The Origins of Cynefin - Part 3

July 9, 2010

I have resolved to complete this history over the next couple of days. In part 1 I took the history from its origins in my reflection on Boisot's I-Space, to a quadrant model contrasting abstraction with learning/culture. In part 2 I moved on to describe a planar model which incorporated complexity and catastrophe theory. These essence of that second model was the realisation that I was talking about the nature of systems (i.e. ontology) not simply a model to understand knowledge flows and that as such the model had more general applicability. My own background was in decision support systems; I designed and built such systems for the Guinness Group, Mersk Shopping, Tootal Group and the Vesty family during my programming/design days in Datasolve using FCS-EPS which was a programming language ahead of its time; sentimental moment there.

I had come to knowledge management from decision theory and strategy. One of the basic models I developed back in those dates (Datasolve had now merged with Software Sciences to create DataSciences) is shown above and just for the record this was back in the mid nineties and yes I did shown the model in Washington before and after 911. Basically the model contrasts certainty of decision making and our level of certainty in our understanding of the situation. If we are confident in both the we are dealing with the known knowns. If we know the situation but we are not sure of the consequences of our decisions then we are dealing with the known unknowns. If we are pretty certain our decisions will do no harm (an early expression of safe-fail experiments) and will help us understand what is possible then we are dealing with the unknown knowns. Then of course we have the really interesting area, both for threat and opportunity, where, when it comes down to we have no idea what is going on or what we should do.

Now I got more and more interested in the unknown unknowns and started to play with another matrix (I hadn't yet worked on the detox programme to stop using two by twos, but in fairness I was not long out of an MBA and knew no better). I can't remember the exact details so I may have this wrong (if any reader our there has an original please let me know) but have done my best to reproduce it here. The key thing is not the content of the boxes, which never really worked, but the introduction of a distinction between known, knowable and unknowable.

Now remember that the Cynefin model was, it is early days a knowledge management model. So the distinction between known and knowable was attractive. In parallel with this I was writing a chapter for Knowledge Horizons on the social ecology of knowledge management. That was still using the learning quadrant model and used movements between the quadrants to identify different culture types in organisations. Rereading it for this posting I can see it was an early phase of what became Cynefin Dynamics and has some potential for development. The quadrant model was, and remains a learning model and it this emphasises the role of language (which was also the inheritance of Boisot). For that chapter I took the uncertainty matrix (my name for the model that starts this post) and translated it into a matrix that balanced capability with objectives. This model shows a nascent version of the current version of Cynefin.

This is a pragmatic model, and tries to get people into the idea that they capabilities and objectives may not match up, along with the idea that informal networks and communities may provide a new way of handling uncertainty. It also contains what became a key feature of later writing, namely the a priori limitation of what expert knowledge can achieve. It put me at odds with a lot of the dominant thinking within knowledge management at the time which emphasised collecting experts in communities of practice.

So all of this stuff was swilling about in my mind and then one day (I think at Warwick University) it all came together and I drew the basic Cynefin shapes of four curved lines with the squiggle at the bottom. In effect I too the planar shape of part two, mixed it up with the various matrix models and created something very different with far more potential.   

There is one more element needed to complete the picture. By now I was in IBM and various attempts were being made to match what I did with others The problem here is that thought leaders don't really mix well; each have their own ideas and they are reluctant to accept challenge (this is commentary and confession by the way). In a meeting at the Hawthorn Labs I was introduced to Stephen Haeckel whose Adaptive Enterprise, creating and leading the sense-and respond organizations had created a following within IBM. Now we had an interesting debate, and as I remember it Cynthia's then managers were present. I liked Stephen (and still like although I have not seen him in years) but we had some significant disagreements. Well I did, Stephen could not see why I was drawing a distinction between knowable and unknowable systems. I realise now was a debate that would happen again and again, between a proponent of complexity and someone writing and thinking in the tradition of systems dynamics. For Stephen it was sense-respond with an underlying assumption that it was possible to manage an organisation on that basis. For me it was just a marginal improvement on the process engineering that dominated that period, and it wasn't radical enough.

Eventually, frustrated and drew the Cynefin model on the wall and created for the first time the four decision models:

  • Known: Sense-categorise-respond
  • Knowable: Sense-analyise-respond
  • Unknowable, complex: probe-sense-respond
  • Unknowable, chaotic: act-sense-respond

My point was that Stephen's model would only work in the known or the knowable, and he was assuming an analytical and model based approach would allow the sense-respond organisation to be built, it was an engineering approach in contrast with my ecological one. It was an important step, but more was to follow. But that is for tomorro

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