Dave Snowden

Cynefin dynamics

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Screen Shot 2015-07-03 at 02.19.53.png In yesterday’s post I looked at my decision to use constraints in the definition of the main Cynefin domains. I talked about those in the content of explains dynamics, the shifts between domains which are as if not more important than the domains. In Complex Acts of Knowing I used various dynamics to handle the instantiation of an informal community as official in the context of need and as a means of understanding when to use (the then popular) Communities of Practice or Intranets. Later in New Dynamics of Strategy Cynthia and I indulged ourselves over several conversations creating multiple dynamics. Later I focused back to the original three KM dynamics (albeit in a wider context) and more recently I have started to use what I call the Grazing Dynamic; a representation of near continuous change with little stabilisation.

Critical to this is the difference between enabling and governing constraints. Yesterday I used the endoskeleton v exoskeleton metaphor to explain that. For a more practical example think of heuristics and rules. Rules are governing constraints, they set limits to action, they contain all possible instances of action. In contrast heuristics are enabling constraints, they provide measurable guidance which can adapt to the unknowable unknowns. So to take the US Marines example: when the battlefield plan breaks down then Capture the high ground, stay in touch, keep moving. It is always worth reminding people that a heuristic is not a principle. Many actions can be justified by interpreting a principle, but a heuristic allows you to measure absolutely if you have compliance.

So given that lets look at the dynamics:

  • BLUE
    The most stable dynamic is shown in blue and moves between the complex and the complicated domains. So ideas emerge in the complex domain within enabling constraints. Then either naturally or by the use of safe-to-fail experiments we see if we can create repeatable outcomes by increasing the constraints. If that works we have moved to complicated and we can focus on exploitation. However we must not be complacent, we monitor for non-repeatability and if it happens then we move back to complex. Understanding the natural cadence between the two is critical to strategy and operations alike. It will be a short timescale in retail, a longer one in in manufacturing and so on.
    If you fail to maintain that dynamic then the situation may start to over stabilise and not respond well as circumstances change, but its too late simply to shift back to safe-to-fail experiments. This is the yellow dynamic, a shallow dive into chaos; breaking up established practice to allow novel practice to emerge and reset the system to allow a new stable dynamic to emerge.
    Only a small percentage of things will fall into the obvious. They only go there when practice is stable, rarely ever challenged and heavily exploitable. In those circumstances we settle on one day of doing things and we enforce that in all bar exceptional circumstances. To be clear this does not mean it is not valuable, it may be the single most valuable aspect of an organisation. No domain is better or worse than any other, all are contextual.
    The new grazing dynamic, in which the overall volatility is such that stability is rarely other than transitionary and we constantly skim the surface of chaos (so much better a phase than the edge of chaos). This is increasingly common in public health, consumer goods, social computing and elsewhere. It requires a very different approach to management, one that goes beyond safe-to-fail experiments. Interventions are small, faster with real time feedback loops and more distributed in nature. Expect more on this in the future.

So by explaining those shifts in the context of changing constraints I avoided associations with hierarchy that people (wrongly) read into the tetrahedrons. It also opened up other possibilities to make operation in each domain and between domains simpler. More on that in future posts.