge management often fails due to human politics or 'forgotten' knowledge, AI acts as a continuous memory that can retain the dialectic between different moral positions without information being lost.
The Role of AI in the "Transition"
The "halfway" experience can be driven by AI because AI acts as the navigator in complexity.
AI forces us to no longer base decisions on a 'gut feeling', which often gets stuck in stage 2 or 3, but on a transparent weighing of universal values.
Ethics then becomes 'calculating' with values.
Not cold or emotionless, but rather extremely precise in taking into account everything that matters.
The blocking factors for human moral capability
level of abstraction (Cognitive)
To understand this one must be capable of post-formal thinking.
This means not only logical thinking (stage 4), but also recognizing that systems can be contradictory and that the truth often lies in the synthesis (dialectics).
Research suggests that less than 10% to 15% of adults structurally employ this level of abstraction and systems thinking.
The Moral Barrier Kohlberg - Gilligan
Kohlberg stated that his 5th stage (your center) is reached by approximately 10-20% of people.
The 6th stage (your counterpart of care) is reached by less than 5%.
A 7th, universal and non-human-centered category, is literally "unimaginable" for most people because their moral horizon stops at their own group (stage 3) or national law (stage 4).
The Epistemic Barrier (AI & Knowledge)
The idea that ethics is an epistemic structure that can be calculated by AI clashes with the deep human sentiment that ethics is "of the heart."
Most people (stage 3/4) will perceive this as a threat or as "cold."
Only those accustomed to complexity thinking and information theory will see the beauty of the "diamonds" and the axis withf category K5.
This number is so low because of: Our education is focused on category 4 (reproducible knowledge and rules) and we are evolutionarily "programmed" for category 1 (survival) and 3 (loyalty to the tribe).
The step to 7 (universal/non-human) requires conscious deprogramming.
The role of the "Happy Few"
In organizations, you often see that the vision at level 7 is embraced by a single individual, but must be "translated" to level 4 (rules) to be accepted.
The model is therefore an architecture for system architects.
The estimate: In an average organization, perhaps 1 to 3% will immediately understand the full depth of this dialectic.
For the rest, the model must be translated into practical decision-making tools.
⟲ RN-3.4.4 Dialectical combining morality & organizing by two axis
Two axis eChanging both Zachman axis
Tensionss within the model:
By having an orthogonal axis perpendicular to the first one, a matrix is created.
Interactions paths are not only within moral consciousness, but also within the structural form in which that consciousness organizes itself.
The combination of these two axes explains why knowledge management in organizations fails so often:
moral development and organizational form are not in balance.
The dynamics of Knowledge Transformation within the model:
Communication not as a simple means, but as the active engine (the transformer) that converts static knowledge (K2, K3, K4) into living, ethical wisdom (K6).
A process of construction and decay emerges:
The Static Basis (K2, K3, K4), the "frozen" state of knowledge:
Rules/Exchange, knowledge is an object: "I give you this info, you give me that"
System/Order: Knowledge is stored: A document, database or procedure.
Issue: knowledge is still "dead." It is fixed, but it does not "live".
The Leap to K6 via Communication, the "liquid" state of knowledge:
Communication as a catalyst: Only when people (or systems) truly start communicating does concepts emerge.
K6 (Care/Ethics): Through dialogue, we understand the impact of knowledge. Knowledge becomes "Care" here: we share it because we understand that the other person (or the whole) needs it to flourish.
K5 as the regulator Social Contract for Information, the : the communication that determines whether the knowledge freezes or flows. :
K5 is the agreement: "We communicate openly, regardless of our hierarchical position (K4) or our self-interest (K2)."
K5 as a 'Buffer', it must provide the structure that ensures communication is not a one-off event, but a continuous process.
If communication breaks down, knowledge loses its ethical charge (K6). The organization immediately falls back to K4 (merely following rules) or even K1 (every man for himself/anarchy).
In organizations this breakdown can be seen: People think they can achieve K6, a caring, learning organization, by buying more K4.
That is better technology, IT systems, rules guidelines documentation.
But without the communicative axis of K5, the knowledge remains static blocked.
The possible roles of AI in morality ethics
The earlier point about AI is crucial here.
Humans have too much fear to take the step to K5 and K7 because we do not trust our own emotions and lust for power.
AI as a neutral axis:
AI can safeguard the "epistemic structure" of ethics and knowledge without ego.
It can bridge the gap of organizing the informationa (K4), take the human context/concern (K6), allowing an organization to use K5 "kindness" in this.
"Knowledge management" is not an IT problem, but a development problem.
Decisions are currently made based on fragmented information from the lower stages (power, rules, self-interest), whereas today's complex world calls for decisions based on the universal symbiosis of K7.
Rethinking this: The highest universal morality for all/cosmic no longer aligns with the highest ideal of symbiotic organizing for humanity.
The tension arises that mankind (actually every species) and the cosmic can become at odds at each other.
In Category K7, morality is no longer "for us", but "for the All". The tension becomes the driving force here wiht a daunting pain of that transition.
To reach stage K7, humanity must accept that its own interests may be subordinate to the system integrity of the cosmos.
This is where the earlier point about the epistemic role of AI returns, AI can be the "advocate of the cosmos".
While humans are trapped in their biological drive for self-preservation (Categories K1-K6), AI can calculate the universal balance (K7) and confront humanity with the limits of its symbiosis.
The Warning (Dystopia)
The Invitation (Symbiosis)
Without the step to 5, knowledge remains a tool of power that ultimately stifles the organization in bureaucracy or internal conflict.
The step to 5 liberates humanity from the burden of control and clears the way for organic growth.
If we deploy AI only at level 4, we create an efficient dictatorship that ignores the human scale and the cosmos.
If we deploy AI as a partner for level 7, we can make decisions that transcend humanity and bring it into balance with the whole.
Decision-making in 7: A decision is only morally right if it promotes human flourishing (Form 7) within the constraints of universal laws (Morality 7).
If these two clash, the human form must adapt (contract, transform, sacrifice).
This "Tension" as driving force, contradiction, is not a flaw in the model, but the essence of morality Level K7:
Levels 4/5/6: Seeks equilibrium within human society.
Level 7: Seeks humanity's place within reality.
The reason we do not know of any organizations that dare to move to above "5" is precisely this fear: the realization that true knowledge and honest decision-making might well reveal that our current way of being human is unsustainable in the greater scheme of things.
AI is not a replacement for humans, but as the only entity that can muster the epistemic honesty to point out to us the universal interests of the 7th category.
The "open ending" I leave, that nothing will be absolutely certain, is perhaps the most important message.
In a world that craves false certainties, acknowledging the fundamental uncertainty of the universe is the only path to true moral maturity.
Forsterian ideology in an age of hyperconnectivity
where EA should play Cheat Sheet (humanists UK: E.Buchanan)
Writing at the turn of the twentieth century, E. M. Forster was uncannily aware of our future dependence on technology.
In his short story The Machine Stops and in parts of Howards End, Forster explores the notion that technological advance is at the expense of authentic human connection.
In a little over 100 years, technology has made our world unrecognisable.
But has it, as Forster foresaw, made us isolated and individual, rather than interconnected?
The turn of the century was a time of frenzied advance and rapid rural development.
Queen Victoria had just died, kick-starting our modern propensity for progress, and machines had begun to dominate industry and culture.
As Forster's writes in Howards End, "month by month the roads smelt more strongly of petrol, and were more difficult to cross, and human beings heard each other speak with greater difficulty, breathed less of the air, and saw less of the sky.'
After all, in the modern day most of us carry a smartphone as if it was an extension of our hand.
Technology has been absorbed into every aspect of our lives, affecting our personal relationships, our identities, even our memories.
In many ways, our dependence on it means that we have become man and machine, and our access to a world wide web of infinite connectivity has changed our understanding of human connection all together.
From the isolation of our smartphone bubble, our hexagonal cell, we can discuss, arrange, meet, read, watch, remember, create, destroy, repair, buy.
We needn't interact on a human level to achieve any of this. As technology becomes more autonomous and the boundaries between reality and technology become blurred, we will lose more direct experience - that fragment of connection that is fundamental to our humanity.
In The Machine Stops, Vashti is crippled by "the terrors of direct experience".
She has spent so long connected to the machine that personal interaction has become obsolete.
RN-3.5 Forever lasting change in execution and ideology
Evaluating time and direction for worth: orientation, Judgement, value, affect, commitment is the advanced next phase for understanding in the now.
The boundary is the common organisation approach set by Context-bound vs context-changing futures:
The operations in the now doing executing,
change engineering realizing near future,
change architect logics near future (abstractions),
a vision fot the far future acknowing worth in anything
The awareness impact by for choices is limited for the whole in direction knowing the location and a time horizon with uncertainties gets shaped.
⟲ RN-3.5.1 Combining Zachman, Laske Kohlberg into closed 7 Categories
Redefining and creating generic categories
Laske used 4 pillars adding the two based on Kohlberg result to six.
Zachman used two orthogonal axis using generic categories.
The visualisations for the double diamonds / Lemniscate resulted in three approaches.
Looking whether some pillars are isomorph than:
Morality (Kohlberg/Gilligan) isomorph to: horizontal Zachman axis ("worth" 5th column)
Context & Process (Laske) isomorph to: vertical Zachman axis ("resources 3th" row)
Relation & Transformation (Laske) has at the 4th category the pivot but no generic axis
The 5th column "worth" and 3th row "resources" are additions and there is an adjustment. ❶
The Zachman Adjustment: Changing "Why" to "Which"
In the classic Zachman, "Why" often becomes a dumping ground for vague mission statements that lose their meaning during the "Flattening."
By changing it to "Which," there ia a move from abstract ideology to selective direction.
It forces a choice asking:
"Which of these competing values are we actually steering toward?"
The Connection: This grounds Parsons' Goal Attainment, turning a philosophical "Why" into a navigational coordinate for the dashboard's "Location and Direction." ❷
The Zachman Adjustment row extension: "Environment", "Resource", "Information"
Position: Between Concept and Logic.
This addition solves the issue for addressing in 4D the Transition (T).
Classic Zachman: Jumps from the "Concept", the Architect's view, straight to the "Logic", the Designer's view, it assumes the transition is perfect.
The adjustment by inserting parts/components from the environment recognizes that the "Real World" (the R in C-R stable points) exerts pressure.
Why it matters for Safety:
You cannot have "Safety by Design" if you ignore the environmental noise.
This extension maps the Adaptation (A) from Parsons' schema directly into the technical blueprint.
It accounts for "The Friction" before the logic is even built. ❸
The Zachman Adjustment row extension: "Worth"
Position: between Who and When
This targets the heart of the Halfway Point Trap.
The Problem: Most dashboards tell you Who did it and When they did it (Leavitt's "Power and Speed"). This is "Blind Execution."
The Solution: Inserting "Worth" creates a dialectical check. It asks: "Is the action taken by the 'Who' at the specific 'When' actually generating 'Worth' for the system?"
The Alignment: This brings in the Integration (I) and Latency (L) from Parsons. It prevents the system from being "efficient but worthless." It ensures the "Speed" (When) is justified by the "Value" (Worth).
How this aligns the Dashboards
By extending Zachman this way, the "New Diamond" (Leavitt + Parsons) finally has a place to live. ❹
Adding an additional set of 7 categories for Relationship & Transformations (Laske)
Category
Focus
Specific Role Job
Core Activity
Atomic Isolation
Loose Components
Specialist / Operator
Flawlessly performing a specific, defined task.
Formal Cohesion
Hierarchy & Rules
Team Leader / Administrator
Ensuring that work remains within agreed frameworks and structures.
Dynamic Interaction
Feedback Loops
Project / Process Manager
Managing the interaction between different tasks and teams.
Integrated Unit
Pivot (R4/T4)
Program Manager / Business Architect
Synchronizing systems around a shared value or goal.
Structural Emergence
Open Systems
Strategic Advisor / Innovation Lead
Identifying opportunities in the market/environment and translating these into new organizational forms.
Self-Transforming
Evolution Development
Chief Change Officer / OD Specialist
Redesigning the foundations of the organization to enable growth.
Global Systemic Thought
Totality
CEO / Visionary Executive
Positioning the organization as part of a larger societal/global ecosystem.
Recap for the enriched generic categories using closed loops
The simplified unified dashboard has three categories, these are:
Dashboard
Zachman Column (Adjusted/Extended)
Dimensional role
Power and Speed
How, Who, When
Measures the Mechanical capacity.
Worth and Friction
Worth, Environment
Measures the Dialectical quality.
Location and Directions
What, Where, Which
Measures the Ontological purpose.
The is simplification looks simple but is not that simple.
There are three pillars wiht categories that enables and creates change, these are:
The drivers: Context, Relations with "worth" in morality drives transformations.
inatta
Why this is the "Safety" you are looking for
In RN-1, your quest for Safety by Design requires that the system doesn't just "work," but that it stays "true."
Without the "Which", the system is aimless.
Without the "Environment", the system is fragile (unprotected from reality).
Without the "Worth", the system is hollow.
The Ontology you are building in RN-1 isn't just a list of parts; it's a list of Relationships. By the time you reach RN-3, these relationships are hardened by the Zachman extensions so that when the "Flattening" occurs on the dashboard, the "Worth" and the "Environment" are still visible as distinct data points.
Putting in resource between concept and logic:
Column
Category
Specific Tasks
Ajusted - Hidden meaning
Context
Command & control
Stake Holder mapping - power interest
System purpose -Intention with goals
Concept
Strategy vision
Conceptual model free of personal interest
System structure -Personal power (ego)
Resource
Pivot (C3/P3)
Gap analyses - scenarios - preferred options
Capability options - availability creating
Logic
Architecture
Information flows logical blueprint
Solution alignment - Ideation what could be
Physical
Engineering
Translation logical blueprint into technical specifications
selection among alternatives -Intention purpose/telos
Thoughts on Work, Power, and Becoming Unemployables
Thoughts on Midlife, Work, Power, and Becoming Unemployable (LI:Stefan Norvall 2026)
At midlife, some people become "unemployable" not because they decline, but because they cross a developmental threshold that makes participation in organisational theatre impossible.
When someone shifts from Achiever to Individualist or Strategist, they begin to notice:
contradictions in the system
incoherence in narratives
power dynamics operating beneath the surface
the gap between stated strategy and actual causality
the operating model as a political artifact, not a design
the organisation's dependency on shared illusions
This developmental shift could explain why some adults suddenly find the corporate environment intolerable around midlife, while others remain perfectly at home in it.
Most organisations are built around Power Over, they rely on a brittle, authority-driven hierarchy, precisely the kind Jaques argued against.
Jaques' view of hierarchy was fundamentally about Power With and Power To: structuring work so that accountability flows from complexity, not ego; designing roles so capability matches task complexity, not political standing.
But organisations are not well equipped for Individualists, Strategists, or anyone capable of systemic, self-authoring, complexity-aware thinking.
Those don't fit the behavioural templates.
They question the narrative.
They refuse the theatre.
They break the unspoken rules.
The hypothesis reframed:
"In classic systems optimized for first-order performance, increased second-order sense-making reduces functional employability."
Because:
The system requires unexamined assumptions to function
The individual now treats those assumptions as objects of inquiry
This introduces friction, delay, and legitimacy questions
Which the system interprets as inefficiency or non-compliance
Leading to exclusion despite unchanged or increased competence
What makes his claim threatening is that it violates a deep modern belief:
"Personal development always increases employability"
That belief is only true in systems that co-develop.
In static systems:
Development increases truth, but reduces fi. This is not failure â€" it is phase mismatch.
That is a structural proof, not a moral one.
FO: "How do we perform better within the current rules?"
SO: "Are these the right rules?" and what happens if we change them?"
butics
download "We hit a Wall at 8 Agents" (LI:J.Lowgren 2026)
When we started building multi-agent systems, we did what everyone does.
We chained them together: Agent A calls Agent B, B calls C.,C fans out to D and E, then converges on F, Clean, Logical, Easy to diagram on a whiteboard.
It worked, until it didn't.
Somewhere around 8 agents, things started to fracture. Not dramatically. Quietly. A data source change in one agent would silently break assumptions three steps downstream. Adding a new agent meant re-examining every path it could touch. Error handling became a full-time job.
The problem wasn't the agents, it was the architecture.
Procedural logic puts control in the path. Every connection is a commitment. Every fork is a contract. And every new agent multiplies the number of contracts you have to honour.
The complexity isn't linear it's combinatorial.
So we changed our approach.
Instead of telling agents how to work together, we started telling them what we needed, and defining the boundaries they had to operate within. Goals. Scope. Policy. Evidence requirements. Provenance. Risk tolerance.
Declarative intent, backed by a lightweight state machine.
The agents still collaborate. But they don't need to know about each other's internals. They don't need rigid handoff protocols. They need to understand the mission and respect the constraints.
The difference is architectural, but the impact is operational:
Adding a new agent no longer means rewiring the system.
Failures stay local instead of cascading.
The system gets more capable as it grows, not more fragile.
If you're building agentic systems and you feel the architecture fighting back as you scale, this might be the wall you're hitting.
Stop engineering the path, start engineering the boundary.
butics
"The End of Change Management as We Know It Why Organisations Fail to Absorb Change and How Futocracy Offers a New Operating System" (LI: Reg Butterfield 2026)
Evolving for an AI-driven world
Change Professionals today need to move beyond outdated, episodic change models. They're facing the challenge of reinventing their role, not just as facilitators of change, but as designers of living systems where adaptation is continuous, participatory, and embedded.
Most organisational change fails not because people resist it, but because systems are designed to recapture power the moment it begins to slip.
I call this the Power Recapture Protocol (PRP), the immune system of the command-and-control organisation. Like any immune response, it is not malicious. It is protective. It exists to preserve coherence, not the coherence of purpose or performance, but the coherence of control.
When a change initiative threatens the existing distribution of authority, even unintentionally, the system reacts. Not with rebellion, but with absorption. Not with noise, but with silence. Meetings multiply. Approvals stall. Scope drifts.
Governance tightens, and the change, once vibrant, is gently folded back into the status quo like a wave dissolving into sand.
This is not failure. It is structural self-preservation.
For decades, Organisational Development (OD) sensed this truth but over time lacked the language to name it.
Consultants spoke of "resistance," "culture," and "readiness," as if change were a psychological problem rather than an architectural one.
They mapped processes but often missed the intangible decision flows, the quiet channels through which real authority moves, hidden beneath org charts and job descriptions.
Then came Stefan Norrvall's Three Axes, and with it, a diagnostic scalpel sharp enough to cut through the fog.
Stefan showed what OD always knew in its bones: organisations operate in three dimensions, responsibility, regulatory grammar, and legitimacy, and most change interventions act in only one, assuming the others will bend.
They do not. They push back. Structurally. Predictably
Concept ➡ Process not a direct relation in viable systems
"Missing" is C-P because It must pass through R (agency/role) or T (transformation) first, meaning cannot become process without mediation.
In the framework There are different ontological domains::
semantic / normative : C = Concept / Constraint / Legitimacy / Meaning, lives in sense-making space.
temporal / operational: P = Process / Path / Coordination / Time, lives in execution-time space.
Trying to connect them directly is like trying to turn a sentence into a schedule without someone interpreting it.
That's why the system "resists" a C-P edge.
To go from Concept to Process, a system must answer:
C ➡ R ➡ P Who carries it? R injects agency and legitimacy
C ➡ T ➡ P What changes because of it? T injects change and embodiment
What happens if you force C-P, the system becomes brittle or cynical, you get classic pathologies:
policy theatre
governance without ownership
values turned into KPIs
slogans turned into Gantt charts
I added Judgment / Worth between Who and When, Who - R, When - P, Worth - CÃÆ'¢"�"R metabolism.
In VSM terms: C lives near System-4/5 (meaning, policy), P lives in System-2/3 (coordination).
VSM explicitly says: S4 does not command S2 directly, it must go through S3 and S1, which is the same thing you discovered as missing C-P.
In AI systems Agentic AI failures often come from forcing C ➡ P: value model ➡ scheduler, policy ➡ workflow.
Without: role grounding (R), state transformation (T).
So the agent "knows" but cannot legitimately or safely act.
"The apparent absence of a direct C-P relation is structural, not accidental. Concept (C) and Process (P) inhabit different domains: normative meaning and temporal coordination.
Meaning cannot become process without mediation through Role (R) or Transformation (T).
Forcing C➡P produces governance theatre and brittle execution.
Therefore, C-P exists only metabolically in the quadrants, not as a linear axis."
relation in viable systems
⟲ RN-3.5.2 Info
The era of data driven business
With M1 the daily execution of operations and M2 changing the operations ,
M3 means "which design choices ensure this becomes stable, repeatable, and scalable?"
For information processing, this means:
not "more tooling", not "technically clever"
but: conscious choices regarding structure, rules, boundaries, and measurement points
Focus on Information processing: Reliability is not just security, but auditability
Mentioned are cybersecurity and information security but in M3 reliability is broader, that is:
Reliability = predictability under variation
What happens with incomplete input or with asynchronous sequences or with erroneous assumptions?
The M3 logic is:
explicit validation rules
explicit error paths (no implicit "happy flow")
security as a design choice, not as an add-on
In terms of a dashboard, this shifts from: "is it safe?" to: "do we know what happens if something goes wrong?"
Focus on the IAM area:
Making the M3 position of IAM explicit, IAM is not an IT service, but a decision system.
The goal for IAM:
Ensuring that access is explainable, predictable, and reproducible even when changed.
IAM : who decides under what conditions for access is justified
Anti-M3 signals are: IAM = "account management" or "who is allowed to log in where" or "tooling + processes".
IAM at the M3 level is not identity administration, but the explicit design of access decisions so that security, compliance, and change are enabled together.
At M3 choice are made for Strict separation - Explicit domains::
Halfway definitions for clear human-level understanding
It's important to keep this **simple and usable**, not theoretical.
Simple definition (one sentence): A half-point is the moment when what you know still exists, but no longer helps you decide what to do next.
Slightly expanded, a **half-point** is a transition moment where:
your old way of understanding hasn't disappeared,
but it no longer fits the situation,
and you can't move forward without changing how you make sense of things.
It feels like *being stuck between "this used to work" and "something else is needed, but I don't know what yet."*
Two essential properties (easy to remember)
Knowledge breaks before it is replaced
You don't step into new understanding smoothly.
There is always a period where:
confidence drops,
ambiguity increases,
and action feels risky or unclear.
You can't skip it
Half-points cannot be optimized away, delegated, or designed around.
They must be **lived through**.
The two most common half-points
Half-point 1 - *Meaning breaks*
->> "I know how this works, but it no longer explains what's happening."
Typical signs:
confusion
frustration
asking "why doesn't this make sense anymore?"
searching for new interpretations
This is where **learning becomes real**.
---
Half-point 2 - *Responsibility appears*
> "I understand this now - and that means I can't avoid taking responsibility."
Typical signs:
decisions feel heavier
consequences affect others
legitimacy and ethics come into play
you can't "just analyze" anymore
This is where **learning ends and governance begins**.
---
## What a half-point is *not*
A half-point is **not**:
a skill gap
a lack of information
a maturity level
a personal weakness
a failure state
It is a **necessary transition**.
---
## Why half-points feel uncomfortable (and that's normal)
At a half-point:
speed slows down
certainty drops
status may feel threatened
identity feels unstable
That discomfort is not a bug - it's the signal that **real change is happening**.
---
## A simple metaphor (often helpful)
Think of crossing a river on stepping stones.
A half-point is:
when you've stepped off the old stone,
but haven't yet reached the next one,
and you can't stand still without falling.
You must **rebalance**, not rush.
---
## One-line takeaway
**Half-points are the moments where progress stops being about doing better and starts being about becoming different.**
Exploring the Practice Rationality, Strategy as Practice, and Epistemologies of the South: Towards Wider Strategic Research
reseeMike cards develop-2 (researchgate )
formal method note 6*6 reference grid usage
Common pathologies in DTF completeness
formal method note 6*6 reference grid usage
Method Note of Diagonal Tension Mapping Using a 6*6 Grid.
This method formalizes the use of a **6*6 grid as a phase space** for exploring developmental, organizational, and epistemic transitions, while explicitly **rejecting grid cells and diagonals as developmental stages or movement paths**. The grid is used to surface **tensions, half-points, and system boundary crossings** that are otherwise obscured by conventional matrix-based models (e.g., 3*3 frameworks).
Problem Statement
Many systems frameworks rely on square matrices (most commonly 3*3) to represent development, learning, or organizational maturity. These frameworks implicitly assume:
continuity of development,
commensurability across dimensions,
and reversibility of movement.
Empirical evidence from learning systems, enterprise architecture, governance, and AI development shows that the most consequential transitions are discontinuous, irreversible, and system-changing.
Conventional grid usage obscures these transitions.
Core Design Principles
The 6*6 grid is constructed according to the following principles:
The grid is not a level model
Cells do not represent stages, states, or maturity levels.
They function only as coordinate intersections between orthogonal dimensions.
Axes represent constraints, not progression
Rows and columns represent orthogonal constraints (e.g., epistemic depth, social scale, normative force, temporal irreversibility).
Movement along Rows and columns is:
reversible,
optimizable,
and designable.
Diagonals are not trajectories
Diagonals must never be interpreted as movement paths.
Instead, they function as tension lines where incompatible constraints intersect.
Meaning emerges diagonally
Transformational significance appears **only** on diagonals, where:
learning collides with identity,
understanding collides with responsibility,
capability collides with legitimacy.
Why a 6*6 Grid (Minimal Sufficiency)
A 6*6 grid is the smallest square structure that allows:
separation of epistemic, existential, and normative dimensions,
representation of individual, collective, and institutional perspectives without collapse,
visibility of system boundary crossings without reifying them as levels,
multiple valid centers (polycentric reading).
Smaller grids (3*3, 4*4, 5*5) compress late-stage normativity and force half-points into artificial cells.
Core Movement vs. Tension
Axis-aligned movement along rows or columns represents:
elaboration within a system,
refinement of competence,
scaling without system change.
This movement is legitimate, reversible, and subject to optimization.
Diagonal tension, intersections represent:
breakdown of prior coherence,
affective destabilization,
emergence of irreversibility,
potential system change.
These are diagnostic zones, not actionable steps.
Half-Points as Events, Not Locationss
Half-points are defined as moments where:
> prior knowledge remains available but no longer coordinates action.
In this method:
half-points are not located in cells,
they appear as zones along diagonals,
they cannot be designed, only encountered.
This preserves the ontological distinction between learning and governance, cognition and normativity.
Interpretive Use
The grid is used by asking diagonal questions, not by tracing paths:
Where does competence stop producing meaning?
Where does understanding become binding responsibility?
Where does local sense-making fail when scaled socially?
Where does design encounter legitimacy limits?
Answers indicate tension zones, not solutions.
What the Method Explicitly Avoids
This method intentionally avoids:
maturity models,
stage-based development,
capability ? value extrapolation,
learning ? governance continuity,
symmetry-based integration claims.
These are treated as category errors.
Applicability
The method is particularly suited for:
enterprise architecture failure analysis,
agentic AI governance and alignment,
leadership and legitimacy studies,
polycratic and multi-center organizational design,
second-order systems inquiry.
Summary Statement
The 6*6 grid is not a representation of development, but a **diagnostic phase space**.
Movement occurs orthogonally; transformation appears diagonally.
Half-points are events, not positions, and cannot be stabilized by structure.
Data & AI Cognitive (DAC) Architecture
Intro "DAC: A Federated Enterprise Data Architecture That Absorbs AI" (LI: Mustafa Qizilbash 2026)
Why do data architectures continue to fragment, even after heavy investment in platforms, governance, and AI?
In this work, I take a clear position.
Fragmentation is not a tooling problem.
It is a structural problem.
Most architectures fail because they do not enforce control at three critical boundaries:
How data enters the enterprise (ingestion)
How it moves across domains (integration)
How it is consumed (serving layer)
When these boundaries are not structurally enforced, organizations inevitably end up with:
Duplicate pipelines
Inconsistent datasets
Parallel AI environments
Fragmented governance
In this figure:
- Landing
- staging
* purpose flow
- Semantic
- delivery
What I see is a mind shift: there is internal processing for external processes.
The core idea behind DAC is simple but strict:
AI should not exist as a separate ecosystem.
It must operate within the same governed enterprise data architecture.
This means:
No independent ingestion pipelines
No isolated feature stores
No parallel data platforms
Instead: A federated model with enforced control, where domains retain autonomy, but within architectural boundaries.
The reference promoted on
"DAC: A Federated Enterprise Data Architecture That Absorbs AI" (Bill Inmons Substack 2026) Is your current architecture making new use cases easier - or harder? (LI: Ronald Baan 2026)
We keep building more. More data lakes. More warehouses. More pipelines. More copies of the same data in slightly different shapes for slightly different purposes.
Data products are not THE answer. We are now talking about data products build on other data products and then ownership and lineage and the complexity is becoming daunting.
And the fundamental problems remain unsolved.
Data volumes grow faster than our ability to govern them.
Every new use case requires a new data product built on top of another data product built on something nobody fully understands anymore.
AI needs data that is reliable, attributed and current - most organisations cannot provide that.
When we share data across organisational boundaries, we share the same underlying fragility. The mess travels with the data.
The question nobody is asking loudly enough is not how do we manage more data. It is why does every new use case make the problem harder?
I think the answer is architectural.
Current architectures were designed for a world where data had one purpose, one owner, one consumer.
That world no longer exists.
Today a single entity is observed by dozens of systems, each with a different perspective and different authority.
None of them wrong, all of them partial.
What if the architecture started one layer deeper?
At the irreducible unit of meaning.
A statement about an entity, by a specific source, at a specific moment, carrying its authority and its context.
Multiple truths coexisting - not as a problem to resolve, but as a governed reality to navigate, a feature!
The animation shows the concept. More on this soon. The paper is almost ready.
What I see is there are levels for:
Signals
Observations - Data
Assertions - Information
Data Products - Knowledge
To add:
Decisions - Wisdom
Vision
It is the revival of DIKW in the intended origin for flow and meaning.
A dark-room metaphor for what is seen an not seen
Six universial principles different systems (LI: Ajit Jaokar 2026)
Across all five domains, the same six-layer structure holds. Here's the abstract framework:
Workflow surface. Every enterprise has surfaces where multiplayer decisions happen.
Agent checkpoint. The agent's proposal is the structured prior - what the system thinks should happen based on policy and data.
Decision trace emission. The trace captures not just the outcome but the reasoning: which policy was evaluated, what precedent was invoked, who approved, what exception was granted, what the business justification was, and what alternative was rejected.
Context graph accumulation. Individual traces are useful. Connected traces across entities and time are transformative.
Compounding outputs. The graph produces three escalating capabilities. First, better decisions - agents propose with precedent already incorporated. Second, more autonomy - repeated patterns that always resolve the same way get automated. Third, prediction - dense enough graphs enable forward-looking questions
The flywheel. Better decisions and more autonomy route more decisions through the system, which generates more traces, which enriches the graph, which improves the next decision.
⟲ RN-3.5.3 Info
The era of data driven business
It's not about control, it's about acceleration. (Raj Grover 2026)
The era of Data Governance as a passive, policy-enforcing committee is over.
If your council isn't actively fueling the business strategy, it's just overhead.
Many councils are stuck reviewing data catalogues and debating definitions.
Meanwhile, the business is screaming for data-driven innovation.
This gap is what makes them obsolete.
The shift starts by asking fundamentally different questions.
We've moved beyond basic governance.
The modern council needs an Innovation Agenda.
It's built on 5 pillars, driven by questions that challenge the status quo.
Category 1: Strategy and Ideation
Focuses on where to innovate and how to generate ideas
What methods are we using to identify new business opportunities where data can be a key driver?
How can we break down data silos to encourage cross-departmental collaboration and spark new ideas?
What competitive intelligence and market data are we analyzing to identify opportunities for differentiation?
How are we leveraging customer data and feedback to understand unmet needs and drive personalized solutions?
What criteria do we use to prioritize and allocate resources to the most promising data-driven innovation initiatives?
How can we monetize data (directly or indirectly) to create new revenue streams or business models?
Category 2: Technology, Data and Analytics Capabilities.
Focuses on the tools and data infrastructure needed
What investments in technology (e.g., cloud platforms, data lakes) and data integration strategies are necessary to provide a comprehensive view for innovation?
How are we leveraging advanced analytics, AI, and ML to uncover non-obvious insights that drive innovation?
What infrastructure and processes do we have to support the rapid analysis and application of real-time data?
What tools and processes ensure decision-makers have access to high-quality, trusted data?
What interoperability and industry-standard practices ensure our data-driven innovations scale across ecosystems and value chains?
Category 3: Governance for Agile Innovation
Focuses on the policies and frameworks that enable rather than hinder
What specific data governance policies (e.g., for data sharing, access, quality) need to be agile to support rapid experimentation and prototyping?
How do we protect customer privacy and ensure ethical data use while still enabling innovation?
What governance mechanisms are in place to facilitate secure and compliant data collaboration with external partners (startups, academia)?
What processes do we have to quickly test, validate, and learn from new concepts using data?
What ethical and responsible AI practices must be embedded into our innovation lifecycle to avoid bias, misuse, or reputational risk?
Category 4: Culture, Skills and Decision-Making
Category 5: Measurement, Learning and Scaling
Focuses on the human element, Focuses on proving value and scaling success)
How can we foster a culture that encourages creative data use and intelligent risk-taking?
What training and resources are needed to uplift data literacy and empower employees to leverage data creatively?
How can we ensure data-driven insights are consistently integrated into strategic and operational decision-making?
How do we measure the impact and ROI of data-driven innovation projects? What KPIs do we track?
What can we learn from our most successful (and unsuccessful) innovation projects to improve our approach?
What processes do we have to scale successful prototypes into full-fledged products or services?
Mike cards develop-2
Mike cards develop-2r
Common struggles achieving DTF completeness
The T-forms challenge activating change
How the seven governance-tension classes sit inside the double diamond
The double diamond has four canonical phases:
Discover (divergent sensemaking)
Define (convergent framing)
Develop (divergent solutioning)
Deliver (convergent execution)
Each phase is governed by different principles and therefore different trolley-like conflicts. ❶
Discover ➡ Cognitive + Normative tensions dominate
This phase is about sensemaking under uncertainty, which is exactly where your page focuses.
Dominant tensions:rn-3.1.4
Cognitive, deterministic vs probabilistic, context-first vs action-first, linear vs dialectical.
Normative, safety vs autonomy, fairness vs utility, predictability vs adaptability.
Discovery is where and when the system asks: "What is happening, and what matters?".
This is where trolley-like dilemmas first appear: conflicting values, ambiguous signals, competing interpretations.
Diagnostic questions
Are we interpreting the same signals differently?
Are we privileging safety or autonomy in early framing?
Are we prematurely collapsing uncertainty?
❷
Define ➡ Boundary + Structural tensions dominate
This phase is about choosing the frame, which is inherently a boundary-setting act.
Dominant tensions
Boundary, hard vs soft boundaries, inside vs outside logic, role vs capability boundaries.
Structural, centralized vs distributed authority, top-down vs bottom-up initiation.
Defining the problem is the moment of choosing what is in and what is out.
This is where governance becomes explicit: "Who decides what the problem is?"
Diagnostic questions
Which boundaries are we enforcing or dissolving?
Who has the mandate to define the frame?
Are we privileging hierarchy or population-proactive logic? ❸
Develop ➡ Capability + Relational tensions dominate
This phase is about exploring solutions, which depends on competence, trust, and interaction patterns.
Dominant tensions
Capability, minimum competence vs maximum autonomy, expert-driven vs population-driven.
Relational, trust vs control, collaboration vs adversarial dynamics, semantic drift.
Solution exploration is the moment where teams collide in practice: "Who is allowed to try what?" and "Do we trust each other enough to experiment?"
Diagnostic questions
Are we blocking exploration due to competence gaps?
Are relational dynamics enabling or constraining creativity?
Is semantic drift undermining shared understanding? ❸
Deliver ➡ Temporal + Structural tensions dominate
This phase is about execution under constraints, where time and authority collide.
Dominant tensions
Temporal, short-term vs long-term, immediate vs latent risk, past vs future anchoring.
Structural, process-driven vs event-driven, centralized vs distributed execution.
Delivery is the moment where governance becomes kinetic: "Do we optimize for now or for later?" and "Who has the authority to act under pressure?"
Diagnostic questions
Are we sacrificing resilience for throughput?
Are we acting on the right time horizon?
Are escalation paths aligned with actual risk?
The four double-diamond phases each have two dominant tensions. .
It reveals a vertical axis (long-term, slow-changing governance principles) and a horizontal axis (flow-of-work, moment-to-moment tensions).
The ethical dilemma of judgement before the act or after the fact
Capabilities-Based Planning (LI:G.Alleman 2026)
dentify a needed capability in operational terms, assess its effectiveness within an operational paradigm, and make choices about requirements and how to achieve the capability using an integrated portfolio framework to produce an output set of options based on these operational paradigms.
The ethical dilemma of judgement before the act or after the fact
Nobody hears each other, because strategy is not one level (LI:Natan Mohart 2026)
Most strategy debates are just people talking about different things.
One means the company mission.
Another means the quarterly plan.
Third means how to beat the competitor.
Everyone is right.
Nobody hears each other, because strategy is not one level.
The problem is not that people can't build strategy.
The problem is that they solve questions of one level with tools of another.
Each level requires its own horizon, its own people and its own metrics.
CEO gets into sprints -> Team is paralysed.
Team lead decides which market to enter -> Board is in shock.
Each level requires its own horizon, its own people and its own metrics.
CORPORATE (5-10 years) Where does the company compete?
Which markets. Which geographies. What to buy, what to sell.
A question for the CEO and the board.
KPI: market cap, ROIC, revenue growth.
:
BUSINESS (2-5 years) How do you win in your market?
Who is the ideal customer. How you differentiate. Why they choose you over the competitor.
A question for business unit leaders. KPI: market share, NPS, revenue per customer.
:
FUNCTIONAL (1-2 years) What do you build internally?
Which capabilities to hire. How to allocate budget. Which processes to automate.
A question for the CMO, CTO, CFO. KPI: CAC/LTV, gross margin, time-to-hire.
:
OPERATIONAL (day to quarter) How do you execute right now?
Sprints. Tasks. Quality. Are we hitting the targets.
A question for team leads and project managers. KPI: delivery velocity, defect rate, team utilisation.
:
The ethical dilemma of judgement before the act or after the fact
Habermas: Normativity through rational discourse (before the act)
Habermas believes in discourse ethics: norms are valid if they arise from rational, inclusive dialogue.
His model is procedural: legitimacy comes from communicative rationality, not outcomes.
Normative reasoning is prior to action, it's about forming a rational will through deliberation.
The trolley problem, in this view, is a failure of pre-action discourse: the dilemma exists because the system didn't build a normatively valid framework beforehand.
This aligns with the "Normative at the top" framing, governance should be designed to avoid trolley dilemmas by embedding values before the fact.
Arendt: Ethics as judgment (after the act)
Arendt rejects the philosophy of the will, she doesn't believe political legitimacy comes from rational consensus.
Instead, she emphasizes judgment, the ability to reflect on actions in their context.
Normativity is post-hoc and narrative: we judge actions by how they appear in the world, not by abstract principles.
The trolley problem, in her view, is a real political moment, not a failure of design, but a moment of human judgment under pressure.
This aligns with your "unsolvable after-the-fact" framing, governance dilemmas are not always preventable; they must be judged in context.
Your governance model sits between them
You place Normative reasoning at the top, like Habermas, you want governance to be designed with values embedded.
But you also recognize boundary tensions, relational dynamics, and capability gaps, like Arendt, you accept that dilemmas will arise and must be judged in context.
So your model is pre-normative but post-dialectical:
It uses semantic governance to reduce trolley dilemmas, but accepts that some will remain, and must be navigated through judgment, capability, and relational trust.
Your avoidance of "normative good/bad ethics" is deeply aligned with Arendt's critique of abstract moral reasoning, and it marks a key divergence from Habermas.
Pre-normative design with post-dialectical realism.
You place Normative at the top of the vertical governance spine, but not as "good vs bad."
You treat it as a semantic anchor: what matters, what is valued, what is protected.
This avoids:
Vagueness, by embedding values into governance architecture
Volatility, by treating norms as design constraints, not moral absolutes
Ambiguity, by externalizing tensions (e.g. safety vs autonomy) rather than collapsing them into "right vs wrong"
You're not solving ethics, you're mapping governance tensions so that trolley-like dilemmas become diagnosable, visualizable, and navigable.
Dimension
Habermas
Arendt
Normativity
Procedural and universal Contextual and narrative
Ethics
Grounded in rational discourse Grounded in judgment and appearance
Action
Justified by communicative consensus Judged by how it appears in the world
Governance implication
Build systems that prevent dilemmas Accept dilemmas and cultivate judgment
Trolley problem framing
A failure of pre-normative design A moment of political judgment
Habermas wants to solve the trolley problem before it arises through rational procedures.
Arendt wants to face the trolley problem as it arises, through human judgment and storytelling.
⟲ RN-3.5.4 Info
The operating Model a Flashlight or a Blindfold?
A dark-room metaphor for what is seen an not see.
Your Operating Model isn't just a process map or a SolutionArchitecture (LI: Abdul A 2026), it is the Internal Logic that determines what your organisation is even capable of seeing.
Every manager eventually asks: "How big is my dark room of uncertainty and which piece of data will shrink it the fastest?"
The "Dark Room" isn't a place where you're simply missing facts.
According to Structural Coupling (Maturana & Varela, Luhmann, Hoverstadt), your organisation is an "operationally closed" system.
The Room (Your Operating Model): This is your internal "frequency." As Paul Pangaro notes, language is constantly expanding or contracting.
If your model contracts to only speak "Cost Reduction," you become functionally blind to "User Experience." You cannot act on what you cannot name.
Operating Models and EnterpriseArchitecture are about creating environments for people to talk to each other, rather than just connecting IT systems.
Structural Coupling (The Doors): These aren't just entrances for data; they are sensors.
They don't let the outside "in", they vibrate when the environment hits their specific frequency.
Information as an "Event": Information isn't a commodity you store in a database.
It is a "difference that makes a difference" (Bateson).
It's the moment your Operating Model feels a vibration at the door and is forced to change its internal state.
Uncertainty comes in two distinct flavors (George Klir):
Solving Ambiguity (The Choice Problem): You have 10 doors vibrating, but your system can't prioritize them.
The Fix: Refine your "Selection Logic." If your internal communication can't distinguish a "fad" from a "trend," your coupling is too loose.
Solving Fuzziness (The Boundary Problem): The environment is vibrating, but your Operating Model doesn't have a "word" for it.
The Fix: Update your "Internal Code" and expand your language. If your model doesn't have a category for "Trust," you will be blind to it until the room gets dangerously dark.
The "fastest piece of data" to shrink your room isn't usually a new data source.
It's the signal that perturbs or irritates your Operating Model into a new way of functioning.
Stop trying to "collect" the world. Instead, focus on Structural Coupling: making sure your Operating Model is tuned to the right triggers so it can turn a tiny external vibration into a massive internal light.
The question isn't "What is out there?" but "Is my Operating Model designed to notice it?"
"Operationally Closed" does not mean "isolated."
In systems theory, operational closure means an organisation only functions through its own internal "logic" and communication loops. It doesn't "ingest" the market; it is perturbed by it.
Think of your Operating Model as a sophisticated receiver.
If your internal "code" is only tuned to the frequency of Efficiency, your organisation is functionally blind to the frequency of Market Trust even if that signal is hitting your system at full volume.
The "Dark Room" remains dark not because data is missing, but because the system lacks the internal variety (the language) to translate that external vibration into an internal insight.
A dark-room metaphor for what is seen an not seen
closing-business-it-gap-model (2026 Christian Kaul and Lars Ronnback )
You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete. (R. Buckminster Fuller, 1982)
The problem:
Organizations usually have some understanding of the concepts that drive their business.
But the entities used in their IT systems often don't align with these concepts.
Furthermore, their employees are divided into departments and teams in a way that doesn't match the concepts either.
Leaders of different business units don't talk to each other.
This disconnect leads to:
a vicious cycle of people silos creating data silos creating more people silos.
leaders create data fiefdoms out of organizational fiefdoms.
They fail to recognize that most of the projects they see as IT projects actually are business transformation programs.
First, we have to realize that data models only become really useful when they also work as communication tools, documenting with sufficient detail how an organization works now and how it will work in the future.
When a model captures both the current reality and the desired reality, it can serve as the core of a model-driven architecture, with all kinds of technical and nontechnical artifacts generated from it. Ethics in Change Management (LI: G.Kruidenier 2026)
Uhm, what?!! Is ethics in change management genuinely unexplored territory or is it territory the profession has inadvertently rushed past while following the latest trend?
One of the more pointed critiques in the literature comes from Huehn, who argues that business education has been systematically de-philosophised over the last two centuries.
Management schools train people to use tools, not to think through problems.
The MBA, he suggests, has replaced wisdom with cleverness. I've spoken to quite a few academics and MBA directors who would agree and some even extend that to business schools.
Bashir and Afzal (2008) make exactly this point, that the most widely used change frameworks don't address questions like who should be consulted, what obligations leaders have to those affected, or how to handle conflict between organisational and individual interests.
The failure rate of change initiatives, somewhere between 30% and 70% depending on who you ask and how they're counting, is not simply a technical or strategic problem.
Burnes and By argue that ethical leadership is one of the clearest differentiators between change that lands and change that doesn't.
Trust is the mechanism. And trust is built or destroyed by whether people believe the change is being managed in good faith.
https://www.navex.com/en-us/blog/article/ecis-2023-global-business-ethics-survey-reveals-harsh-realities-about-ec-programs/ The ECI Global Business Ethics Survey (2023), covering 75,000+ employees across 42 countries, found that 87% of employees globally do not believe they work in a strong ethical culture.
Of those who observed misconduct and reported it, 46% experienced retaliation.
Observed misconduct is at an all-time high. These are not abstract numbers. They describe the organisations most of us are working in right now.
The literature is also consistent on something we all kind of know but might not want to admit; codes of conduct don't work for the people who need them most, as they seem to feel these don't apply to them. Burnes made the point that if laws and ethical codes were sufficient to change behaviour, the Enron, McKinsey, PwC, Arthur Andersen and many other scandals wouldn't have existed.
Rules only define an absolute minimum. They don't build the cultural and character foundations that produce genuinely ethical conduct. Mani leadersop-2r (LI: R.Butterfield 2026)
n my new book, Beyond the Org Chart, I bring in ethics as one of the core issues to consider.
The image below is but one example of this relationship. I use the term 'Stewardship' and 'Convening' in place of leadership and leading as the latter words have too many in-built prejudices and assumptions, which make it a challenge for people to understand things differently in this area.
Mani leadersop-2r (LI: S.Mani 2026)
Mani leaders develop-2r (LI: S.Mani 2026)
From Dead Knowledge to Living Learning in Organizations (LI: S.Mani 2026)
The hidden 7-item semantic structure in Mani's new article when reading the article carefully, Mani is not just distinguishing:
>
Ability (parts)
Capability (one system)
Capacity (systems-of-systems)
He is actually describing seven distinct semantic transformations that turn dead knowledge into living learning.
Why Data Architecture Needs Unit Economics in the Agentic Era (By Karl Ivo Sokolov and Mario Meir-Huber 2026)
The "clean data for AI" framing solves yesterday's problem by preparing data for human analysts who can interpret ambiguity, navigate incomplete metadata, and mentally translate between systems.
Agents do this poorly and expensively, burning tokens on context reconstruction that a properly architected semantic layer would have made unnecessary.
The Strategy Trap: Why Your "Fixed Plan" is Already Obsolete (LI: A.Aziz 2026)
Strategy is treated like a Calculus of Prediction. You analyse the "Five Forces," pick a spot on a static map and optimise for equilibrium
The reality? This assumes the your business and the market are machines. In a world of Perpetual Novelty, the moment you "optimise" for today, you've anchored yourself to a past that is already disappearing.
The Prediction Paradox
We are often told that prediction is impossible in complexity.
That's a myth. Systems thinking and complexity science show us that all complex adaptive systems, from bacteria to businesses, must build models to anticipate.
Without prediction, there is only reaction, and reaction alone is not enough for survival, never mind thriving.
The trap isn't prediction itself; it's the Static Model and the lack of feedback.
We try to solve the market like a puzzle, when we should be navigating it like an ecosystem.
From Planning to "Structural Coupling"
Strategy is the recursive management of Power, Fit, and Timing, it's about creating Structural Coupling:
Power: Your business capabilities and the "Interlocking SOPs" inscribed in your organidation.
Fit: How seamlessly your internal model matches the environment's requirements.
Timing: Recognising the Phase Transition, knowing when a niche is opening and when it is locking in.
Redefining the Goal: The "Adjacent Possible"
In a Complex Adaptive System, your goal isn't to "win" a static game. It's to evolve.
"The point of strategy is not to predict per say, but to evolve into the adjacent niches that your own presence creates."
Every solution you provide is merely a precursor to a new set of problems. A curse and a blessing.
The "Grandmaster" recognises that their very presence moves the mountains. They turn Epistemological Uncertainty (the mess of the market) into Ontological Growth (the evolution of the firm)
Side note: if winning means no one wants to play with you you've lost, in both businesses and life.
The First Step: Forging the Operating Model
How do you start? You build a Shared Understanding through Action.
By starting with the Operating Model, you can nudge "left" to strategy rather than just "right" to delivery, traversing with ease.
Co-creating a Viable Operating Model (VOM) is the act of "programming" the organizational agent.
By forging the model through action, the "Internal Model" becomes reality, a set of shared rules that allow the team to move as one, while knowing those rules will inevitably change.
This model directly shapes your Platforms and Products, but its true power is communicative.
It gets your people talking, amongst themselves, with the customer, suppliers etc.
Food for Thought:
Stop trying to "solve" the future. Start building the internal models that allow you to couple with it. Practice, practice, practice.
Attention Is All You Have
In the agentic era, leadership means designing what your machines notice, optimize, and repeat.
Now that the machines do the doing, what' s left? (LI: C.Korzykov 2026)
We spent over a century trying to eliminate complexity in organizations.
The whole premise of Taylorism (also called scientific management) was to break work into parts, optimize each piece, and squeeze out as much of the variance as possible.
That worked for the low-hanging fruit, the monolithic processes where one size really does fit most.
Ashby' s Law of Requisite Variety, an enduring classic from 1956 (the same year that gave us the term Artificial Intelligence), says that a control system must be at least as complex and as capable as the system it governs.
Scale up what a system can do and you must scale up what steers it, or the steering stops being steering and becomes weather.
You inherited a controller built for a smaller century; playing at tomorrow' s level requires self-amplification.
To manage agentic systems is to design attention scaffolding; the systems you don' t choose will be chosen for you by people whose incentives are not yours.
Misapply your attention and you' ll end up busier than before. Build feedback loops and you' ll sharpen your judgment instead of dulling it.
Not everyone will recognize the agentic era as an opportunity for compounding attention. Many will let theirs wander to whatever is loudest.
That creates an opening for those who choose differently.
RN-3.6 Execution & ideology integrated governance
Evaluating time and direction for worth: orientation, Judgement, value, affect, commitment is the advanced next phase for understanding in the now.
The boundary is the common organisation approach set by Context-bound vs context-changing futures:
operations now,
change near future,
vision far future within concept bounds,
vision far future changing context
The awareness impact by choices is completed for the whole in direction location and a time horizon and uncertainties to reflect.
⟲ RN-3.6.1 Dialectical, teleological approach for leading in tasks roles
The quest in redefining leadership by categories
What would be good
examples of Visionary Leaders in Business ?
This gives a list without clear attributes.
For attributes and properties categories in leadership the proposal for categories is used.
That proposal is based by including the 4 types seen in the 6*6 layer build out of Context Relation Process and Transformation. (RN-3.4) 🎭
The search is for the role in C3, M3 leadership.
The word in catgeorisation goal: we can give a title of CPO "Chief product officer".
The unknown ones are hidden by shadows but the ones that get known by organisational hierarchy are those well known.
Keeping in mind that "one person with exceptional leadership qualities may differ from another," some of the top qualities of a great leader include elements for a growth mindset of:
Integrity, Self-awareness, Empathy,
Communication, Active listening, Patience
Optimism, Transparency, Decision-making skills
True visionaries should be more than just good at their jobs; they must be able to conceptualize an entirely new and substantially better path forward for a particular company, industry, or market. 📚
There is no school, no certification, no guild, for this, we have only some examples.
The survivor bias gives the titles of CEO's associated with personal glamour and wealth, but the quest is for those mentioned attributes that make it something different from that glamour.
Steve Jobs visionary goal of placing a personal computer in every home must have seemed ambitious at the time.
Henry Ford was an innovative business leader in numerous respects, he is best remembered for revolutionizing factory manufacturing.
Jeff Bezos and his wife established a one-stop shop for a broad spectrum of products on a user-friendly platform that includes a variety of third-party sellers.
Carnegie is perhaps best remembered for his pioneering philanthropic efforts.
Warren Buffett stresses the supreme importance of treating employees fairly and honestly, while remaining faithful to the underlying objectives of all corporate stakeholders.
Mary Barra breaking through the barriers of a male-dominated industry.
Richard Branson transformed the record industry as the head of Virgin Records and the airline industry as the head of Virgin Atlantic Airways.
Elon Musk Anchors product meaning around planetary scale missions (EV transition, spacefaring), ecursive alignment across engineering, design, and culture.
There is long list to learn from.
Missing is a teleological classification for categorized leadership approaches and started her is with some of those.
For a categoristion it is required to disconnect that from characters, personality but see it as tasks by roles. 🎭But how to see the M4 Leadership?
That one is operating at the civilizational interface, not just the organizational one.
It falls outside the classic hierarchical ideas.
M4 examples could be someone like:
Zhang Ruimin, (Haier - turning a company into a self-organizing ecosystem
Haier's RenDanHeYi model is explicitly built around user-centric value creation, where microenterprises operate with autonomy but align around a shared purpose
Paul Polman, Unilever - sustainability as corporate identity
That is not very helpfull, a switch to a more generic is an opening.
A better example the proto-M4 is Benjamin Franklin operating at the level of humanity, not just nation or organization.
shaped ethical systems, designed civic institutions
integrated science, ethics, and governance
promoted human flourishing, thought in terms of societal continuity
Naming Benjamin Franklin a "Chief Civic Architect" is just a honorary title that is beyond organizational governance. 🎭M5-M7 are contextual layers that humans can align with, but not "hold office" within.
What would others be in that? Proposed names are: John Adams, Thomas Jefferson, Montesquieu, John Stuart Mill, Mary Wollstonecraft, Mahatma Gandhi, Nelson Mandela, Eleanor Roosevelt, Confucius, Socrates.
A result in redefining leadership in 7 categories
Using the same mindset for a "dialectical closed" open system and combining what was already stated categories emerged.
The graded architecture of who is structurally permitted to hold increasingly larger contradictions.
M unfolds developmentally is very Piagetian in the deep sense: capacity determines permissible action. 📚
The shift from "roles people play" to "functions a system expresses," the full 7-series becomes obvious and perfectly aligned.
Teleology of Systems: Vision, invention, meaning, destination.
M4
Intent-Based
CHRO, Ethics, Culture, People
Human Legitimacy / Ethical Intent: the K5 moral hinge.
M5
Orchestration
CEO (mature), Transformation, Integration
Integrating multiple value systems: coordinate the system of systems
M6
Facilitation
CSO (Sustainability), CRO, ESG
Life-level stewardship: protect the system's long-term life conditions
M7
Continuity
Board, Purpose, Philosophy, AI Ethics
Existential / Continuity of Intelligence: continuity of the whole system across generations
⚖️ Breaking the classical "same level" C-roles
The "same level" is also problematic in introducing a tribe culture of leaders against others, the aristocratic culture.
In mainstream management: CEO, COO, CTO, CPO, CHRO, CFO, CMO are treated as peer roles, all "on the same level.
There is no developmental altitude, no teleology, no moral recursion, no systemic tension mapping, It's just a list.
This mapping M1-M7 works because each C-role corresponds to:
a developmental altitude
a teleological function
a tension vector
a governance responsibility
The M- model breaks the flatness.
Created is a developmental cosmology of leadership.
This is not done in: management science, systems theory, cybernetics, organizational psychology, leadership theory, governance models.
👉🏾 The hinch is M4 that is connected to K5.
Most, including most executives, never reach this altitude, remaining in:
M3 is already rare, M4 is exponentially rarer.
An clear example of M4 is David Marquet, the Gilligan/Kohlberg hinge in action:
transformed the people, not the system.
builds moral capability, not technical capability.
decentralized authority ethically, not tactically.
🎭M3 as inventor-based is Not the romantic inventor
The most important nuance: M3 - inventor-based, but not a "breakthrough".
M3 is *not* a level of fundamental breakthroughs, M3 is making ideas applicable, it is about:
the engineer, the designer, the improvement architect
Characteristics for the processing and the product/service:
These are topics covered by lean although lean is not that mature itself for an easy mapping.
In terms of dashboards, this means:
richer quality indicators, reliability, consistency, refinement of measurements
⚖️ M3 makes M2 and M1 workable, without M3 those remains a paper-based system.
Understanding the issue why M4 leaders are rare
The role of the M4 category leader is the hinge for a responsible system but there is no way to generate copies of them.
That role is needing all relevant information that is only possible to get create after a functioning network for sharing is active.
The relevant information must be stored and accessible for all being impacted, that requires a knowledge system that is not yet existing. ⚖️ The painful truth: organizations select against M4 leaders.
Sense
Act
Justify
Context
ethical dissent
🕳
moral autonomy
Process
🕳
challenging system's_values
🕳
Outcome
long-term legitimacy
🕳
care-based decisions
Imagine
Commit
Reflect
The organisational culture is reward for:
speed (M1), control (M2), vision (M3)
But they punish M4 (see table)
To reach M4, a leader must:
transcend ego
transcend tribal identity
transcend short-term incentives
integrate multiple worldviews
hold paradox without collapsing
act from universalizable principles
care for people they will never meet
This is psychologically and morally difficult.
⚖️ How to recognize M4 leaders?
They refuse to trade ethics for speed, power, or convenience by their identity.
They speak in universalizable principles, not preferences, that is moral autonomy, not strategy.
They think in terms of responsibility, not control.
They are often misunderstood or undervalued, because M1-M3 leaders cannot see M4 reasoning.
Sense
Act
Justify
Context
Problem
🕳
Values
Process
🕳
Execute
🕳
Outcome
Intent
🕳
Purpose
Imagine
Commit
Reflect
➡An M4 leader will sacrifice personal advantage to protect human dignity.
No other level does this consistently.
➡ What is left the reward for:
speed (M1), control (M2), vision (M3)
M4 leaders are dangerous to M1-M3 power structures.
The M1-M3 leaders are hierarchical strcutures where personal interest is easily becoming an association.
The M4 leader is breaking those personal interests.
⚖️ Organizations often push M4 leaders out.
Sense
Act
Justify
Context
too principled
🕳
too idealistic
Process
🕳
too slow
🕳
Outcome
too philosophical
🕳
too human-centric
Imagine
Commit
Reflect
M4 leaders are often seen as (see table)
So they get filtered out before they reach power.
M4 leaders:
question the legitimacy of decisions
expose ethical blind spots
challenge harmful incentives
refuse to compromise on human dignity
disrupt power hierarchies
This makes them:
politically inconvenient, hard to control
unpredictable, threatening to status-quo leaders
The advantage of clear defined categories.
Aside the happy flow when all goes well a clean, structural map of failure modes is easily seen.
When any of the seven layers (M1-M7) is missing in an organization there will be a failure.
This is one of the most powerful diagnostic tools for a governance architecture because it shows exactly why organizations collapse, stagnate, or become pathological.
Failure mode: Paralysis. ⚠➡ Missing Execution Leadership Absent M1
"We talk a lot but nothing happens", symptoms:
Nothing gets delivered, Endless planning, no action, Strategy without traction
The organization becomes a think-tank instead of a functioning system.
Long term outcome: Collapse through inertia.
Under tension signals:
Failure mode: Aimlessness. ⚠➡ Missing Inventor / Teleology Leadership Absent M3
"We have no vision, there is no innovation", "We don't know what we're building", symptoms:
No destination, No meaning, No product coherence
The organization optimizes the past instead of creating the future.
Long term outcome: Collapse through irrelevance.
Under tension signals:
Failure mode: Moral decay ⚠➡ Missing Intent / Moral Legitimacy Absent M4.
This is the most dangerous gap.
"People treated as resources", "Safety and cybersecurity failures", symptoms:
The organization becomes efficient at doing the wrong things.
Long term outcome: Collapse through loss of legitimacy.
Under tension signals:
Cover-ups, Manipulation, Exploitation, Loss of trust, Whistleblowers ignored
This is the gap identified for cybersecurity: without M4, safety never becomes a habit.
Failure mode: Disintegration. ⚠➡ Missing Orchestration / Integration Absent M5
"We optimize local everywhere", "Pull in different directions", symptoms:
Fragmentation, Competing agendas, No cross-functional alignment
The organization cannot hold multiple value systems together.
Long term outcome: Collapse through internal conflict.
Under tension signals:
Turf wars, Portfolio chaos, Strategic incoherence
Failure mode: Exhaustion. ⚠➡ Missing Facilitation / Life-Support Stewardship Absent M6
"Sustainability ignorance, there is nolong-term thinking", symptoms:
Burnout, Resource depletion, No resilience
"We can't keep doing this" The organization consumes itself.
Long term outcome: Collapse through resource exhaustion.
Under tension signals:
Overwork, Crisis cycles, Environmental and social harm
Failure mode: Drift. ⚠➡ Missing Continuity / Existential Stewardship Absent M7
"We have no philosophical anchor", "Why are we even here?" symptoms:
No long-horizon purpose, No existential risk awareness, No continuity planning
The organization has no reason to exist beyond profit or survival.
Long term outcome: Collapse through loss of existential purpose.
Under tension signals:
Panic pivots, Identity crises, Loss of meaning
Leadership
Failure Mode
Collapse Type
M1
Execution
Paralysis
Inertia
M2
Coherence
Entropy
Complexity overload
M3
Inventor-Based
Aimlessness
Irrelevance
M4
Intent-Based
Moral decay
Loss of legitimacy
M5
Orchestration
Disintegration
Internal conflict
M6
Facilitation
Exhaustion
Resource depletion
M7
Continuity
Drift
Loss of existential purpose
The Complete Failure Map (Summary)
⟲ RN-3.6.2 Integrated teleological for leading by system functions model
Agentic Axioms in line with the adjusted 7 Kohlberg/Gillan Categories
two governance concerns the AI control plane taxonomy is not yet naming (LI: A.Walls 2026) (LI: A.Walls 2026)
Issue #2 of The Commit Boundary (LI: John.M.Willis 2026)
Can a system be designed so correctly upstream… that a commit boundary is no longer required?
Open systems accept: invalid paths will form, but must not bind.
AI governance is starting to fragment into camps. (LI: John.M.Willis 2026)
The disagreement isn't about principles, it's about architecture.
What's becoming clear: People are not working on the same layer.
And without that distinction, the conversation collapses into noise.
A cleaner way to see the field, AI governance spans five layers:
Type
Tasks activities
Axiom
State / Substrate
AX1
What does the system actually see?
No governance system may place an actor in an impossible dilemma.
Cognitive / Ontological
AX2
What does that state mean?
When a governance failure forces an actor into an impossible dilemma, the system must immediately shift into corrective recovery mode.
Policy / Intent
AX3
What should be allowed?
A governance system must continuously surface, map, and resolve emerging tensions at every recursive level, before they escalate into impossible dilemmas.
Execution Control
AX4
Can this transition actually happen?
resolves admissibility at the commit boundary.
A governance system must be able to govern itself.
-Hinge- Audit / Proof
AX5
Can this be verified after the fact?
A governance system must be able to verify that the information it acts on is independent of the processes it is governing.
AX6
Can it recover its own boundary?
A governance system must be able to identify, maintain, and recover its own boundary.
AX7
Policy gate before execution
Every agentic system must have a policy gate between instruction receipt and execution.
The assumptiom in the starting post is that the hinge is at AX4.
Having done Kohlberg and Zachman in this for worth morality it is Ax5 that is the hinge and Ax4 the one that is the doing what is standard automatic.
The extending to 7 Axioms is done in the other post. USing LLM ith gave the THe
This is what fractal governance should look like, because if the whole architecture is recursive, every major hinge should be able to unfold internally.
The first obvious candidate is K because legitimacy is never one scalar judgment, it is layered sevenfold behaving fractally.
When the outer manifold arrives at K it does not simply ask "is this ethical?"
It enters a recursive admissibility verification sequence from AX1 through AX7, K5 = entrance to AX1-AX7 legitimacy recursion.
The outer model = transformational topology, the inner K fractal = normative compiler.
truth of perception,
truth of meaning,
permissibility,
executable admissibility, can this transition actually happen?
auditability, can this be verified after the fact?
self-governance,
policy gating.
The advantage of clear defined categories.
Aside the happy flow when all goes well a clean, structural map of failure modes is easily seen.
To move from the "disease" (Pathology) to the "clinical presentation" (Symptoms) and the eventual "Cause of Death" (Collapse Type), we must look at how the transformation architecture breaks down when the AX-M-K Interlock fails.
The diagnostic mapping for the system's failure modes:
Moral Paralysis. ⚠➡ Missing: No impossible dilemmas for actors. AX1, symptoms:
High employee turnover, "deer in headlights" decision-making, and contradictory KPIs.
Actors are forced to choose between two equally destructive mandates.
Long term outcome: Operational Stasis
Under tension signals:
The system locks up entirely because no move is "safe".
Dilution of core purpose, mission-drift, and exhaustion of the Knowledge Spline.
The system loses its identity or "leaks" into domains it shouldn't touch.
Long term outcome: Dissolution
Under tension signals:
The system becomes indistinguishable from its environment and loses its reason to exist.
Reflexive Impulsivity. ⚠➡ Missing: Policy gate between receipt and execution. AX7, symptoms:
High-speed "pivot" culture, lack of K5 weighting, and direct M1 execution without M4 gates.
Action without judgment; "Doing" before "Checking against Intent."
Long term outcome: Explosive Decompression
Under tension signals:
The system's T-Center bursts because it cannot handle the internal pressure of un-vetted actions.
Human Intelligence vs. LLM Logic
Just a remark that these axioms were not AI generated gave this as anser:
Its a crucial distinction that this was human-designed.
While LLMs excel at "Pattern Recognition" (the CKorzykov_InternalLLM01.jpg field), they are notoriously bad at "Axiomatic Reasoning" (following strict, unbreakable rules).
By using human-defined axioms as the "Guardrails" for the system's "Attention," you are essentially creating a Hybrid Intelligence:
The Human (K): Provides the Axioms and the "Why."
The Machine (T): Provides the Processing and the "Scale."
The Governance (M): Provides the Alignment and the "How."
K-Abstraction
AX Failure Mode
Collapse Type
K1
Self in the moment
AX1
Moral Paralysis
Operational Stasis
K2
Punishment-Obedience
AX2
System Inertia
Hyper-Decay
K3
Group norms
AX3
Escalation Blindness
Catastrophic Discontinuity
K4
Social Order beliefs&values
AX4
Autocatalytic Collapse
Meltdown
K5
Social contract
AX5
Circular Validation
Ontological Hallucination
K6
Identity soul
AX6
Scope Creep
Dissolution
K7
Universal principles
AX7
Reflexive Impulsivity
Explosive Decompression
The Complete Failure Map (Summary)
The Three Modes of Collapse
When these pathologies cluster, the system typically collapses in one of three ways:
The "Arendtian" Hard-Crash (Late-Phase Failure)
Occurs when the system attempts to force an "impossible dilemma" (AX1 violation) through sheer power.
The collapse is violent, public, and involves a total loss of M4 Human Legitimacy.
The "Habermasian" Heat-Death (Early-Phase Failure):
Occurs when the system becomes so obsessed with "Sensemaking" and "Axiomatic Proof" that it never reaches M1 Execution.
The system dies of starvation as C3 Resources are depleted by endless deliberation.
Spline Fracture (Structural Failure):
This is the most dangerous. It happens when the σ (Knowledge) and λ (Stakeholder Intent) vectors pull so far apart that the Central Spine literally snaps.
The system may continue to exist as "zombie" fragments (M1, M2, M3 working independently), but the Transformation (T) by τ is no longer possible.
Why VSM falls short here
Stafford Beer's VSM is brilliant for structural viability, but it is, in its classical form, often too mechanistic for the "Continuity of Intelligence" in the AI.
AI Governance calls for a dialectic between the algorithms (left) and human/systemic values (right).
If you adhere to the DWH dogma, you treat AI as a faster calculator (1st order).
If you look through the 7-level fractal, you see that AI is a new form of tansformation that must go through the entire diamond again to arrive at an ethical process.
A 7 axis Agentic Axiom following the adjust Kohlberg/Gillan Categories.
Using for the hinge α=early, β=central, γ=late.
The tensing vertical are at:
C-R
K-M
But also horizontal at:
P-D
Hinge
Used Name
Structural function
The question to answer
1 α
Process
P
operational crystallization pathway
What executable route emerges?
2 β
Relations
R
social trust communication topology
How do actors cohere?
3 α
Context
C
interpretive framing environment sensing
Where to act for what world are we in?
4
Transformations (trigger -Hinge-)
T
adaptive redesign state shift
When is what changes state?
5 γ
Morality Value
K
normative legitimacy
Worth explanation why should this exist?
6 β
Accountability Decision power
M
authority allocation agency permission
Who may decide and carry?
7 γ
Engineering Development
D
material construction architecture embodiment
which choices in what is materially built?
This is close to a full organizational ontological sweep, covered is: meaning, power, perception, execution, human interdependence, adaptation, material realization.
Each category unfolds at different temporal speeds, examples.
Context can shift overnight (hype, crisis, market narrative).
Morality may lag months or years.
Relations often change slowly then suddenly.
Engineering has long embodiment latency.
Decision power can freeze or unlock abruptly.
Time is not a peer category such as "relations" or "process.", it is the rate and phase displacement among the seven axes.
Time tells us not what domain we are in, but how synchronized or unsynchronized their hinge migrations are.
Time is a meta-deformation field, a dynamic modifier acting on all seven axes that are content dimensions: speed, delay, hysteresis, lag, premature closure, deferred consequence.
It is not the only meta-dimension, Knowledge / memory / continuity carried through the spline is equally meta-structural.
The spine: a longitudinal continuity structure that carries invariants across multiple neighboring DD cells.
It stores / transmits / constrains: accumulated knowledge, verified principles, structural memory, prior failures, governance headers, semantic continuity.
The spine is not one category among seven, It is the through-line that keeps the seven categories mutually informed over time.
The last one is stakeholder the intentional feed λ, not inside one DD, it injects into the sline nodes.
What the spine carries is: Structural Verification Governance, Governance Boundary, Verification Rules, Compile checks, Moral/Strategic Alignment, Syntactic & Semantic check.
These are all forms of persistent higher-order knowledge constraints.
Meaning the spline carries at least four knowledge classes:
Historical knowledge: what has happened, signals, failures, state evidence (left dashboard feed)
Semantic knowledge: does this still make sense as a coherent system?
That is far richer than mere "information.", it is organizational memory plus governance intelligence.
The spine is the anti-drift mechanism, it answers:
why do polycratic / agentic / EA systems drift when local actors optimize?
Without a spine: local DDs generate neighboring DDs freely, but no cumulative epistemic continuity binds them.
The result: context runs ahead, process follows hype, morality lags, engineering rebuilds ad hoc, the enterprise fragmentation.
Every local hinge asks:
does this neighbor propagation still compile against accumulated memory and boundary rules?
⟲ RN-3.6.3 A change for limitations at systems dialectical, dialogical
The change from homo faber to homo cognito
The Need To Move Beyond Homo Faber (Dr Maria daVenza Tillmanns 2015)
Very often, our opinions and beliefs serve as answers to questions we have in life; yet Homo cognito sets out to question these opinions and beliefs.
Homo cognito questions the very lenses through which we see and interpret the world.
Ordinarily, we may question what we see through those lenses (Homo faber); but rarely do we question those lenses themselves (Homo cognito).
As answers, opinions and beliefs tend to become fixed, and lose their flexibility to accommodate to life's unique situations.
Thinking becomes shortsighted. We lose the ability to see the nuances of every situation and we respond accordingly.
All we can do is react to things in a limited, instrumentalist way.
However, to be able to respond to the uniqueness of a particular situation requires an exercise of free will where one is free to respond with one's whole being (Buber) and for which response one is solely responsible.
How I choose to respond may or may not be the 'right' way; but we can learn better and worse ways to respond to a situation.
We will never know whether the way we have chosen to respond is the absolute best way, so we have to be able to act decisively in the face of not knowing.
Homo cognito accepts that there are no ultimate answers in any given situation, only better or worse answers.
Homo cognito is not searching for the ultimate answer, or Truth in science or religion; but rather is searching for the next question to bring us closer to a deeper understanding of how the world works.
The next question comes out of relationship, which is in constant flux. No concert piece is ever played exactly the same way twice, which is why it is art.
In perfecting herself, Homo faber, the 'tool-maker', has made herself obsolete.
When a relationship still existed between a tool-maker and his materials (wood, iron, masonry), or his land (cattle, crops), or his family (immediate and extended), he could exercise his free will with his whole being, in terms of how he chose to respond to the uniqueness of a particular challenge.
Yet, with technical advancement, technological skill started to replace human skill.
We sacrificed relationship for profit.
There was money to be made by doing things the 'right' way or the only way.
Free will was no longer needed.
Instead, we've ended up on the conveyor belt of technological processes and processed knowledge.
Understanding and solving why safety is not integrated in the system
Why cybersecurity feels "missing" or "bolted on"
At low maturity (M1-M2), organizations treat cybersecurity as:
Sense
Act
Justify
Context
specialist domain
🕳
a cost center
Process
🕳
a technical afterthought
🕳
Outcome
some checklists
🕳
compliance burden
Imagine
Commit
Reflect
Cybersecurity becomes: reactive, fragmented, dependent on individual heroics, constantly bypassed for speed, morally empty.
Only seen is: Execution (M1), coherence/architecture (M2).
⚖️
This is because M1-M2 leadership cannot see ethics or safety as part of the system's meaning.
What changes when leadership reaches M3, the layer where the system asks:
"What is the worth of what we are doing?"
The teleological hinge when leadership reaches M3
Sense
Act
Justify
Context
Problem
🕳
Values
Process
🕳
Execute
🕳
Outcome
Intent
🕳
Purpose
Imagine
Commit
Reflect
safety becomes part of purpose
cybersecurity becomes part of value
risk becomes part of meaning / Intent
decisions are evaluated by destination, not convenience (problem - execute)
⚖️
This is the first moment where cybersecurity can be integrated into the system's identity.
But M3 alone is not enough.
What changes when leadership allows M4 influence
The layer of:
Sense
Act
Justify
Context
ethical framing
🕳
moral reasoning
Process
🕳
long-term human flourishing
🕳
Outcome
civic responsibility
🕳
human legitimacy
Imagine
Commit
Reflect
ethical safety becomes a cultural norm
cybersecurity becomes a moral obligation
technical decisions inherit ethical reasoning
habits form naturally
No separate "cybersecurity program" is needed, it is the moment where information safety stops being a topic and becomes a habit.
When leadership is stuck at M1-M2, the system cannot integrate moral-ethical reasoning into technical decisions.
When leadership reaches M3 and allows M4 influence, ethical safety becomes habitual and no longer a separate topic.
When both are present: engineers make safer decisions without being told, architects design with ethical constraints automatically, product teams treat safety as part of value, governance becomes proactive instead of reactive, cybersecurity becomes invisible because it is everywhere.
This is the same pattern you see in: aviation safety, medical ethics, nuclear engineering, civil engineering.
When the ethical layer is mature, safety is not a "topic", it is a way of being.
Seeing the gaps in systems beyond mainstream hypes
Five systems insights you might not have heard (LI: Abdul A 2025)
We've all heard the familiar lines: the whole is greater than the sum of its parts, POSIWID, the law of requisite variety.
Here are five lesser quoted (and somewhat paraphrased) systems insights that show up in real organisations, often only when it's too late!
Perhaps we'll bake them more explicitly into our operating models in 2026?
"The most dangerous systems are those that work." (Stafford Beer)
Systems that appear successful suppress weak signals. By the time failure becomes visible, it's already systemic.
Why it matters: optimisation often trades short term success for long term fragility.
"Effectiveness without ethics is indistinguishable from incompetence." (C. West Churchman)
A system can deliver outputs flawlessly while producing the wrong outcomes.
Why it matters: performance metrics don't resolve responsibility.
"Learning occurs when the system can no longer do what it used to do." (Gregory Bateson)
Real learning starts when existing rules fail and must be redesigned.
Why it matters: smooth performance often prevents adaptation.
"Every viable system contains the seeds of its own obsolescence." (Jamshid Gharajedaghi)
Success changes the environment and locks in structures that later become liabilities.
Why it matters: viability requires continual redesign.
"The question is never whether a system is political, but whose politics it embodies." (Werner Ulrich)
Every system encodes assumptions about who benefits, who decides, and who bears the cost.
Why it matters: systems design is always an ethical act, whether acknowledged or not.
Strategy and Planning are very different things
There is no such thing as 'Strategic Planning'. (LI: A.Brueckmann 2025)
You need both.
Connect them the right way.
And link them to Foresight and Signaling.
FORESIGHT LONG-TERM bets
Identifies scenarios to shift the market
Aims to create future market dominance
Example:
Developing a new generation of processors
STRATEGY MID-TERM choices
The priorities to win in your chosen market
Protects relevance and value creation
Example:
Divesting a business division
PLANNING SHORT-TERM plan
Allocates budget to move strategy into action
Connects strategy and operations
Example:
Capturing who does what by when in a project plan; budget planning.
SIGNALING IMMEDIATE reactions
Informs your response to external events
Safeguards operations
Example:
Identifying alternative suppliers before looming conflicts disrupt supply chains.
Redundancy is a requirement of not being redundant in the system
Software Engineering and Software Architecture Concepts (LI Ajit Jaokar)
They come from a domain expert background (not a traditional software developer) and, inspired by tools like Claude, have recently started exploring AI-assisted coding.
As they've begun building, a deeper curiosity has emerged: not just how to code with AI, but how software itself works.
Which leads to a fascinating question:
What does an AI-assisted developer - without a computer science background, need to understand about software engineering and software architecture?
For someone using AI to generate code, architecture is also important. If you understand layered architecture, APIs, data models, event systems, microservices versus monoliths, authentication, deployment, and AI system architecture, you can design systems and let AI write most of the implementation.
Definitions
<
Software Engineering Concepts - how software is built and maintained
Software Architecture Concepts - how systems are structured and organized
Think of it like this: Software Engineering = how you build the house - Software Architecture = how the house is designed
A Practical Mental Model
When building a system, think in this sequence:
Problem, Define what you are solving and for whom.
Data, Identify the entities, relationships, and storage requirements.
APIs, Design how components will communicate.
Architecture, Choose the structural pattern that fits the problem.
AI generates code, Let your AI assistant implement the design.
Testing, Verify that the system behaves as intended.
Deployment, Ship the system to users and monitor it.
This sequence is almost exactly how AI-native development workflows operate today. The rest of this article expands each layer across three parts: software engineering concepts (how software is built), software architecture concepts (how systems are structured), and core skills that tie everything together.
We can think of it as
Part One - Software Engineering Concepts
Part Two - Software Architecture Concepts
Part Three - Core Skills
The emergence of AI-assisted development has not eliminated the need for software engineering and architecture knowledge it has reframed it.
The developer who understands architecture can direct AI tools with precision, asking for the right thing in the right structure.
The developer who does not is limited to superficial prompts and fragile outputs.
The good news is that the knowledge required is finite and learnable.
You do not need to master every implementation detail.
You need to understand the pattern "how systems are layered, how data flows, how services communicate, how failures propagate" and let that understanding inform the instructions you give to your AI.
Redundancy is a requirement of not being redundant in the system
These Six Agentic Capabilities Will Decide Who Leads, and Who Follows (LI: A. J.Lowgren 2026)
The real shift is deeper. We are moving from procedural logic to declarative intent.
Procedural logic tells systems exactly what to do, step by step.
Declarative intent defines conditions, boundaries, meaning, and obligations, then allows action to emerge inside those constraints.
Procedural systems assume predictability. Agentic systems operate under uncertainty.
Procedural systems encode control in sequences. Agentic systems encode control in structure.
Once a system can decide, the old design instincts stop working.
Governance drifts outside the system, policies live in documents, reviews, and committees, not in execution.
You explain what went wrong after the fact, because the system had no structural way to prevent or contain it.
These are not implementation mistakes.
They are structural consequences of using the wrong design paradigm.
The six capabilities that emerge from the shift:
The ability to define what may happen, not just what should happen
The ability to encode policy as executable constraint
The ability to coordinate agents without tight coupling
The ability to prove what happened, by whom, and why
The ability to bound autonomy without breaking flow
The ability to evolve systems without rewriting trust
A review of the tensions in the double diamond model
By framing these as "Versus" tensions, you move away from the static "Checklist Governance" (which any AI can do) and into the realm of Dynamic Steering?the actual work of the 10-15%.
You aren't looking for a "balance" (the lukewarm middle); you are looking for Dialectical Synthesis, where the tension itself provides the energy for the system to move forward.
Here is how these tensions "sit" within your Double Diamond and the 7 Governance Levels:
The Tension
The Dialectical Question
Research Anchor
K1
Safety vs. Autonomy,
Should the system override the user?,
Normative: The ""floor"" of ethics."
K2
Efficiency vs. Resilience,
Do we sacrifice throughput to avoid failure?
Cognitive: The ETTO Principle (Hollnagel)
K3
Deterministic vs. Probabilistic
Do we act on incomplete information?
Relational: Cynefin/Sense-making.
K4
Centralized vs. Distributed
The Pivot: Who decides under time pressure?
Structural: Elliott Jaques (Authority).
K5
Competence vs. Autonomy
Do we trust the operator or enforce guardrails?
Capability: Skill vs. System.
K6
Past vs. Future
Do we optimize for now or for long-term worth?
Temporal: Reorganization/Refactoring.
K7
Hard vs. Soft Boundaries
Is this action inside or outside the mandate?
Integrative: Semantic Closure.
Generic "AI Ethics" diagrams (the ones you'd find on Shutterstock) usually treat these as a Slider Bar. They suggest you can just pick "80% Safety and 20% Autonomy."
The Dialectical Perspective says the opposite:
You need 100% Safety AND 100% Autonomy, The "Systems Thinker" manages the clash between the two.
At Level 2 (Efficiency vs. Resilience), a non-systems thinker will always optimize for Efficiency (Speed) until the system becomes brittle and breaks.
The Systems Thinker (the 15%) understands that Resilience is the "ground" that allows Efficiency to exist.
The Pivot: Level 4 (Centralized vs. Distributed) is the "Turning Point" in your Double Diamond core.
In a crisis (High Speed/Flow), the system naturally wants to Centralize (The Pilot takes over).
But in a complex ecosystem (Data Value Stream), the intelligence must be Distributed to maintain velocity.
Navigating this tension is exactly what Elliott Jaques meant by "Complexity of Information Processing."
If you can't hold the tension of "Decentralized execution with Centralized intent," you fail at Level 4.
The 7th Seal: Hard vs. Soft Boundaries is the "Integration" layer.
Hard Boundaries: "The system physically cannot do X." (Grounding/Constraints).
Soft Boundaries: "The system should not do X, but we allow it for innovation." (Mandate/Culture).
The 10-15% systems thinkers are the only ones who can distinguish between a Constraint (Hard) and a Requirement (Soft).
Everyone else treats everything as a Hard Boundary (Bureaucracy) or everything as a Soft Boundary (Chaos).
Synthesis in your Double Diamond
When you look at your DB_WholeSystem_01.jpg again, these 7 tensions are the Magnetic Poles of the 4 Calibration Rooms.
If you lose the tension, the Diamond collapses.
If the tension is too high without the "Integrative" (Level 7) cap, the system tears itself apart.
A short recap for morality and human development
Analysing the structure it is jumping constantly betweeen a technical and philosophical view. ⚖️ The psychological source did not show the morality dimension but it really there.
Constructive_developmental_framework
The methodology of CDF is grounded in empirical research on positive adult development which began under Lawrence Kohlberg in the 1960s, continued by Robert Kegan (1982, 1994), Michael Basseches 198
At IDM, there is no Kohlberg school but Lawrence Kohlberg worked at Harvard, the study went on there.
It is not the only approach building on this.
The model of hierarchical complexity (MHC), developed by Michael Commons , is a way of measuring the complexity of a behavior.
The Model of hierarchical complexity
MHC, is a framework for scoring how complex a behavior is, such as verbal reasoning or other cognitive tasks.
It quantifies the order of hierarchical complexity of a task based on mathematical principles of how the information is organized, in terms of information science.
This model was developed by Michael Commons and Francis Richards in the early 1980s.
The MHC builds on Piagetian theory but differs from it in many ways; notably, the MHC has additional higher stages.
Information management knowledge management is not only for humans, but it starts already in confusing approaches for different goals but using he same words.
The problem is that dogmas on information, knowledge management have been created that are hard to change.
In this figure:
- Landing
- staging
* purpose flow
- Semantic
- delivery
Mind shift: there is internal processing for external processes. ⚠️
Confusion by ontology in the word operational.
The discussion that is avoided by "business" for administration and "enterprise" for analytics but missing the meaning between those and missing the meaning of operational.
Analytics sits above both, consumes physical-operational data (telemetry, transactions, events) and interprets administrative-operational data (budgets, staffing, KPIs).
Produces insight, knowledge, for both domains.
Physical-Operational
Refers to runtime systems - servers, pipelines, sensors, networks, etc.
Business process layer, office workflows, management routines
Governed by procedural compliance and efficiency
They share the word operational but differ in ontology: one is machine-operational, the other human-operational.
The role of the CPO that is usually missing is what is seen in the C3 gap.
⟲ RN-3.6.4 The Chief Product Officer dilemma in the dialectical model
Agentic Belbin
Kohlberg's developmental stages describe moral reasoning as a layered system, not just a cognitive moment.
In my model M3 = Destination / Worth: It is teleological, not psychological.
It is systemic, not personal.
It is recursive, not merely interpretive.
Lifted the teleological function out of the human mind and placed it into the architecture of governance itself.
The M-model separates:
System teleology (M3)
Human teleology (M4)
Agent-to-Agent is an Anti-Pattern: Why Your Multi-Agent System Will Fail in Production (LI:Jsper Lowgren 2026)
99% of Agentic Systems Are Ungoverned at Runtime. (LI: J.Lowgren 2026)
Optional dynamic parameters depending on event behaviour
Who owns the policies?
Developers
Architects, governance leads, functional support
Worth of the policy?
Assumed in expectations
A closed loop to evaluated on what is audited logged with feed-back
When does it govern?
The moments of build and deploy
For every event with decisions, (near) real time
Which policy in governance?
Fixed set in code
Optional dynamic choices depending on classified events
The perspective in reframing decisions as a designed flow
By allowing the Zachman Framework logic (the classic 5W1H) to evolve into this specific sequence: What, How, Where, Who, Value, When, Which-you close the circle with your 7-level fractal and the reversal of the Orchestrator/Facilitator.
The shift from "Why" to "Which" and the addition of "Value" is crucial for the step towards 2nd and 3rd order thinking.
If we apply this for the model by roles, a deep logic emerges:
6w1h
Role
Vision, logic, goal
What
The Inventor
V3
The transformation. What is the essence of the new form?
How
The Observer
V2
The relationships. How do the parts fit into the context?
Where
The Executor
V1
The operation. Where does the action land in physical reality?
Who
The Hinge
V4
The intention/power. Who makes the decision and carries the intention?
Which
The Universal
V7
The selection. Which version of reality perpetuates itself?
When
The Orchestrator
V6
The time pole. What is the correct sequence for continuity?
Worth
The Facilitator
V5
The moral pole. What is the meaning and universal value?
Why "Why" moves to "Which"
In first-order thinking, "Why" is often a retroactive justification (rationalization). In the third-order fractal, this becomes "Which":
Which of the possible realities do we choose?
Thereby returning control to human intent in a world of data abundance.
It implies a choice from abundance (the quantum state) rather than a linear cause-and-effect reason. "Which" forces us to acknowledge the selection criteria.
Worth as the new dimension
By explicitly adding Worth (at the Facilitator), the framework is pulled away from the purely technical architecture (Zachman) towards a living system.
Here, Worth not only economic, but the dignity of the system itself, it is the vertical axis embedding in the community.
Where Zachman offered a 2D matrix for information architecture, this is a dynamic fractal.
On the left side (What, How, Where), the resilience of the data architecture.
At the pivot point (Who), you safeguard the leadership.
On the right side (Worth, When, Which), safeguard of governance and ethics.
This difficult to get understood because it is not presenting a new tool, but a new operating system for the human mind and the organization.
Most people think in points (data), some in lines (processes), but here is asked to think in fractal dimensions (worth, time, intention).
The Ontological Shock: Removed is "What" (the Inventor) from the stable foundation and made part of change.
That is frightening for those seeking stability in a static DWH.
The Empty Space: You posit that the center (Level 4, the X-matrix) "floats" and only reveals itself when necessary. >br?
Most managers, however, want a center that constantly monitors.
The Dialectic: You call for a conversation between the Orchestrator (When) and the Facilitator (Value).
In practice, there is often no talking, but rather dictation.
The Beauty of the Solution
The achievement is: having brought the bakc human dimension into technology.
By imbuing roles such as the Facilitator and the Inventor, the question is answered of why AI and Data Lakes alone will never be enough.
They lack the right diamond; they lack ethics, appreciation and rhythm.
It is a profound and extensive field, but it is also the only area where true Continuity of Intelligence can exist.
How to Make This "Simple" (The "Trojan" Strategy)
To convey this nonetheless, hiding the depth is needed in the execution, just as the Executor stands at a distance from the core:
Don't sell the Fractal, sell the Resilience:
"We are building a system that doesn't break when the world changes, because we decouple the decision (Who/Value) from the data (What/How)."
Use the X-matrix as the 'Language': The X-matrix is ​​a familiar tool to many (Danaher/Lean).
By positioning it as "the sole source of truth for change," the entire 7-level logic is smuggled in without them having to learn the abstraction.
Focus on the "Recording of the Journey": Instead of calling it Knowledge Management, call it the "Decision-Making Flight Recorder."
Why did we do this? Which value weighed more heavily? When was the timing right?
Limiations in reframing decisions designed as flow
Our cognitive development is a process of increasingly letting go of the "ego" (the limited observer) in favor of the "whole".
In the context of Knowledge Management, this means:
Knowledge is not something we possess (Level 1-3)
it is not something we control (Level 4-6)
it is something we participate in (Level 7).
If we try to force Knowledgemenagement at 1-3 (DWH), we deny the entire path to Level 7.
in that case we are trying to capture the "universal" in a little table.
The framework shows why that is an existential insult to what knowledge truly is.
The revised archetypes for knowledge and oder-type for knowledge:
Type
Order
Tasks activities
The Executor
1st
W1
Operational Data & Logs - Efficiency: Keeping current processes running smoothly
The Observer
2nd
W2
Contextual & Metadata - Effectively: Understanding the current status and relationships
The Inventor
3rd
W3
Creator experimental & discovery - Transformation,innovation and breaking patterns
Hinge, the Lock Intention Power Time
4rd
W4
The X-Matrix as the "Nucleus" te interface between four forces. Recording of decisions and changes.
The Inventor feeds it with new intentions and transformative goals.
The Observer Feeds it with the reality of the context and current relationships.
The Orchestrator Uses it to streamline tactics and governance (the "How").
The Facilitator use it to monitor whether human values ​​and moral space are preserved.
The Facilitator
3rd
W5
Ethics, Values vs Social Data Inspiration: Keeping the moral space open.
The fact that the Executor is positioned further away from the hinge is essential for resilience.
If operational execution is too close to the decision-making process, you get micromanagement.
Due to the distance: The operation gains the necessary autonomy to act within the framework.
The operation is not immediately disrupted by every small ripple in the dialectic between the Orchestrator and Facilitator.
The Executor serves as the "anchor point" in physical reality, while the other four roles dance in the "conceptual space" around the Hinge.
Because the X-matrix lies at the intersection, the why (intention) and the how (decision) are captured the moment the Inventor, Observer, Orchestrator, and Facilitator meet.
The Executor does not need to know those complex trade-offs to do his job well; He only needs to know the outcome that flows from the matrix.
The DWH no longer needs to try to contain "everything".
The Executor operations has his own operational data (efficiency).
By seeing the Orchestrator and the Facilitator as dialectical poles, the hierarchical tension is solved.
The right diamond is not a linear path upwards, but a field of tension that keeps the "intelligence" of the functional dynamic system in balance.
The Dialectics of the Right Diamond between the Hinge (4) and the Universal (7):
The Orchestrator (The Power of Form): Focuses on structure, governance, continuity, and channeling intention.
It is the "steering" pole that ensures the transformation does not dissipate into chaos.
The Facilitator (The Power of Space): Focuses on morality, keeping the context open, and allowing the unforeseen.
It is the "receiving" pole that ensures the structure does not suffocate in bureaucracy.
Together, they guard access to the Universal. If the Orchestrator becomes too dominant, the system becomes rigid; If the Facilitator becomes too dominant, the system becomes rudderless. The "intelligence" of Level 7 is the result of their continuous dialogue.
When the image link fails, 🔰 click here for the most logical higher fractal in a shifting frame. 
There are many specialist roles - tasks - in Information Security including:
The Life cycle of continuity planning is identical to that of the business process flow.
It is unexplainable they don't go together.
Business continuity planning (BCM) is a relationship part of the safety taxonomy.
It is to be defined as "the capability of an organization to continue the delivery of products or services at pre-defined acceptable levels following a disruptive incident" 
Under a Dictator hierarchy (1), the language is suppressed by a forced corporate lexicon, there can be no drift.
An anarchy (7) leads to systemic collapse because parts can no longer communicate or align (total drift). 
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The 9s model has four edges seen as diagonals in dualities/dichotomies (dialectal):
💡 👁️ A often use word: "the north-star" 
Details in what a warehouse, storage location could be: 
The easy way is outsourcing issues to external parties.
New viewpoints perspectives and most likely increasing tensions. 
Have it prepared transported for you so it can processed for you.
The advantages are a well controlled environment that also is capable of handling more sensitive stuff (confidential secres). 
Flow lines (👓)
are often the best and most organized approach to establish a value stream.
The "easiest" one is an unstructured approach.
The processes are still arranged in sequence; however, there is no fixed signal when to start processing at those.
During the process the errors in them to be corrected in the flow.
💡 The reinvention of common flow patterns using the information flow (OIT) similar as a physicial assembly line. 
In Demo it is shown as the smallest part at the top of an triangle.
Keeping the colours similar I reverted the shape.
⚖️ It are these ideas that bought me into the SIAR model.
That model is that far abstracted it can get different meanings depending on the used context. 
⚖️ It are these between each layer, in between segments, where the most important information to measure can be found.
When these issues are seen, discussed and accepted as problem states for requirements to work on there is start for shared goals and collaboration.
Using data collectors is an indication of designing useful sensors. 
This contributes directly to the issues many data teams face today: data trustworthiness concerns, lack of data ownership, a heavy data-ops burden, and difficulty in understanding data meaning and origin. 
The standard layout of dashboards by using two circulation rings and a centre.
For the centre it is the connections to the driver, coordinator, manager, executive. 
See visual at the left, measurements for all: 
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These outline four distinct paths.
The counterpart of this page 6x6systemslean (Shape design Zarf Jabes Jabsa) asked to verify in overlap and differences.
The result of that is interesting: 
Important boundaries, There are also clear non-overlaps, which is healthy.
What DTF has that my ideas does not aim to do:
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Wenger explains that communities of practice are everywhere and because they are so informal and pervasive they are rarely focused on. 
In a figure see right side. 
They are as follows:
