Examining Complex Systems

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We live as part of a complex system. This means that we struggle to make sense of what is really happening around us. To cope, we greatly simplify what we see, we build false narratives that explain what is going on and we create in our own minds a world as we would like it to be rather than how it is. In many ways we are still quite primitive creatures driven by an instinct to survive. Having said that, we have tried to   develop the way we think and to learn about the world in which we exist.

Ever since the enlightenment Western societies have been schooled to believe in logic and rationality. This schooling makes us value the reduction of the systems that affect us into cause-and-effect mechanisms as a way to understand the world around us. By doing this we believe that we can understand why things happen in the way that they do. By increasing our understanding, we hope we can see ways to control what happens to us.  By having this control, we seek to make our world a safer place to live. However, there is one major flaw in this logic. While some people have a capacity to understand far more than others, no member of humanity has the mental capacity to understand the system as a whole. Everybody needs, to some extent, to simplify the whole to make sense of it.

To understand the world, we build mental models. These models are given many different names. They may be called theories (both academic and lay), hypotheses, propositions, frameworks or other system models. However, it has to be recognised that all models are full of assumptions and simplifications. George Box has therefore provided a valued heuristic when we consider the models we use. He said, "all models and wrong but some are useful." To me models are useful when they make us question what we see. To me they are useful when they make us probe the assumptions we are making, examine the ways we have simplified what we are looking at and where they make us conscious of making these choices.

The very nature of learning means that we are building a set of assumptions about how the world works. Some of these assumptions will be found to hold true every time. Some of these assumptions will be found only to hold true in certain circumstances and others will prove to be false. Life is a continual process of learning where we refine our assumptions and learn when they are likely to hold true and when they probably will not. It would be good if this process was a linear journey of accumulating understanding but, unfortunately, it is not. While we do learn, we also forget and so learning has to be seen as another complex (non-linear) process. We forget because we have a somewhat limited mental capacity to make sense of things.

This limited mental capacity also means that we instinctively simplify what we see in order to make sense of it. We simplify the world in many ways such as placing boundaries around problems, limiting what is being considered. We use heuristics as a shortcut to decision making and reduce non-linear systems to a linear process. As humans the approach we take to tackling complex problems is to take them one step at a time. This is referred to as 'muddling through'. The problem with this approach is that it often produces non-optimal outcomes compared to if the problem had been tackled holistically from the start. The problems produced by muddling through are compounded by what Kurt Gigerenzer calls one-reason decision-making: this is when we make decisions based on finding the first option that meets a certain criterion. In short, in both muddling through and one-reason decision-making, we trade a thorough understanding of an issue with knowing enough (sufficing) to take the next step.

The dilemma is acknowledged more often than you might think. Every time someone utters the phrase "but in a perfect world" they are acknowledging, at least sub-consciously, the dilemma. The phrase acknowledges that there is, in theory, a perfect outcome but it laments that such a perfect outcome may not be possible to achieve.  During my earlier work I have defined what such a perfect world would look like: see here. The problem is however that the perfect world paradigm is a linear system while the real world is non-linear. I have accepted that in order to act we will often have to simplify the problem we face in line with the ETTO principle. However, from a risk governance perspective, every false assumption and simplification provides a gap between hopes and reality through which an unwanted event may emerge. I therefore see each thoroughness/ efficiency trade-off requiring a cost benefit analysis. I do however recognise that each trade-off will also be the subject of its own trade-off and so many of these gaps will be overlooked. In the end, the outcome I would hope for is that decision-makers become more aware of the risks they are taking due to unexamined false assumptions and simplifications where they had previously never been conscious of them.

The purpose of my research is to develop a framework that provokes debate that exposes hidden assumptions and simplifications amongst those tasked with managing a complex system. An additional benefit of such debate is that it should help to develop cross-understanding and therefore alignment of thinking within the team.

As I have said previously, while there are many researchers who look to manage complexity through quantitative methods, my approach is more qualitative and focused on sense-making. My personal preference when it comes to sense-making is to try to visualise the relationships between the parts that make up the system. As an example of how a complex system might be visualised, I offer below one produced by PA consulting. Their visualisation tries to depict the non-linear dynamics that affect the social stability of Afghanistan in 2009. It should be noted that, at that time, NATO had over 55,000 troops in country to support their political ends. Over time this number was reduced to 10,000 and yet the country's dynamic of macro stability was maintained. However, it only took the withdrawal of the 2,500 US troops in September 2021 for the country's political system to collapse. While the dynamics of this system collapse would no doubt be fascinating to study, that is not my purpose. I will however be referring back to this diagram to help readers visualise the points I will be making about [1] sense-making and [2] learning when it comes to complex systems.

In order to understand the true complexity of the system that this diagram depicts, readers will need to imagine that there would be a similar detailed diagram to describe each component (node) of this network of interactions. This would be similar to the cube I depict here. In this diagram each set of words should be considered to be a node.