Tag: complex systems

Complex and adaptive

On the complexity of change

Let’s forget about changing anything. Just for a little while. Let’s just think about complexity. Something complex. A complex process. Got it? Why is this process complex? What makes it complex?

First answers are simple: a process with more than one actor is more complex than a process with just one actor. But it is not just the participants. Many natural or industrial processes are complex, and they do not necessarily even have participants (humans) that act in them. So, there can also be many components. And if that were not enough, more often than not there are many variables. You remember these variables from math classes in school.

x + 7 = y

This is a nice linear equation – and thus not complex. For each x there is exactly one y, which can be calculated, if you know how do do this sort of thing.

Think about the complex process you have in mind. It does not just have one variable, one x, that changes or can be changed. Most processes in life, in society, in biology, in physics, in nature, … in most places where we care to look, have more than one variable. More than one (in)observable trait, characteristic, or feature that can change or that can be changed.

Now that’s OK, you say. We just have to look at a few more things. Right! Problems arise when there are very many, often too many, to always keep our eyes on, to look out for, to consider. And not only that. Each of these variables, each x, if you like, does not just have one dependent y. More than one variable can depend on each changing variable.

I am changing the period of time I use for exercise in the morning. I am changing time t. Time t influences my fitness level; I am increasing muscle mass and flexibility. Because of the increased muscle mass, my metabolism changes during the day. I feel better, I am more agile, I move more and quicker, burning more calories than on the days prior. And by increasing time t for exercise, I am reducing time r for reading … Twitter, my favorite book, a newspaper, or some emails. I am also reducing time c for cooking, so I will have to have my lunch prepared the evening before or will have to go to the cafeteria to buy something to eat.

You get the point.

A complex phenomenon does not just have many variables. Each of these variables potentially interacts – metaphorically speaking bounces off and changes – one or more other variables. Overstating just a little bit: each of the many variables changes all the time, in concert and against each other.

Did I say at the beginning: Let’s forget about change for a little while? Impossible. We quickly returned to the concept of change. Change is part of complexity and complexity is part of change. We cannot – and should not – consider one without the other. [Maybe just for a quick thought experiment, or if we are really tired in the evening.]

What are the consequences? Complex phenomena are in constant flux, change constantly. That’s why we often talk about complex dynamic systems. Variables interact with one another, components interact, actors (participants) interact. In these many continuous or iterative interactions, each variable, component, and actor are also prone to change. They co-adapt. Especially for social systems, we often use the label complex adaptive systems (CAS). And if we want to understand change better, be able to influence it a little bit, or just deal with it, it is useful to look at some of the characteristics of complex adaptive systems.

  • CAS are likely to be on a nonlinear trajectory, which means a change I put in does not necessarily result in a proportionate change to come out.
  • CAS are sensitive to initial conditions. The variables, however small they might be, that were there from the very beginning are most likely to have had a relatively large impact on the whole process, simply because they have been around for long enough.
  • CAS have attractor states – states they are more often and more likely in. They also have repeller states, states which they could reach theoretically but never or hardly ever reach.
  • CAS are likely to reach an equilibrium – like a standstill, change is very close to zero – if no new energy enters the system.

I am glad I got this out of the way. And maybe so are you. Remember that I said it is often useful to apply a theoretical lens to gain a better understanding of a problem? At some stage I had to introduce the lens. In subsequent posts, I will look at these characteristics of complex adaptive systems, one by one. And I will show for each one what role their understanding can play in solving personal problems, problems at work, in social interactions, or just around the house.

The neat thing with these CAS is that there has been a lot of research that tried to figure out how to get a better handle on the complexity. And I am as sure as one can be that what we learn about the ever-changing complexity will come in handy almost every day, when solving problems. Whether this is in your personal life, when making leadership decisions, or simply when you are trying to fix something that you believe needs fixing.

And to finish off, if you’d rather read the texts on the Complexity of Change in one possible order … a table of contents is emerging.

All these complications!

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.

No one steps in the same river twice.

What problem(s) do you have?

On the complexity of change

It’s too difficult! Does this really have to be so hard? You are being complicated.

Have these thoughts crossed your mind? Every day? Each hour? Fleetingly? Or have they lingered, recurred? Made you swear or resign? Or you buckled down and tried harder? I know for me it has been all of the above. And more. I have to ask, though. All of these feelings and experiences are subjective. It depends on us whether or not and to what degree we perceive something – a task, a request, a plan, an experience, a process … – as hard and challenging or as easy and quick. Yet, many of the problems or challenges we face or see others tackling “contribute” in and of themselves to being more complicated than others. Why?

At first sight, the answer is trivial. Such processes are not only complicated, they are complex. Complex problems.

I believe it is useful to take a good look at their complexity. At bare minimum, we know better what we are dealing with; at best, we arrive at a path to a solution and—with a little bit of luck—get a feeling of ease and simplicity.

Let’s put on our theoretical lens. (Very helpful, remember?) What is a problem? And what makes many of them complex?

Let’s pretend you have not encountered the concept of problem before. Let’s take a fresh quasi-naïve look.

So, you stare at your very first problem … What is happening? The process you look at is in state A. You want to, have to, plan to have the process reach state B. There is a hurdle, an obstacle between state A and state B. It’s easy, right? Solving that problem involves overcoming the obstacle and getting the process from the current state A to the desired state B.

The management consultant and researcher David Snowden distinguishes four different types of problems. I will call them simple, linear, complex, and chaotic problems.

Simple. You get up in the morning. You want some coffee (desired state B). There is no coffee; the pot is empty (current state A). The obstacle is minimal: fresh coffee needs to be brewed. You have done it a thousand times. You know exactly what to do, without having to analyze the current state and its context, available tools and avenues, and possible solutions. This is a simple problem. It presents itself, you immediately recognize it, automatically know the details of the desired state B – a nice cup of dark roasted coffee, no milk or sugar because its acidity are low and neither is needed.

Linear. You have had your coffee. The day can start, but first you decide to immediately wash your cup. And! When you pour water in the sink, you realize the drain is blocked (current state A). (The desired state B is an unblocked sink drain, of course. The obstacle is the drain has to be unblocked.) You analyze the situation. You look and think, you poke around. What is blocking the drain? How stubborn is the blockage? You look at some contextual factors: how urgent is it? how much time do I have? what tools do I have at home? what am I able and willing to do? who could help? how much does it cost to call a plumber? and when are they gonna come? You do this analysis of state A and its context once. You know how to do it. You match the result of your analysis with an appropriate course of action, such as pouring hot water or drainage cleaner down the drain, removing the elbow underneath yourself and cleaning it, notifying the landlord or building manager, or calling a plumber … If this is indeed a linear problem, then this course of action will produce a result. With a bit of luck – and skill and effort – the drain is unblocked. And the cups of the future can be washed. A linear problem like this one requires analysis. Both the analysis and overcoming the obstacle require a skill set and some labor. Linear problems have a best solution, which is the one that most likely and most efficiently leads to the desired state B. You can consult an expert who will present, and often implement, the required solution to/for you.

Since the third type is called complex problems. You are assuming right: neither linear nor simple problems are complex. The general problem of problem-solving is, as David Snowden pointed out, that most problems we encounter in our daily lives, with our and other people’s’ health, at work, in relationships, in politics, with the environment, in history, … are neither simple nor linear.

I am going to hazard a guess: most problems you have encountered, witnessed, heard about are complex. So, in the next post—you have been reading for long enough—I will take a closer look at these omnipresent complex problems.