On the complexity of change
A good morning. I know what I want to do. I know I can do it. I am optimistic. I have sufficient energy. [Not as much as I used to have some years ago, but good enough.] All this makes me feel great. Then! I glance at my email inbox. I see the one email. Yes, that one. I read it again. It sinks in deeper. I sink deeper. I have seen “this” before. I have dealt with “this” before. I had fixed it. Was that not good enough? Really, “this” is coming up again? It obviously is. ∑√i†!!! I have to do “this” again and can’t do what I want to do. Again, there is no time to do what I want to do, what actually needs doing [or so I believed], because I have to go back. Again. And again. Really?!
Sitting here writing, I can see “this” as what it is: yet another one of my encounters with a complex problem. Why does it happen so often? Time to put on our theoretical lens to get both a little more clarity and some – also emotional – distance.
The four types of problems – simple, linear, complex, and chaotic – do not each arise with the same frequency. Simple problems arise far less often than linear problems. We encounter linear problems far less often than complex problems. [Since we all live in a good world at a good time, chaotic problems arise least frequently of them all. But that’s a topic for another day.] We often find complex problems complicated. We might even react with frustrated surprise. Normally, we are more familiar, more comfortable, and hence more successful (in solving the problem) when we have encountered something more frequently. Here the opposite seems to happen: the more often the problem occurs, the more complicated we find dealing with it. It gets more and more frustrating. Why is that?
Essentially, a problem is wanting to move a process from state A to state B, and there is a hurdle between the two states. Two states. This makes us think of “this” as a binary. It is either “this” or “that.” It is an If—Then; if I do this, then that will happen. Either “this” gets fixed now and will be in a “good” state, or “this” does not get fixed and will be in a “bad” state forever. [We as humans seem to have a preference to see the world in linear binaries: either—or, if—then, cause—effect, plus—minus, right—wrong, … female—male, black—white, we—other, native—foreign, … That is also a topic for another day.] In other words, we expect to encounter linear problems more often than linear problems do occur. And, complex problems, because of their complexity, are likely to look different every time they arise. And, they appear frustratingly similar at the same time, especially if one looks at their surface first and foremost.
How can we deal with a complex problem effectively? This problem type arises from us being one actor in a complex dynamic system, which is basically a process that has multiple interacting actors, components, and variables and that is (very) sensitive to its context. [In a later post, we will take a good look at complex dynamic systems.] Because of that, we – as the problem solver – have to be prepared to consider this emerging process thoroughly and comprehensively. We have to assume there is no best solution, as their is for both simple and linear problems. After careful consideration or analysis, there is a solution. It is unlikely – and it might actually be undesirable – that a solution will bring the whole process into a stable end state. This means, we implement a solution and need to be prepared and willing to keep observing the changing system, ready to repeat our work of consideration and analysis and to implement another solution. The complex process will change again. The change is unlikely to be proportionate to the solution. The reasons for that are in the complexity of the process. More on this also later. So, we will have to be prepared to observe the system, consider it and its context, and to implement another solution, as we did the first time and as we will be doing as long as we care. Although different facets of the system, the problem, and our solution are often self-similar, it is not the same over and over again.
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