👐    metier   👐    design: bpm    sdlc    bianl    sense    data    meta    math    👐    devops: bpm    sdlc    bianl    sense    data    meta    math 👐
👐    intro    Evolve     oneoff    optindus    devtst    infl20_1    changedev    infl20_2    dev-aiml    review    👐    top bottom   👐

Process engineering - operations research - Machine learning


Historical developments - (design bpm)

Evolution change, documenting

rethink what has happened TN To get know what has happened looking into archives is a starting point.
Connect that to what is happening so you can understand the why.

🔰 the most logical begin anchor.


Progress


Contents

Reference Topic Squad
Intro Evolution change, documenting 01.01
Evolve What is changing, just thinking 02.01
Origin of computerization 02.02
oneoff One off proces, immediate running (business proces) 03.01
optindus optimalization industrial era (I) 04.01
devtst Develop & Test, POC, before running (business proces) 05.01
infl20_1 optimalization 20-th century (II) 06.01
Changing the world (a) 07.01
changedev Change of human influance inventing a proces 08.00
Fully human, immediate impact (I) 08.01
Delegated but human, validation before change (II) 08.02
Computer aided decision making, validation before change (III) 08.03
infl20_2 optimalization 20-th century (III) 09.01
dev-aiml Machine supported Develop & Test, POC, Run 10.01
Changing the world (b) 11.01
review Review of my thoughts 12.01

What is changing, just thinking

The ICT is transforming into using more ML (Machine Learning), a subarea of AI (Artifical Intelligence). The proces how to implement that is not settled yet.

A personal figure is of a ML proces (develop & operations):
BPM AI ML proces
It looks very complicated tyring to show the development and operational proces. I will have to explain the steps that have led to this. This figure doesn´t cover the several stages that are present at development / test at the left side.

Origin of computerization

We are presuming using computers, machines is of very recent years. That assupmtion is not correct.
Jacuard_loom
Optimization of the work force started with the industrialisation.

Programming machines saving on costly hard manual work. The jacuard loom (wikipedia) was the first example.

With this in mind a lot has changed nobody these days is worried about.

One off proces, immediate running (business proces)

Before ICT was common al lot of processes have been executed. They delivered sometimes marvelous wonders like the egyptian pyramids (physical buildings).
A personal figure is of a classic one-off proces ( just operations):
one off proces, immediate running
As one-off nu proof of concept, no development and testing is done. Only knowledge and experience, experiences handed over by teachers.

There are four basic components in every proces, these are:

Applicable situations for an one-off
Apllo project, man to the moon There are a many situations that this is the best approach. Not all projects are clearly one-offs.
In the Apollo project everyting was tested and validated. Only the unforeseen being a problem.

optimalization industrial era (I)

Winsor Taylor Taylor (wikipedia) Taylor's scientific management consisted of four principles:
  1. Replace rule-of-thumb work methods with methods based on a scientific study of the tasks.
  2. Scientifically select, train, and develop each employee rather than passively leaving them to train themselves.
  3. Provide "Detailed instruction and supervision of each worker in the performance of that worker´s discrete task" (Montgomery 1997: 250).
  4. Divide work nearly equally between managers and workers, so that the managers apply scientific management principles to planning the work and the workers actually perform the tasks.
Within the setting of a factory fully control of workers is possible. This rigid approach of seeing human workers as inhuman robots caused the aversion.


Henri Fayol Henri Fayol (wikipedia) While Fayol came up with his theories almost a century ago, many of his principles are still represented in contemporary management theories.
  1. Division of work = Different levels of expertise can be distinguished within the knowledge areas (from generalist to specialist).
  2. Authority = gives the management the right to give orders to the subordinates.
  3. Discipline = about obedience.
  4. Unity of command - Every employee should receive orders from only one superior or behalf of the superior.
  5. Subordination of Individual Interest = The interests of any one employee or group of employees should not take precedence over the interests of the organization as a whole.
  6. Remuneration = All Workers must be paid a fair wage for their services.
  7. Centralisation and decentralisation = Centralisation refers to the degree to which subordinates are involved in decision making.
  8. Scalar chain = The line of authority from top management to the lowest ranks represents the scalar chain.
  9. Order = There should be a specific place for every employee in an organization.
  10. Equity = Managers should be kind and fair to their subordinates.
  11. Stability of tenure of personnel = High employee turnover is inefficient.
  12. Initiative = Employees who are allowed to originate and carry out plans will exert high levels of effort
  13. Esprit de corps = Promoting team spirit will build harmony and unity within the organization.
Within the mining setting a self management responsible team is required, operating in an dangerous environment. There is no option for micro-management as the generals keeping away from the most dangerous locations.

Develop & Test, POC, Run (business proces)

ICT has for many years being operated in a proces model: human defined algorithms. In a develop test environment simulating the operation, no real information.
A personal figure is of a classic one-off proces ( develop, test - operations):
Develop & Test, POC, before running
There is a working group placed in the middle between the leaders (top strategy) and the workers (operations).

supporting changes

Apllo project, man to the moon
There are many companies offering an ITIL course. The idea is responding on an event that was not planned.
An Apollo 13 ITSM - game 💣 The goal is acting on incidents. Building and operating in a reliable predictable way is not covered.
Prioritizing would be better avoiding that proces as much as possible.

optimalization 20-th century (II)

Edwards_Deming W. Edwards Deming (wikipedia) The "Seven Deadly Diseases" include:
  1. Lack of constancy of purpose
  2. Emphasis on short-term profits
  3. Evaluation by performance, merit rating, or annual review of performance
  4. Mobility of management
  5. Running a company on visible figures alone
  6. Excessive medical costs
  7. Excessive costs of warranty, fueled by lawyers who work for contingency fees

pdca dmaic
PDCA (plan–do–check–act or plan–do–check–adjust) is an iterative four-step management method used in business for the control and continuous improvement of processes and products. It is also known as the Deming circle/cycle/wheel


Ford_Pocline
Henry Ford faster & cheaper facturing Assembly line (wikipedia)
1913 Experimenting with mounting body on Model T chassis. Ford tested various assembly methods to optimize the procedures before permanently installing the equipment.


Rik_Maes.jpg
Visie op informatie-management (AIM Amsterdam Infroamtion Model "Amsterdamse raamwerk voor informatiemanagement")
pdca dmaic Many see this as a static situation. Often only the strategic level is considered. Strategies are worthless untill they are adopted by tactical and operational level. The tactical level needs to define which projects are needed forthe strategy. On an operational level, the projects have to be implemented and included in daily operations. The tactical level sets goals and preconditions of the strategic domain into: concrete, realizable objectives, responsibilities, authorizations, frameworks, and guidelines for operations.


Changing the world (a)

ML_Agriculture
optimalization Agriculture
Food production and demand on a global basis, with special attention paid to the major producers, such as China, India, Brazil, the US and the EU.
Agricultural_science (wikipedia)

ML_smarthome.jpg
optimalization your home
A Smart Home is one that provides its home owners comfort, security, energy efficiency (low operating costs) and convenience at all times.

ML_logistic
optimalization transport
Logistics Transport (wikipedia)

Change of human influance inventing a proces


Change immediate human invented only

Fully human, immediate impact (I)

This is: changing in production.

That can be effectieve when the proces is new and nothing being replaced.

When something unexpected is happening, the delay in delivering as ususal, most nost be problematic.

Change human invented only algorihtmic

Delegated but human, validation before change (II)

This is: changing in planned journey´s.

The journey myst be clear. The differnces between the real operation in performance, date settings, connections must get managed.
Release mangement (DTAP) to be implemented.
When something unexpected is happening, fixing must be able bypassing changes already waiting.

Change with algorihtmic support human guidance

Computer aided decision making, validation before change (III)

Computer support defining logic, Machine Learning.

An evaluation loop on results, scores, score log, are actions during develop and operations.
Expect the model to behave different in time. Adaptive behavior can be a cause for decreasing results.


optimalization 20-th century (III)

Peter_Drucker Peter_Drucker (wikipedia) quotes:


Abraham Wald plane
Abraham Wald is seen is one of the founders of Operations research (wikipedia).

Wald noted that the study only considered the aircraft that had survived their missions—the bombers that had been shot down were not present for the damage assessment.

Wald proposed that the Navy instead reinforce the areas where the returning aircraft were unscathed, since those were the areas that, if hit, would cause the plane to be lost.

There are many caviats using Machine Learning. The bias data, the correct meaning data are some of them.
Understanding the uncertaintities, the effect on the whole process but being fair to outlayers are others among a long list.

Machine supported Develop & Test, POC, before running (business proces)

ICT has for many years being operated in a proces model: human defined algorithms. In a develop test environment simulating the operation, no real information.

The personal figure of using a Machine Learing proces ( develop, test - operations):
BPM one-off process
The big change is: the exchange using real documents and real information as input and generating logic. This approach is only possible with ICT. The special property is being able to make exact copies of operational versions.

More links associated - entry/exit
Is used at:
👓 threats for data & tools Proces Life Cycle.
Details to be found at:
👓 resulting Life Cycle ALM, business Life Cycle.
👓 Release management SDLC - release management.

Detailed topics are:

 
 

Changing the world (b)

ML_travel
optimalization personal travelling
Travelling (wikipedia)


ML_deepblue kasparov
optimalization decisions
Playing chess is making decisions in a timely manner. with the advice of a machine anyone can beat the master. Note the man behind the computerscreen, he is moving the pieces.


ML_health
optimalization Health
Health services research (wikipedia)

Review of my thoughts

SAS analytics lifecycle
Looking arround what others are posting and what the direction of the opinions is ....

The life cycle is becoming a hot topic (2019). Just modelling, inventing new processes and not able to operationalize doesn't bring the expected value. There are many more issues to solve than becoming aware of this.

(Picture snapped in a SAS presentation)

analyst viewpoint

Even the life ycle apporaoch is seen: Forrester Business Clear Implementation Cycle
Many companies still struggle to realize value from predictive analytics despite considerable investments in technology and human capital. This is largely due to the insights-to-action gap — the disconnect between analytical insights and operational processes Source: Close The Insights-To-Action Gap With A Clear Implementation Plan Forrester report (Brandon Purcell 2017)

🔰 the most logical begin anchor.



👐    intro    Evolve     oneoff    optindus    devtst    infl20_1    changedev    infl20_2    dev-aiml    review    👐    top bottom   👐
👐    metier   👐    design: bpm    sdlc    bianl    sense    data    meta    math    👐    devops: bpm    sdlc    bianl    sense    data    meta    math 👐

© 2012,2019 J.A.Karman