Mainfram Reality

Organisations have traditionally been treated as complex machines.  Theories and approaches employed for changing organisations were concerned with mechanical or technical solutions.  What is worse, with capability based planning we are now treating organisations as military capabilities. Examples of classical change solutions include improving performance by changing technology used, training people, etc…  All this makes sense as long as you hold a firm belief that an organisation is a machine.  Well organisation are systems and so are machines, but organisation are primarily complex social systems and secondarily technical systems.

The image below shows a model for changing organisations, it is what I currently consider my ideal design for changing socio-technical systems.  It is primarily based on work done at MIT by both System Design and Management Group and MIT Sloan School of Management.   The big influence on my point of view below are Peter Senge (named strategist of the century for his work on learning organisations at MIT) and Russell L. Ackoff professor at Wharton School (one of the pioneers in operations research and management science, idealised design and interactive planning pioneer).

Idealised Design – Changing Socio Technical Systems

Events
Events are seen parts of the socio-technical system under study. Changes done at Events level are reactive and are short lasting. There is no optimisation, at this level, only day by day reactions to the events generated by the socio-technical systems. Many complex organisations have departments that operate by responding to events, since they are in many cases devoid from understanding of the organisational strategy.

Patterns
At some point the management of an organisation realises that there are certain patterns that explain the events over time. This is the beginning of an analytical view of an organisation. By understanding patterns management can perform predictive changes but lack the overall system view and can therefore sub-optimise parts of the organisation by simply managing patterns of events over time. This is better then fully reactive management but falls short in understanding the full socio-technical system being managed.

Structures
The event patterns are driven fundamentally by structures that make up the enterprise. Structures like business processes, organisation structure, information systems, etc. This is where Enterprise Architecture as a discipline ends. From events through patterns and structures, enterprise architecture is well equipped to deal with changes in these realms. However, enterprise is a socio-technical system, most of the leverage for change so far is technical, but enterprises are more social then technical, therefore for true transformation, enterprise architecture is anti-systemic.

Mind Models
Mind models describe what and how thinking allows the structures to persist. If a change initiative changes the fundamental structure of a business process, of organisation itself or introduces a new set of information systems without addressing the thinking behind the previous architecture, the change effort will generally fail. By changing the thinking of people participating in the socio-technical system, a large leverage can be achieved to perform long lasting changes. Mind models are the core of social systems, mind models are the fundamental building blocks of enterprise architecture not processes or information systems. Enterprise architecture discipline has not addressed this aspect of the enterprise, which change management discipline has addressed it without the rigor applied to structures, patterns and events.

Vision
Changing vision is the deepest and highest leverage that can be applied in order to change an organisation. Entire enterprises can be re-built by changing the vision and following through the stack up to the events. Vision is what shapes the mind models of people working with an enterprise. It is also the hardest part of the enterprise to change and requires much more work and dedication then changing other aspects.

Conclusion
The mind model I am proposing here is one of “Systems Thinking”, understanding of the whole of enterprise, not just parts and not broken down into disciplines. And most of all, dealing with people not as machines but complex social systems. There is not equilibrium to be found, social systems are adaptive and purposeful and as such must constantly change to survive.

Without a doubt one of the most overloaded words in use today is a word “system”.   The free dictionary entry on word “system” best illustrates this point.   The definition I have become most comfortable with is the following:

A system is an entity which maintains its existence through the mutual interaction of its parts.

The mutual interaction of system parts differentiate the system from a collection, where parts are merely assembled and do not peruse common goals.   System parts do not interact in a simple cause and effect manner, but form a greater hole.  Another way of looking at it is to understand that systems are purposeful.

So in addition to the definition above the system can be categorized as having following properties (taken from work of Dr Russell L Ackoff):

1. A system (a whole) has one or more defining properties or functions
2. Each part of the system can effect the behavior or properties of the whole
3. There is a subset of parts that is sufficient in one or more environments for carrying out the defining function of the whole; each of these parts is necessary but insufficient for carrying out this defining function.
4. The way that each essential part of a system affects its behavior properties depends at least one other essential part of the system.
5. The effect of any subset of essential parts of the system as a whole depends on the behavior of at least one other such subset.

One of the most important implications of thinking of systems in this way is that…

A system is a whole that cannot be divided into independent parts without loss of its essential properties or functions.

Thinking in Systems by Donella Meadows is a great introduction into systems.

For more information about systems, a Wikipedia entry on System is a great starting point.  Study of systems is a complex subject but one essential to pretty much every field of study.