Design Data - BI, Analytics
RO-1 Introductions for functional details at realisations
RO-1.1 Contents
⚙ RO-1.1.1 Looking forward - paths by seeing directions
A reference frame in mediation innovation
When the image link fails,
🔰 click
here.
There is a revert to main topic in a shifting frame.
Contexts:
◎ r-steer the business
↖ r-shape mediations change
↗ r-serve split origin
↙ technical details
↘ data value stream
Fractal focus for fucntionality by technology
The cosmos is full of systems and we are not good in understanding what is going on.
In a ever more complex and fast changing world we are searching for more certainties and predictabilities were we would better off in understanding the choices in uncertainties and unpredictability's.
Combining:
- Systems Thinking, decisions, ViSM (Viable Systems Model) good regulator
- Lean as the instantiation of identification systems
- The Zachman 6*6 reference frame principles
- Information processing, the third wave
- Value Stream (VaSM) Pull-Push cycle
- Improvement cycles : PDCA DMAIC SIAR OODA
- Risks and uncertainties for decisions in the now near and far future, VUCA BANI
The additional challenge with all complexities is that this is full of dualities - dichotomies.
⚙ RO-1.1.2 Local content
⚖ RO-1.1.3 Guide reading this page
The position of this pages in the whole
This page is positioned as the
functionality details that are a split from the concepts in the Zarf JAbes technology idea for enabling a realisation.
The technology concepts page is a split from the generic technology page (r-serve). That page is part of the generic 6*6 reference frame.
There is no intention to have all chapters completely filled ar achieve a belanced load in the content.
The goal is a collection of what I have in a more understandable strcuture than beig spread all over many pages.
| | | | Details |
| | | | Technology |
| Context | r-serve: SDLC DevOps | Concepts | 🕳 |
| | | | Functional |
| | | | Details |
The entry anchor will be the RO-2 chapters.
An introdcution when appplicable RO-1
The impact when applicable in RO-3
The quest for methodlogies and practices
⚒ RO-1.1.4 Progress
done and currently working on:
- 2026 week 4
- Starting to refill this page in a new structure
The topics that are unique on this page
RO-1.2 The technological approach in performance
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⟲ RO-1.2.1 Info
butics
The Tragic mismatch in data strategy
A review on the 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 in Data Acquisition versus Monetization Strategies. (LI: Bill Schmarzo 2020.)
The Internet and Globalization have mitigated the economic, operational and cultural impediments traditionally associated with time and distance.
We are an intertwined global economy, and now we realize (the hard way) that when someone sneezes in some part of the world, everyone everywhere gets sick.
We are constantly getting punched in the mouth, and while we may not be sure from whence that punch might come next (pandemic, economic crisis, financial meltdown, climate change, catastrophic storms), trust me when I say that in a continuously transforming and evolving world, there are more punches coming our way.
my next two blogs are going to discuss: How does one develop and adapt data and AI strategies in a world of continuous change and transformation?
It"s not that strategy is dead (though at times Strategy does look like an episode of the "Walking Dead"); it"s that strategy - like every other part of the organization and the world - needs to operate in an environment of continuous change and transformation.
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.
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.
No wonder CIO"s have an almost singular mandate to reduce those data management costs (hello, cloud).
Data is a cost to be minimized when the only "value" one gets from that data is regulatory, compliance and management risk reduction.
Companies are better at collecting data, about their customers, about their products, about competitors, than analyzing that data and designing strategy around it.
Too many organizations are making Big Data, and now IOT, an IT project.
Instead, think of the mastery of big data and IOT as a strategic business capability that enables organizations to exploit the power of data with advanced analytics to uncover new sources of customer, product and operational value that can power the organization's business and operational models.
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.
Technology push focus BI tools.
The technology offerngs are rapidly changing the last years (as of 2020). Hardware is not a problemtic cost factor anymore, functionality is.
hoosing a tool or having several of them goes with personal preferences.
Different responsible parties have their own opinion how conflicts should get solved. In a technology push it is not the organisational goal anymore.
It is showing the personal position inside the organisation.
🤔 The expectation of cheaper and having better quality is a promise without warrants .
🤔 Having no alignment between the silo´s there is a question on the version of the truth.
Just an inventarization on the tools and the dedicated area they are use at:
Mat Turck on
2020 ,
bigdata 2020 An amazing list of all,kind of big data tools at the market place.
RO-1.3 Competing functionality vs safety to realisation
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⟲ RO-1.3.1 Info
Safety first by design, a pracatical case II
The question:
Why spending capitals on hiring, while their best people walk out the door?
is about culture trust, ethics, conflicts, commitment, accountability, team results for the service outcome.
- A limited list of culture killers - (LI: P.Evans 2025)
That's because a high-performing culture isn't built, it's engineered.
And most leaders don't realise they've hard-coded failure into their system.
I've seen it happen across startups, scale-ups, and global giants...
- Great people
- Great products
- Slowly pulled apart by how they operate internally.
Because culture isn't built through slogans on the wall.
It's the unseen behaviours that either build trust or break it.
Here are 8 hidden culture killers that quietly drain performance:
- '"We're a family" ➡ Sounds warm, but it blurs boundaries and excuses.
👉🏾 Instead: Build a team, not a family. Clear roles and fair expectations create psychological safety, not forced intimacy.
- Micromanagement ➡ Kills initiative, grows dependence on leaders, and destroys creative confidence.
👉🏾 Instead: Replace control with clarity. Define outcomes, not tasks, and let people own how they get there.
- Too many managers, not enough doers ➡ Suddenly, meetings multiply, progress slows, and still, no one's held accountable.
👉🏾 Instead: Flatten decision-making. Reward action over alignment.
- Ignoring feedback ➡ If people stop speaking up, you've already lost them.
👉🏾 Instead: Build feedback loops into your system. Retros, pulse surveys, open channels. But remember, listening is only powerful if it leads to visible change.
- Decisions behind closed doors ➡ Secrecy leads to suspicion faster than any pay gap.
👉🏾 Instead: Default to transparency. Share the '"why" behind decisions, not just the '"what." It builds trust and alignment faster than any "all-hands" speech.
- Overloading top performers ➡ You don't reward excellence by exhausting it.
👉🏾 Instead: Scale their impact, not their workload. Automate, delegate, and invest in systems that protect your best people from burnout.
- No work-life boundaries ➡ If rest feels like guilt, performance will collapse.
👉🏾 Instead: Treat recovery as performance infrastructure. Model it yourself, when leaders rest, permission follows.
- Silent meetings➡ When the same voices dominate, innovation slowly dies.
👉🏾 Instead: Engineer participation. Rotate facilitators, ask for written input. Inclusion is a design choice.
You can't just '"hope" your culture into being. You have to engineer it.
Every system either builds trust or breaks it, and if you don't fix it, someone else will leave because of it.
Construction: existing systems that are hard to change
Construction regulations for 2025 focus heavily on sustainability, safety, and digitalization, with key changes including stricter energy performance, new Digital Product Passports (DPP) for materials in the EU, updated health & safety roles (like registered safety managers), and a push for greener building methods (heat pumps, solar). In the UK, the Building Safety Levy and new protocols for remediation orders are emerging, while globally, there's a trend towards clearer, faster permitting and greater accountability in construction.
Key Themes & Regulations
- Sustainability & Energy (EU & UK Focus):
- Digital Product Passports (DPP): Mandatory digital IDs for construction products under the EU's Ecodesign Regulation, tracking materials, performance, and recyclability.
- Energy Efficiency: Stricter standards for new builds, pushing low-carbon heating (heat pumps) and better insulation.
- Embodied Carbon: Increasing focus on calculating and reducing the carbon footprint of materials.
- Health & Safety (Global Updates):
- Professional Registration: Introduction of registered Construction Health & Safety Managers (CHSM) in some regions (e.g., South Africa draft regs) to elevate standards.
- Ergonomics: Greater emphasis on worker well-being and preventing musculoskeletal disorders.
- Notification Changes: Some areas are expanding the scope of all construction work requiring notification to authorities, not just high-risk activities.
- Building Safety (UK Specific):
- Building Safety Levy: A new levy on new homes in England to fund remediation of building safety defects.
- Legal Protocols: New court guidance expected for building safety remediation orders and liability orders.
- Permitting & Process (EU Trend):
- One-Stop Shops: Calls for simplified, digital, single-permit systems with clearer timelines for approvals.
Legal Protocols: New court guidance expected for building safety remediation orders and liability orders.
What it Means for You (General)
- Design for Green: Incorporate heat pumps, solar, and high insulation from the start.
- Track Materials: Be ready for DPP requirements and provide detailed environmental data.
- Elevate Safety: Expect new training and potentially registered safety roles.
- Expect More Scrutiny: Authorities are increasing oversight on safety, sustainability, and permit compliance.
Note: Regulations vary significantly by country.
Guide to Construction Products Regulation (CPR)
The Construction Products Regulation (CPR) is a pivotal EU legislation that sets standardized safety, performance, and environmental impact requirements for construction products across the EU. Originally established in 2011 to streamline the circulation of construction products within the Single Market through standardized guidelines, the CPR was updated in 2024 to address modern environmental challenges, advancing sustainability and transparency in the construction sector.
Health:
cdisc
In July 2022, the FDA published, in Appendix D, to their Technical Conformance Guide (TCG), a description of additional variables they want in a Subject Visits dataset. A dataset constructed to meet these requirements would depart from the standard, so validation software would create warnings and/or errors for the dataset. Such validation findings can be explained in PHUSE?s Clinical Study Data Reviewer?s Guide (cSDRG) Package.
phuse
The Global Healthcare Data Science Community Sharing ideas, tools and standards around data, statistical and reporting technologies
phuse
PHUSE Working Groups bring together volunteers from diverse stakeholders to collaborate on projects addressing key topics in data science and clinical research, with participation open to all.
RO-1.4 Defining taxonomies - concepts - ontology
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⟲ RO-1.4.1 Info
The 4 leadership behaviors that drive transformation
An email promotion:
"Many leaders discover: they are the problem." (email: lean.org. 2025)
Tools account for 20% of success. Leadership behaviors account for 80%.
David Mann, in his research on lean management systems, found that "implementing tools represents at most 20% of the effort in lean transformations; the other 80% is expended on changing leaders' practices and behaviors, and ultimately their mindset."
Yet most organizations invest heavily in tool training while treating leadership development as optional.
Four behaviors that drive transformation:
- Go See (Gemba)
Regular presence where value is created. To understand, not inspect.
- Ask Why (Coach)
Develop capability through questions. Build scientific thinking.
- Show Respect (Safety)
Create environments where problems surface early.
- Connect to Strategy (Hoshin)
Ensure every level understands how daily work supports objectives.
These aren't separate activities. They're interconnected behaviors that create the management system for sustained performance.
Daily management boards drive problem-solving (not just tracking). Teams catch issues early because they understand targets and feel safe surfacing problems.
From "Managing on Purpose" (book): "Hoshin kanri is an excellent opportunity for leaders to learn to lead by responsibility as opposed to authority."
butics
Moral Complexity of Organisational Design (LI:R.Claydon 2025)
Buurtzorg has become a kind of organisational Rorschach test. In his original essay, Stefan Norrvall reads it through a lens of organisational physics:
- complexity is conserved,
- work is stratified,
and Buurtzorg works because it relocates integrative load from managers into small whole-task teams, architecture, and an unusually supportive Dutch welfare ecosystem.
In response, Otti Vogt argues that this frame is ontologically and morally too thin: Buurtzorg is not just a clever cybernetic design, but a solidaristic, post-neoliberal project grounded in care ethics, widening moral circles, and a refusal to treat nursing as timed piecework.
Certainty uncertainty in the theory of constraints
Continuation of the 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
A typical example of ignoring uncertainty is widespread reliance on single-number discrete forecasts of future sales.
Any rational forecast should include not just the quantitative average (a single number), but also a reasonable deviation from that number.
The fact that most organizations use just single-number forecasts is evidence of the illusion of certainty.
Organizations typically plan for long-term objectives as well as for the short-term.
A plan requires many individual decisions regarding different stages, inputs or ingredients.
All such decisions together are expected to lead to the achievement of the objective.
But uncertainty typically crops up in the execution of every detail in the plan.
This forces the employees in charge of the execution to re-evaluate the situation and introduce changes, which may well impact the timely and quality of the desired objective.
What motivates people to make the decisions that they do?
Many readers will be familiar with Abraham Maslow's hierarchy of needs.
Maslow theorized that humans have needs that they strive to satisfy.
Further, Maslow suggested that it's unsatisfied needs that motivate people to action.
Maslow also suggested that human needs are hierarchical.
This means that satisfying needs lower in the hierarchy pyramid captures a person's attention until they are largely (though not necessarily completely) satisfied.
At that point, the these lower level needs become less of a motivator than unsatisfied higher level needs.
The person in question will then bend most of his or her efforts to fulfilling those needs.
The Dod Strategy statement knowledge management: data safety
DoD data strategy (2020) Problem Statement
Make Data Secure
As per the DoD Cyber Risk Reduction Strategy, protecting DoD data while at rest, in motion, and in use (within applications, with analytics, etc.) is a minimum barrier to entry for future combat and weapon systems.
Using a disciplined approach to data protection, such as attribute-based access control, across the enterprise allows DoD to maximize the use of data while, at the same time, employing the most stringent security standards to protect the American people.
DoD will know it has made progress toward making data secure when:
| | Objective | information Safety |
| 1 | Platform access control | Granular privilege management (identity, attributes, permissions, etc.) is implemented to govern the access to, use of, and disposition of data. |
| 2 | BIA&CIA PDCA cycle | Data stewards regularly assess classification criteria and test compliance to prevent security issues resulting from data aggregation. |
| 3 | best/good practices | DoD implements approved standards for security markings, handling restrictions, and records management. |
| 4 | retention policies | Classification and control markings are defined and implemented; content and record retention rules are developed and implemented. |
| 5 | continuity, availablity | DoD implements data loss prevention technology to prevent unintended release and disclosure of data. |
| 6 | application access control | Only authorized users are able to access and share data. |
| 7 | information integrity control | Access and handling restriction metadata are bound to data in an immutable manner. |
| 8 | information confidentiality | Access, use, and disposition of data are fully audited. |
Retrosperctive for applying collective intelligence for policy.
Ideas into action (Geoff Mulgan )
What's still missing is a serious approach to policy.
I wrote two pieces on this one for the Oxford University Press Handbook on Happiness (published in 2013), and another for a Nef/Sitra publication.
I argued that although there is strong evidence at a very macro level (for example, on the relationship between democracy and well-being), in terms of analysis of issues like unemployment, commuting and relationships, and at the micro level of individual interventions, what's missing is good evidence at the middle level where most policy takes place.
This remains broadly true in the mid 2020s.
I remain convinced that governments badly need help in serving the long-term, and that there are many options for doing this better, from new structures and institutions, through better processes and tools to change cultures.
Much of this has to be led from the top.
But it can be embedded into the daily life of a department or Cabinet.
One of the disappointments of recent years is that, since the financial crisis, most of the requests to me for advice on how to do long-term strategy well come from governments in non-democracies.
There are a few exceptions - and my recent work on how governments can better 'steer' their society, prompted by the government in Finland, can be seen in this report from Demos Helsinki.
During the late 2000s I developed a set of ideas under the label of 'the relational state'.
This brought together a lot of previous work on shifting the mode of government from doing things to people and for people to doing things with them.
I thought there were lessons to learn from the greater emphasis on relationships in business, and from strong evidence on the importance of relationships in high quality education and healthcare.
An early summary of the ideas was published by the Young Foundation in 2009.
The ideas were further worked on with government agencies in Singapore and Australia, and presented to other governments including Hong Kong and China.
An IPPR collection on the relational state, which included an updated version of my piece and some comments, was published in late 2012.
I started work on collective intelligence in the mid-2000s, with a lecture series in Adelaide in 2007 on 'collective intelligence about collective intelligence'.
The term had been used quite narrowly by computer scientists, and in any important book by Pierre Levy.
I tried to broaden it to all aspects of intelligence: from observation and cognition to creativity, memory, judgement and wisdom. A short Nesta paper set out some of the early thinking, and a piece for Philosophy and Technology Journal (published in early 2014) set out my ideas in more depth.
My book Big Mind: how collective intelligence can change our world from Princeton University Press in 2017 brought the arguments together.
The lean project shop
The project shop is associated with not possible applying lean thoughts.
The project shop, moving the unmovable a lean appraoch, is altought possible to see getting done in lean approache.
Does it or are there situations where new technology are implementing a lean working way.
It is using a great invention of process improvement over and over again.
That is: the dock. Building in the water is not possible. Building it ashore is giving the question how to get it into the water safely.
🔰 Reinvention of patterns.
Moving something that is unmovable.
Changing something that has alwaus be done tath wasy.
Minimizing time for road adjustment, placing tunnel. Placing it when able to move done in just 3 days. Building several months.
See time-lapse. 👓 Placing the tunnel was a success, a pity the intended road isn´t done after three years.
The project approach of moving the unmovable has been copied many times with the intended usage afterwards.
rail bridge deck cover
The approach is repeatable.
💡 Reinvention of patterns. Moving something that is unmovable.
A generic mindshift for integrated governance
Business Integrated Governance (BIG) is a framework that aligns governance, risk management, and compliance (GRC) with business strategy and operations to enhance decision-making and drive sustainable performance.
Key Aspects of Business Integrated Governance (BIG):
- Alignment with Business Strategy: Governance frameworks are designed to support and drive business goals rather than just ensuring regulatory compliance.
- Risk Management Integration: Governance processes include proactive risk management, identifying and mitigating risks that could impact business performance.
- Performance-Driven Governance: Decision-making is data-driven and focused on improving efficiency, effectiveness, and business outcomes.
- Stakeholder-Centric Approach: Governance considers the interests of all stakeholders, including shareholders, employees, customers, and regulators.
- Technology & Automation: Digital tools and AI are often used to streamline governance processes, ensuring transparency and real-time monitoring.
- Agility & Adaptability: Governance frameworks are flexible and adaptable to changing market conditions, regulatory requirements, and organizational needs.
The challenge of BIG is to shift from relying on a patchwork of governance practices to defining and managing fully integrated governance operation with the necessary Capability.
For any organisation, a well-defined (BIG) Capability primarily enables the effective communication of strategic expectations, followed by ongoing systematic performance oversight, decision making, re-steering, and course corrections, leading to greater strategic outcomes and agility.
See right side
Generic governance a double loop.
Capability achievement requires the consideration of several crucial elements, including a strategy information model, integrated operating models, and a governance regime.
Clear accountability management, suitable enablers (tools, processes, standards), business support and assurance (orchestrating the operation), data / information solutions and leadership are all essential for success.
RO-1.5 Defining temporal boundaries dependencies
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⟲ RO-1.5.1 Info
The Certainty loophole in wanting predictability
(LI: A.Constable 2025)
In strategy, understanding the distinction between scenarios and forecasts can be crucial to achieving long-term success.
The distinction is this:
- Forecasts ➡ What is likely to happen:
- Based on historical data, trends, and expected developments
- Provides a single probable outcome
- Often used for budgeting and short-term planning
- Scenarios ➡ What could happen:
- Considers multiple possible futures based on key uncertainties
- Helps organisations prepare for different potential outcomes
- Critical for long-term strategic resilience and stress testing
While forecasts help navigate the near future, scenario planning equips organisations to anticipate shifts, adapt strategies, and stay ahead in an unpredictable world.
Lean accounting removing certaintity constraints
The Danaher Business System (DBS), developed by Mark DeLuzio, is a comprehensive Lean-based operating model that transformed Danaher Corporation into one of the most successful industrial conglomerates in the world.
It integrates strategy deployment, continuous improvement, and cultural alignment into a unified system for operational excellence.
| Element | Description |
| Lean foundation | Built on Toyota Production System principles, emphasizing waste elimination, flow, and value creation. |
| Policy Deployment (Hoshin Kanri) | Strategic alignment tool that cascades goals from top leadership to frontline teams. |
| Kaizen culture | Continuous improvement through structured problem-solving and employee engagement. |
| Visual management | Dashboards, metrics boards, and process visibility tools to drive accountability and transparency. |
| Standard work | Codified best practices for consistency, training, and performance measurement. |
| Lean accounting | Developed by DeLuzio to align financial systems with Lean operations , focusing on value streams rather than traditional cost centers. |
Mark DeLuzio's Role and Philosophy
- Architect of DBS: As VP of DBS, DeLuzio led its global deployment and helped Danaher become a benchmark for Lean transformation.
- Lean Accounting Pioneer: He introduced the first Lean accounting system in the U.S. at Danaher's Jake Brake Division.
- Strategic Integrator: DeLuzio emphasized that Lean must be tied to business strategy , not just operational tools.
- Respect for People: A core tenet of DBS, ensuring that transformation is sustainable and human-centric.
| Activity | Description |
| Eliminating waste in accounting processes | Traditional month-end closes and cost allocations often involved redundant steps. Lean Accounting applies value-stream mapping to streamline closing cycles, freeing finance teams to focus on strategic analysis |
| Value-stream based reporting | Instead of tracking costs by departments, Lean Accounting organizes them by value streams , the end-to-end activities that deliver customer value. This provides clearer insight into profitability tied to actual products or services |
| Real-time decision support | Lean Accounting emphasizes timely, actionable data rather than lagging reports. This enables leaders to make faster, more informed investment and governance decisions |
| Continuous improvement in finance | Just as Lean manufacturing fosters kaizen, Lean Accounting embeds continuous improvement into financial governance, ensuring reporting evolves with operational needs |
| Integration with agile governance | Lean financial governance adapts investment tracking to modern delivery methods (agile, hybrid, waterfall), ensuring funding and prioritization align with how initiatives are actually execute |
| Transparency and cultural alignment: | By eliminating complex cost allocations and focusing on value creation, Lean Accounting fosters a culture of openness and accountability across departments |
Why This Matters for Governance
Traditional accounting often obscured the link between operations and financial outcomes. Lean Accounting reshaped governance by:
- Making financial metrics operationally relevant.
- Aligning investment decisions with customer value creation.
- Enabling adaptive governance models that support agile and Lean transformations.
This is why companies like Danaher, GE, and others used Lean Accounting as a cornerstone of their governance systems , it provided clarity, speed, and alignment between finance and operations.
Using BI analytics
Using BI analytics in the security operations centre (SOC).
This technical environment of bi usage is relative new. It is demanding in a very good runtime performance with well defined isolated and secured data. There are some caveats:
⚠ Monitoring events, ids, may not be mixed with changing access rights.
⚠ Limited insight at security design. Insight on granted rights is done.
It is called
Security information and event management (SIEM)
is a subsection within the field of computer security, where software products and services combine security information management (SIM) and security event management (SEM). They provide real-time analysis of security alerts generated by applications and network hardware.
Vendors sell SIEM as software, as appliances, or as managed services; these products are also used to log security data and generate reports for compliance purposes.
Using BI analytics for capacity and system performance.
This technical environment of bi usage is relative old optimizing the technical system performing better. Defining containers for processes and implementing a security design.
⚠ Monitoring systems for performance is bypassed when the cost is felt too high.
⚠ Defining and implementing an usable agile security design is hard work.
⚠ Getting the security model and monitoring for security purposes is a new challenge.
It is part of ITSM (IT Service maangemetn)
Capacity management´s
primary goal is to ensure that information technology resources are right-sized to meet current and future business requirements in a cost-effective manner. One common interpretation of capacity management is described in the ITIL framework.
ITIL version 3 views capacity management as comprising three sub-processes: business capacity management, service capacity management, and component capacity management.
In the fields of information technology (IT) and systems management, IT operations analytics (ITOA) is an approach or method to retrieve, analyze, and report data for IT operations. ITOA may apply big data analytics to large datasets to produce business insights.
Loss of confidentiality. compromised information.
getting hacked having got compromised by whale phishing is getting a lot of attention.
A whaling attack, also known as whaling phishing or a whaling phishing attack, is a specific type of phishing attack that targets high-profile employees, such as the CEO or CFO, in order to steal sensitive information from a company.
In many whaling phishing attacks, the attacker's goal is to manipulate the victim into authorizing high-value wire transfers to the attacker.
Government Organisation Integrity.
Different responsible parties have their own opinion how conflicts about logging information should get solved.
🤔 Having information deleted permanent there is no way to recover when that decision is wrong.
🤔 The expectation it would be cheaper and having better quality is a promise without warrrants.
🤔 Having no alignment between the silo´s there is a question on the version of the truth.
RO-1.6 Defining what is learned for systems maturity
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⟲ RO-1.6.1 Info
The challenge in adults and continious learning
Individual learning k (Walter Smith book review 1987 )
The concept of learning style and its subsequent utilization in learning programs has grown out of the realization that traditional group instruction methods are not adequate for modern education systems. With new technologies rapidly creating a labor market where there is virtually no unskilled labor, the traditional group instruction approach to learning, with its process of eliminating slower students, has been deemed totally inadequate (Knaak, 1983).
The Paradox, duality- dichotomy:
Adults need to be able to cope with and respond to diversity, contradictions, dilemmas, and paradoxes.
These are listed by Brundage and MacKeracher (1980) as the dynamic equilibrium between
- stability and change,
- exposure to threat of failure and loss of self-esteem,
- the threat of becoming overqualified for their current work or
- throwing their personal relationships out of balance,
- and the conflict between the need to be needed and need to learn independency.
While some stress is normal and necessary to stimulate challenge in the learning environment, it may also create anger and frustration.
Anger was alleviated in this project by explaining to the students that it was a normal part of the learning process and by helping each of them deal with it in their own way.
Affective Learing systems mapping (LI: walter Smit 2026)
Administrative learning systems set the stage for dynamic management.
Everyone was on the same page, and the page could be adapted to management needs.
In short, learning systems are people systems. The lay a foundation for continuous problem solving that is interconnected throughout the school or business.
Decision can be made at different levels so that the entire system flexes with smallest change.
The interesting part of this taxonomie is a 9 plane with each of the ceels mentions 9 items.
| Thinking | Enabling | Existential | Emergent |
| Proactive imagery | Generic Education learning | Organization Learning Systems | Systems Evaluation Learning systems |
| Proactive activity | Projects learning Systems | Programs Learning Systems | Administration Learning systems |
| Reactive knowledge | Visual Learning Systems | Language Learning Systems | Value learning systems |
butics
Removing certainty constraints blocking decisions
Affective Learning Systems
...
⟲ RO-1.6.2 Info
butics
⟲ RO-1.6.3 Info
butics
⟲ RO-1.6.4 Info
butics
RO-2 Anchorpoints for functional details at realisations
RO-2.1 Using standard patterns for component in lines
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RO-2.2 Performance of the processing for flow
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RO-2.3 Tradeoffs in achieving functionality vs safety
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RO-2.4 Understanding taxonomies - concepts - ontology
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⟲ RO-2.4.1 Info
Aligning Human relations into a Diamond model
A 4+2 model to acknowledge cultural distinctions
| Dimension | Focus | Governance Implication |
| | Internal (Governable) |
| 1 | Individualism vs. Collectivism | Self vs. group orientation | Balance team incentives between personal accountability and collective outcomes |
| 3 | Uncertainty Avoidance | Comfort with ambiguity | Adjust processes:
high avoidance ➡ clear rules
low avoidance ➡ flexible experimentation |
| 4 | Masculinity vs. Femininity | Competition vs. cooperation | Align leadership style:
assertive goal-driven vs. relational
quality of life emphasis |
| 5 | Long-Term vs. Short-Term Orientation | Future pragmatism vs. tradition/immediacy | Shape strategy
invest in innovation cycles vs. emphasize quick wins and heritage |
| | External (Contextual) |
| 0 | Power Distance | Acceptance of hierarchy | Account for structural limits
flat vs. hierarchical authority patterns in organizationss |
| 6 | Indulgence vs. Constraint | Freedom vs. restraint | Recognize societal norms
openness to leisure vs. strict codes of conducts |
This creates a 4+2 model: four internal drivers for operational culture, two external forces that shape the environment.
It distinguishes between what governance can actively modulate versus what governance must respect and adapt to. It also makes dashboards more actionable, since leaders can see which dimensions they can influence internally and which ones they must design around.
Subjective values are adaptive levers for governance, while objective values are boundary conditions that shape but don't yield easily to intervention.
Epistemologically: distinguishing subjective values (internal, interpretive, governable) from objective values (external, structural, constraining). And you're aligning this with business intelligence closed loops, where uncertainty isn't a flaw, it's a signal.
- Internal dimensions are adaptive levers:
they can be shifted through governance, knowledge sharing, and team design.
- These are subjective values.
- The only execption is the operational functional product-service flow that is objective traceable.
- External dimensions are boundary conditions:
they set the cultural context but are harder to change directly.
These act like "environmental constraints" in the systems framing.
- These are objective values.
- The only execption is the operational functional product-service flow that is subjective.
Uncertainty Avoidance, in particular, becomes a governance dial: high avoidance ➡ tight loops, low tolerance for ambiguity; low avoidance ➡ open loops, exploratory learning
| Dimension | Focus | Governance Implication |
| | Subjective |
| 1 | Individualism vs. Collectivism | Align incentives and team structures | Reveals motivational asymmetries in decision loops |
| 3 | Uncertainty Avoidance | Design process flexibility and risk tolerance | Injects adaptive tension into closed loops , uncertainty becomes a learning input |
| 4 | Masculinity vs. Femininity | Shape leadership tone and performance metrics | Surfaces value conflicts in goal-setting and feedback |
| 5 | Long-Term vs. Short-Term Orientation | Set strategic horizons and innovation cadence | Modulates loop frequency and depth of insight capture> | >
| | Objective |
| 0 | Power Distance | Respect structural hierarchy and authority norms | Defines access boundaries and escalation paths in BI systems |
| 6 | Indulgence vs. Constraint | Acknowledge societal norms and behavioral latitude | Frames behavioral data interpretation and ethical thresholds |
Subjective values: Internally held, interpretive, and governable through dialogue, incentives, and learning. They vary across individuals and can be shifted through team dynamics and feedback loops.
Subjective values are loop-sensitive: they affect how feedback is interpreted, how decisions are made, and how learning occurs.
Objective values: Structurally embedded, externally imposed, and less governable. They reflect societal norms, institutional structures, or inherited constraints that shape behavior but resist direct modulation.
Objective values are loop-bounding: they define what feedback is allowed, who can act on it, and what constraints shape the loop's operation.
Uncertainty Avoidance, in particular, becomes a governance dial, high avoidance leads to tight loops with low tolerance for ambiguity; low avoidance supports open loops and exploratory learning.
| Loop Stage | Subjective Values Influence | Objective Values Constraint |
| Data Capture | Individualism vs. Collectivism: shapes what data is noticed (self vs. group signals). | Power Distance: defines who is allowed to collect or access data. |
| Interpretation | Uncertainty Avoidance: governs tolerance for ambiguity in analysis. | Indulgence vs. Constraint: frames acceptable narratives (open vs. restrained meaning). |
| Decision | Masculinity vs. Femininity: biases toward competitive vs. cooperative choices. | Power Distance: constrains who has authority to decide. |
| Action | Long- vs. Short-Term Orientation: sets horizon for implementation (quick wins vs. long cycles). | Indulgence vs. Constraint: limits behavioral latitude in execution.> |
| Feedback | All subjective values: modulate how lessons are internalized and adapted. | Objective values: bound how feedback can be expressed or escalated. |
In BI loops, uncertainty isn't noise , it's the adaptive signal.
High Uncertainty Avoidance ➡ closed loops tighten, feedback is filtered, risk is minimized.
Low Uncertainty Avoidance ➡ loops stay open, feedback is exploratory, innovation thrives.
Thus, uncertainty avoidance is the governance dial that determines whether loops become rigid control systems or adaptive learning systems.
RO-2.5 Understanding temporal boundaries dependencies
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⟲ RO-2.5.1 Info
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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.
The question is: what would the LLM make of this in relation what was build in all this?
You moved these on the vertical axis and leaving some of it open, from:
- C6 shift + P3 process directionality (dynamic change within a system)
- C6 shift Suggests movement, Implies agency, Fits horizontal or diagonal exploration.
- P3 directionality Presumes intention, sssumes steering is possible, belongs to within-system navigation
into:
- C5 dependency + P2 process phases (structural binding and temporal sequencing)
- C5 dependency suggests asymmetry, introduces non-reversibility, explains why vertical crossing is cost
- P2 process phases, describes sequence without agency, you cannot skip phases, time becomes structural, not managerial.
"You don't move up or down because you want to you move because the phase has changed."
That is not cosmetic, it changes the ontology of the diagram.
The Vertical ⇅Â movement, the vertical = binding / constraint / irreversibility.
Because now the center is not: a decision point, a coordination node, a synthesis, it is a collision point that makes the center a half-point, not a hub, between:
- horizontal sense-making (relations, processes, timing)
- vertical binding (dependency, phase, legitimacy)
Open vertical lines now signal:
- No predefined path upward or downward
- No guaranteed integration
- No designed transition
Vertical movement now represents:
- role-to-responsibility shifts
- private-to-public exposure
- learning-to-governance crossings
Those cannot be closed without ideology.
Do not read vertical movement as: maturity, progress, evolution.
It is better read as: exposure, binding, loss of optionality.
You can read the diagram as two orthogonal perspectives:
- Open horizontal lines = execution / what is changing
Horizontally, the model shows: process phases, coordination, "rhythm, pacing, interruption, stabilization," mutual influence in action.
This is the perspective of: work being done, systems being run, change being implemented.
It answers: "What is happening now, and what changes next?"
This perspective assumes motion is possible.
- Open horizontal lines says execution never closes: processes adapt, workarounds emerge, systems are always unfinished.
Closing the horizontal would imply perfect control.
- Open vertical lines = ideology / how change is justified and bounded
Vertically, the model shows: dependency, breakdown / negation, reorganization, emergence, "limits, containment, authority"
This is the perspective of: justification, legitimacy, values and worldviews, what kind of system is this?".
It answers: "Why is this change allowed, resisted, or required?"
This perspective assumes motion is constrained.
- Open vertical lines says ideology never closes: legitimacy is contested, values drift, authority must be renewed.
Closing the vertical would imply final truth or total governance.
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.
RO-2.6 Understanding for what drives systems maturity
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RO-3 Impacts consequences for functional details at realisations
RO-3.1 Analytics reporting.
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RO-3.2 The goal of BI Analytics.
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RO-3.3 Preparing data for BI Analtyics.
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RO-3.4 EDW performance challenges.
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RO-3.5 Omissions in BI, Analytics reporting.
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⚠ RO-3.5.1 ETL ELT - No Transformation.
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RO-3.6 .....Omissions in BI, Analytics reporting.
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