Complex systems are, as their name implies, hard to understand. The main difference between the sciences of certainty and the sciences of complexity lies in the different causal frameworks they are built upon. Up to now, we have seen the world around us as systems that, we thought, could be described and understood by identifying causal links between things: if I choose X, then it will lead to Y. If, on the other hand, I choose A, it will lead to B.
We are accustomed to drawing boxes and lines between the boxes. We try to model the world as predictable processes that we can control.
The mainstream ways of thinking about management are based on the sciences of certainty. The whole system of strategic choice, goal setting and choosing actions to reach the given goals in a controlled way depends on predictability. The problem is that this familiar causal foundation cannot explain the reality we face. Almost daily, we experience the inability of leaders to choose what happens to their organizations – or to their countries.
We live in a complex world. Things may appear orderly over time, but are inherently unpredictable. If a system’s long-term behavior is unpredictable, goals can still be set, but there is no certainty that the actions taken are going to realize them.
Complexity refers to a pattern, a movement in time, that is at the same time predictable and unpredictable, knowable and unknowable. Healthy, ordinary, everyday life is always complex, no matter what the situation is. Human patterns that lose this complexity become repetitive and rapidly inappropriate for dealing with life. Unlike mechanical systems, human systems thrive on variety and diversity. An exact replication of behavior in nature would be disastrous. For example, a failing heart is typically characterized by loss of complexity.
Human interaction cannot be understood as predictive processes but as patterns. A pattern is something that unfolds through the complex interactions between elements in a system. Although there is apparent order, there is never exact repetition if the system is viable. This is why human interaction cannot be understood as processes in the way they were used in manufacturing, but as patterns.
Patterns that are more repetitive are normally called routines or habits. However, those routines do not cause our behavior. Instead routines are emergent patterns. They emerge in what we do. They continue to be sustained only as long as they are present in our everyday interaction.
The American sociologist George Herbert Mead (1863 – 1931) distinguished between two types of objects: physical objects and social objects. While a physical object may be understood in terms of itself, a social object has to be understood as being composed of patterns of interaction.
Mead referred to a market as an example of a social object. The acts of buying and selling define a market. Markets cannot exist without these social activities. When one person offers to buy something, this act involves a range of responses from other people. A person making an offer can only know how to make the offer if she is able to understand the attitude of the other parties to the bargain. The ideas of buying and selling are thus always interconnected. This is why it is called a “social” object.
The routines define the object. The social object can only be found in the conduct of different individuals engaged in the social act. Thus, there is no market that can be understood as an “it”. Mead’s social objects are not things but generalized tendencies to act in similar ways in similar situations.
We find it easy to regard social phenomena as things with an independent existence. We talk about financial markets being “nervous”. We want more people to recognize patterns “to predict what is going to happen”. But patterns can only be found in the experience of interaction itself. They have no existence separate from interaction and we cannot influence the patterns as separate entities.
We can just participate in interaction – in a dull and repetitive way or in a creative and rich way.