The evolution of Cynefin [Snowden, Corrigan]

I first learned about Dave Snowden’s Cynefin model in a Lean-Kanban conference circa 2015–16 and have made references to it in a handful of blog posts in the past [1, 2]. 

It first received broad recognition in a 2007 HBR piece titled A Leader’s Framework for Decision Making. On March 1 (St. David’s Day) 2019, Snowden took it upon himself to write a series of blog posts (5 in total) covering updates to the model, and in this year’s St. David’s Day, he decided to turn it into an annual ritual. 

Cynefin St David’s Day 2020 (1 of 5)

Chris Corrigan took it upon himself to aggregate the model and the key changes here:

A tour around the latest Cynefin iteration

And I am going to attempt to distill it even further. This is going to be a challenging post to write and I know the end product is not going to be great. Both because the subject matter is difficult, and because I have yet to have mastered the framework. But that’s exactly the point of writing about it…

First, a quick orientation: the Cynefin model is designed to aid decision-making and inform actions, recognizing that the decision-making process leading to the best action is different based on the context (domain) — the environment/situation — in which the action needs to be taken. 

 The model discerns between 5 different domains, the two on the right (Clear, Complicated) are “ordered” domains where the environment is mostly knowable and predictable and problems are solvable. The distinction between those two domains is more nuanced and is a factor of the number of parts in the system/situation. The higher the number, we’re going deeper into the Complicated domain and the level of expertise required to know the right answer increases. 

The two on the left (Complex, Chaotic) are “unordered” domains where the environment is mostly unknowable and unpredictable. In the Complex domain phenomena such as emergence and self-organization exist but those are enabled by some constrains. In the complex domain, there are no meaningful constraints leading to semi-random behavior. 

Going counter-clockwise (Clear -> Complicated -> Complex -> Chaotic) there are fewer constraints and therefore the more unordered and unstable the situation becomes. Going clockwise, there are more constraints on the situation and it becomes more ordered and stable. 

In the middle is the Confusion domain, broken down to “Aporetic” (“at a loss”) where the confusion is unresolved or paradoxical, and “Confused” where we just haven’t fully understood the situation yet — a more temporal state. 

I’m going to keep the green sections indicating liminality out of the scope of this post for the time being. 

Putting the framework to action

Almost any situation that requires a response has multiple aspects, each mapping to a domain. 

Step 1 is decomposing the situation to its various aspects. 

Step 2 is mapping each aspect to its respective domain: 

  • A clear and obvious aspect where things are tightly connected and there is a best practice → Clear
  • An aspect with a knowable answer or a solution, which has an endpoint, but requires an expert to solve it for you → Complicated.
  • An aspect with many different possible approaches, and uncertainty around which is going to work → Complex.
  • An aspect that is a total crisis, which completely overwhelms you → Chaotic.
  • Aspects whose domain is still unclear should be left in the middle, “Confused” domain. 

Step 3 is applying the appropriate approach to the aspects in each domain: 

  • Clear (Sense → Categorize → Response): just do them.
  • Complicated (Sense → Analyze → Response): research using literature and experts, make a plan, and execute.
  • Complex (Probe → Sense → Respond): get a sense of the possibilities, try something, and watch what happens. As you learn things, document practices and principles that guide in making decisions. If rules are too tight, loosen them. If rules are too loose, tighten them. 
  • Chaotic (Act → Sense → Respond): apply constraints quickly and maintain them until the situation stabilizes. 
  • Confusion: monitor those aspects and re-evaluate as new information becomes available and may help classify them into the appropriate domain. 

Key changes in the framework 

  • Renaming the first domain as “Clear” instead of “Simple” (or “Obvious”)
  • Highlighting the roles that constraints play in each of the domains: fixed constrains (Clear), governing constraints (Complicated), enabling constraints (Complex), no constraints (Chaotic). 
  • Renaming the middle domain to “Confusion” (from “Disordered”) and decomposing it to: “Aporetic” and “Confused”. 
  • Adding liminal boundaries around the Complex domain. 
  • Adding approach “labels” in addition to approach sequences: best practice (Clear), good practice (Complicated), exaptive discovery (Complex), novelty under stress (Chaotic). 
The evolution of Cynefin [Snowden, Corrigan]

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