I have been noodling on a decision-making framework, and I am hoping to start writing things down in a sequence, Jank-in-teams style. You’ve probably seen glimpses of this thinking process in my posts over the last year or so, but now I am hoping to put it all together into one story across several short essays. I don’t have a name for it yet.
The first step in this adventure is quite ambitious. I would like to offer a replacement for the Cynefin framework. Dear Cynefin, you’ve been one of the highest-value lenses I’ve learned. I’ve gleaned so many insights from you, and from describing you to my friends and colleagues. I am not leaving you behind. I am building on top of your wisdom.
This new purported framework is no longer a two-by-two. Instead, it starts out as a layer cake of problem classes. Let us begin the story with their definitions.
At the top is the class of solved problems. Solved problems are very similar to those residing in Obvious space in Cynefin: the problems that we no longer consider problems per se, since there’s a reliable, well-established solution to them. Interestingly, the solution does not have to be deeply understood to be a solved problem. Hammering things became a solved problem way before the physics that make a hammer useful were discerned.
Then, there is a class of solvable problems. Cynefin’s Complicated space is a reasonable match for this class of problems. As the name implies, solvable problems don’t yet have solutions, but we have a pretty good idea on how they will look when solved. From puzzles to software releases, solvable problems are all around us, and as a civilization, we’ve amassed a wealth of approaches on how to solve them.
The final class of problems loosely corresponds to Complex space in Cynefin. These are the unsolvable problems. Unsolvable problems are just that: they have no evident solution. At the core of all unsolvable problems is a curious adaptive paradox: if the problem keeps adapting to your attempts at solving it, the solution will continue being just out of reach. I wonder if this is why games like chess usually have a limited number of pieces and a clear victory condition. If the opponents are matched enough, there must be some limit to make this potentially infinite game finite. Another way of thinking about unsolvable problems is that they are trying to solve you just as much as you’re trying to solve them.
You may notice that there is no corresponding match for Cynefin’s Chaotic space in this list. When describing Chaotic space, I’ve long recognized the presence of a clear emotional marker (disaster! emergency!) that seemed a bit out of place to how I usually described other spaces. So, in this framework, I decided to make it orthogonal to the class of the problem. But let’s save this bit for later.
The interesting thing about all three classes is that they are a spectrum that I loosely grouped into three bands. Obviously, I tend to think in threes, so it’s nice and comfy for me to see the spectrum in such a way. But more importantly, each class appears to have a different set of methods and practices associated with it. You may already know this from our studies of Cynefin. Just think of how the effective approaches in Complex space differ from those in Complicated, and how both are different from those in Obvious.
Still, it is also pretty clear that the transition between these classes is fuzzy. As my child self was learning to tie shoes, the problem slowly traversed across the spectrum. First, the tricky bendy laces that kept trying to escape my grasp (oh noes, unsolvable!?) became more and more familiar, while tying the crisp Bunny Ears knot, despite being clearly and patiently explained, was a challenge (wait, solvable!). Then, this challenge faded, and tying shoes became an unbreakable habit (yay, solved). This journey across the problem class layers is a significant part of the framework, and something I want to talk about next.
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