Systems thinking vs complexity theory (or why building a strategy could be the wrong thing to do)

Are these two sides of the same coin or a completely different approach

There are literally thousands of books and pieces of research into this area so I am only going to be able to make a relatively small ripple

Why is there so much research? Because the world we are living in is seemingly getting more and more “complex” (or even chaotic) which in turn makes it harder to manage. So making sense of a “system” to make it less complex is a natural order

I start with one of my most favourite of quotes and authors in this space:”Complex does not mean it is complicated” – from Eric Berlow (Eric Berlow: Simplifying complexity).  Berlow demonstrates through actual use cases that when you look at some systems map they do look very complex but if you can break then down they become less complicated and hence easier to understand and diagnose.

Another model I particularly like is the one authored by Dave Snowden ( of  Bangor University:

Snowden created the The Cynefin Framework (Cynefin meaning “habitat” in Welsh) whilst working at IBM.  The full research can be found here (

All too often a management theory is the following (and I have regularly used it..)

– Define the current state

– Define the target state

– Create a migration/transformation plan to get there (based on the target state)

This is the essence of a systems theory.

The Cynefin  framework starts off with the premise:  “How do you work from where you are, not where you would like to be?  This is quite a subtle difference

Cynefin has four domains and a centre of “disorder”.  The domain names have changed a little over time but the key to each is they offer a sense to analyse and behave.  There are two dimensions of ordered and un-ordered – the difference being ordered is where cause and effect can be discovered whereas in unordered,  cause and effect can only be deduced from hindsight or not at all

The domains are

Simple – these are the known/knowns. There are rules (best practice in place) and it is stable. One of the big dangers of this domain is over-simplifying

Complicated – known unknowns – cause and effect requires analysis and expertise. It is possible to work rationally towards a good decision. This is where engineers, surgeons, academics (and in our 21st Century – Machine Learning/AI)  etc apply their expertise

Complex- these are unknown unknowns (cue the Donald Rumsfeld quote ( There are no right answers and cause and effect can only be retrospective. Battlefields, corporate cultures are complex systems  as the very actions that change the situation create unpredictable outcomes

Chaotic– cause and effect is unclear.  In this domain, searching for the right answer could be pointless because there are no manageable patterns  The job of a leader in this domain is not to discover patterns but to establish some form of order and sense which elements are stable (if any). Top down communications is critical

Disorder/confusion – this is in the centre as this is when there is no clarity about which of the domains to apply. Multiple perspectives will apply, leaders will argue and cacophony rules. The only way out of this domain is to break down the situation and assign each to its relevant domains.

Moving through the domains – as knowledge increases there is a clockwise drift – from chaotics, through complex and complicated into simple.   There is the opposite movement as well of course as generations question the rules and knowledge is forgotten


So we now have a framework to help answer the original question

Lets start with Systems Thinking.

Systems Thinking is an holistic approach that focused on the each of the constituent parts of a system and how they inter-relate.  By assessing the number of components and the number of interactions – this determines the level of complexity.  The term has been defined and redefined in many different ways since its coining by Barry Richmond in 1987.  In doing my own research, ironically the definition and use of Systems Thinking has been complex in its own right and despite a lot of knowledge to move into complicated or simple domain – I haven’t found that to be the case. Systems thinking is centred around having a goal. What systems thinking shouldn’t do is create a reductionist process – as these are unable to fully allow deeper understanding. By using a goal, the ideal end state is defined and the process is all around how to close the gap

Complexity systems  uses the concept of stepping stones because when you start on a journey you don’t know what you are going to discover and having an explicit goal you could miss the very things you need to discover.  We don’t see what we don’t expect to see. Lewis Caroll , in Alice in Wonderland made this come to life:

– “Cat: Where are you going?
– Alice: Which way should I go?
– Cat: That depends on where you are going.
– Alice: I don’t know.
– Cat: Then it doesn’t matter which way you go.”

In order for complexity theory to work it will have a natural iterative effect that is learning and will focus on the interactions with each relevant component. Circling back round to the Cynefin structure, the holistic approach is to identify the domain/domains that is being reviewed and to use the relevant technique to move it away from a chaotic/complex to a more traceable cause and effect process. From a chaos theory perspective my favourite  is the butterfly effect which determines that from a very very small cause (the flapping of a butterfly wing) can create a significant effect (a tornado).    Not all the hardest problems are complex and the key is to structure them as efficiently as possible. It if remains complex or even chaotic, it means that defining the target state is not going to help and more likely


Systems Thinking and Complexity Theory are both attempting to make the leadership and management of actionable problems work as efficiently to the best target state possible.  Holistically they do have two different approaches. Both work left to right but critically Systems thinking will define at the  very start a target solution and therefore assesses each component, their interactions and the process to achieve the target state.  Conversely, Complexity theories (such as Cynefin) is focusing on categorising the problem space (domain) so the right technique is used in the right context,  and most significantly states the emphasis should be on understanding the current rather than target state and take each step as it comes. Of course, the reason for this approach is because of the complexity. If it was a simple problem, the target could be mapped out, the process clearly defined and each step would enable successful completion more of a reality.

I like the Complexity theory as it also plays to the corporate anti-pattern of needing a big strategy, misson statement etc . As Simon Wardley plays out  (, understand your landscape before you start..otherwise all you need is an automated strategy builder (







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