I’ve been developing a theory of constraints both as a method for strategy mapping and as a way of better understanding domains and sub-domains in Cynefin. That thinking was in part stimulus for the liminal version of Cynefin. I’ve used a base distinction of Fixed/Governing constraints for order and Enabling constraints for complex. The notion of Enabling constraints has been extensively elaborated by Alicia (and you still have a chance to make the Cynefin Retreat were she is part of the faculty). That set is fine to explain basic Cynefin but I was looking for a greater range of meaning that would also handle different aspects, or degree in each domain (in particular complex). At the same time I’ve been working on the full workflow for a complex systems approach to strategy and that requires some form of indirect mapping to avoid premature convergence; avoiding any hypothesis is key to sense-making and a part of that is getting people to look at the situation tangentially or abstractly before they form conclusions.
The typology of constraints I posted last December has survived the test of multiple presentations and discussions and has the advantage of combining the distinction between resilience and robustness which is critical to any understanding of strategy. I’m assuming familiarity with that earlier post so if you haven’t read it use the link. A search of this site on constraints will also give you over a hundred other posts on the subject, but they need to read in context of the dates they were written. There are a lot of posts on resilience and robustness as well but to save time I’ll quickly summarise how I use them:
Now having a double typology (containers or connectors; robust or resilient) will allow be to create more subtle definitions within the liminal version of Cynefin, possibly replacing the domain models (the three by three matrices for those familiar with the idea). I’ll build on that later in the week and also show what I think is the near final version of the liminal model which has changed a little since last week. For the moment I want to talk about a key starting point in situational assessment; the more accurately I can describe the current situation the better positioned I am to come up with a strategic focus which has some chance of success. The danger is that opinions about the future or the past fundamentally influence how people see the present and no exhortation for openness or objectivity will change that on a sustainable basis. As with most of my work I want to create systems that do not require high levels of sainthood to work. We need to work with what we have evolved to be, not what an idealistic facilitator would like us to be. That means working with cognitive bias rather than trying to pretend it doesn’t exist.
One key method for that is to start indirectly not directly, shifting to a level of abstraction in the complex-chaotic liminal domain of Cynefin. One way to do that is to start with a full mapping of the constraints in play, and a related mapping of the degree of controllability of said constraints. I’ve been using that approach in several sessions, a majority of which have been at C level, over the last few months and with some success. I start by giving the typology of constraints and then get groups to identify those in play at different levels. Ideally I’d do that with SenseMaker® on a distributed basis but it will work within workshops. Then we go through the following steps (this isn’t necessarily complete, a work in progress and I’m developing new control forms)
Ideally all such changes should take place within a fractal relationship, appropriate to context. By experimenting with such constraint changes we allow an emergent approach to strategy, reducing the risk of major shifts. As the experiments start to stabilise the liminal complex-complicated aspect of Cynefin comes into place before we scale.
Apologies as this is still a little cryptic, I’m making and sharing notes rather than codifying a comprehensive set of methods – that is coming.
So why the knots? More on that in my next post, The images are from Magda Indigo
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I was originally going to move on to post about constraints but a early meeting ...
Coming to the end of two weeks in New Zealand and I’ve been struck by ...
This approach seems to have legs! I can see it being useful in the behavioural approach we (Baltic Works Commission) are developing to environmental harm. Take the Baltic Sea – too much phosphorus from forestry/agriculture and sewage treatment. If you analyze the chain from the harm back through to its origins, and ask each human “why did you do that” you can see the constraints on their decision making and pu tit into the typology typology. This will inform and help come to a solution.
In this case you can also look at behaviour in this way “if X never Y then Z would never happen” If people never flushed their loos there would be no pollution the Baltic couldn’t handle. IT is VERY interesting to ask people why they flush their loos. I even know people who don’t but that is for another time. This eco-system of constraints and decision alternatives around loo flushing shows up some of the real problems of our time in terms of what an environmentally concerned citizen(agent) can and can’t do, political attitudes. It has nice scientific basis too, as the constraints are real if they affect people’s behaviour and can be mapped reliably.
That’s an interesting example. If we were to define the system as each person’s house or flat and told them that they had to deal with their own waste themselves it would make our cities almost unlivable fairly quickly. Public sewers are a way to make city living much cleaner, safer and better smelling. But, as you say, it transfers the problem elsewhere, in this case, the Baltic Sea.
Now, suppose the local government builds a Sewage Treatment Plant and requires each person to use the public sewer system. There is a capacity constraint on that treatment facility. That is a Fixed or Governing Constraint. But, no one is impacted by that constraint unless the population grows beyond the design capacity. Until that time, the requirement that everyone use the system is an Enabling Constraint. Individuals may not like it since it constrains their actions, but it improves the entire system.
Your chain of causality in which something X does impacts something Y does which impacts Z Is an example of the difficulty of trying to find one specific root cause. You can nearly always keep going back in time. That reminds of Carl Sagan’s quote:
If we want to talk about constraints and causality, we first have to be clear on the boundaries of the system we’re looking at. This is why we talk about the problem of scope creep when trying to solve problems. A workable solution to any type of problem will depend on matching the solution to the constraints within the boundaries of the system of interest.
Well, would our cities become unliveable? Think abundance here. Urine is a valuable fertiliser. Here in Sweden the municipal connection fee is at least $7000 and the annual charges $300. If this were no longer available a whole new market would open up. Indeed the legal demand on sewerage is a huge constraint of a rigid type.
If you admit it is a complex problem then the simple thing to do is announce the sewers are closing, give people their money back and encourage circle economy entrepreneurs to get at it. The market can solve the problem.
Sewers solve one problem but they create many more, including even driving antibiotic resistance. So I cannot call them enabling constraints. I think you’ll find there is a pipe lobby and chemical industry in there somewhere dressing their solution up as “enabling”
You miss the point on root cause. The idea of going back is not to find the root root cause only the human behaviour at the start of the chain. You have to be reasonable. If no-one pissed there would never be a Baltic problem, true. But it is not reasonable to look there as it si not reasonable to expect people not to piss. It is reasonable to expect them to find alternatives to flush toilets.