Information Processing - Systems thinking (IV)

We are evolving into the information age but have a lot of challenges to understand in what it is about in information systems. Systems thinking: understanding the information system as a whole gives a structure to adapt to changing environment changing conditions the information system as a whole.

What is required at all systems:

1. Does the system do what it is intended to do?
2. Will the system sustain by robustness?
3. Does the system adapt to effectiveness? .. not only in terms of financial resources, but also human resources, energy resources, environmental resources, etc.
4. How are unintended actions, side effects, and consequences minimized?

There was once upon a time a start to do an scientifical approach for understanding complex systems. The abstraction level is on more of that of all of the science areas. The logical complex systems, interactions to social systems, did not get the traction that the physical complex systems (robotics) have.

Operations research attempts to provide those who manage organized systems with an objective and quantitative basis for decision; it is normally carried out by teams of scientists and engineers drawn from a variety of disciplines. Thus, operations research is not a science itself but rather the application of science to the solution of managerial and administrative problems, and it focuses on the performance of organized systems taken as a whole rather than on their parts taken separately.

What goal to Optimize: decrease of entropy in a purpose

In the context of information processing we have several options in optimizing. The usual dictated goal for optimisation is: financial driven. Financial driven goals are hampered for a limited valid time in the future. Other values of the purpose, eg being a part of a social system, are too often neglected.

• Information is something that is subject to entropy. It can be chaotic, not describable what may be relevant and structured with a value that still needs to be understood.information is something that is subject to entropy.
• Changing the goal in information processing in decreasing the entropy, chaotic meaningless, into well structured meaningful is a different perception of optimisation.

For optimisation the argument that always is coming back is removing constraints decreasing waste is the key in a mindset for well determined choices for actions. The question is getting the answers in what well determined actions and their results and impact are.

A perception change is decreasing entropy is the way for higher maturity levels.

A generic structure for between demand and delivery of change.

All organisations are unique in the same way as all humans are unique. The change in perception for a purpose is a difficult one. The need is unlearning the financial profit as goal but seeing that as a resource for enabling a purpose. Changing a perception is difficult and is not without risks. There could be a pathway to something new or it could be a harming impact. How would a model for a generic organisation interactions system look like?

Only having the focus for what done by technology is the "DevOps" doublet. The first mindset change is a switch that in information processing it is not only about technology.

1. The well known "DevOps" doublet is an enabler for the organisational purpose
2. A doublet "PortfolioPlan" is the enabler for "DevOps"

This would be too simple if that was all. There is not a supply nor supplier chain mentioned. These are the perception for results for the buyer and the acquirement of resources, materials.

1. There is a "Pro-visonBuyer" doublet for the intended deliveries.
2. A "MotiveAssets" doublet for enabling the deliveries

These four doublets are part of the four layers of the 3d model describing an organisation. They are fractal in the system and a system on their own.

The question in this: how to manage the knowledge for a start and result of all those relevant interactions? A framework and the support by real products for that is the "Jabes" proposal.

Using knowledge at changes, for changes

Managing a system is very difficult by all of what is assumed, missing ambiguous or even what has been wrong stated. Extending and using the Viable system theory there is a lot possible to classify in different levels in fractals. This is not exactly the same as reducing a complex system in components that are smaller but there is a shift in the context for goals in why what how.

Any system can be evaluated for extending to a macro-level (more complex systems) or decomposing it into simpler micro-levels (components).

To understand what is going on in complex systems we should go back how we learn to manage those complex systems. That order is not the logical order in learning how to use complex systems.

1. In an educational approach we learn about he theory of the technology for platforms.
2. When the basic principles of technology in platforms is understood by education there is a switch made in personal preferences: a/ for how to use them, b/ how to improve them, c/ paths for creating new platforms and d/ manage the persons for activities at those .
3. The purpose of a complex system arise from what is needed in a social community and/or what someone sees as an opportunity in a system of what he is part of.

More content (external)

There is a long brain dump for this, an adjusted Zachman structure as the whole. It is not the result what is the most important of that but the journey what resulted into to result. Elucidation https://metier.jakarman.nlman.nl/