Up to now, we have seen the world around us as systems that, we thought, could be described and understood by identifying rational 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 arrows between those boxes. We try to model the world as predictable processes based on knowing how things are and how they will be. We want to be certain, and we think we are.
Management thinking is 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 them, to their organizations – or to their countries. Things may appear orderly over time, but are inherently unpredictable. We live in a complex world.
Complex systems are, as their name implies, hard to understand. Social systems, like organizations consisting of people, are accordingly complex and hard to understand. There is no linearity in the world of human beings. There are no arrows and people are not boxes, or fit inside of boxes. This is why our thinking needs to develop from the sciences of certainty to something more applicable, the sciences of uncertainty, the sciences of complexity.
Complexity refers to a pattern, a movement in time that is, at the same time, predictable and unpredictable, knowable and unknowable. Chaos theory explains how these patterns form. A parameter might be the flow of information in the system. At low rates, meaning no input or more of the same input, the system moves forward displaying a repetitive, stuck behavior. At higher rates and more diversity the pattern changes. At very high rates the system displays a totally random behavior. The pattern is highly unstable. However, there is a level between repetition/stability and randomness/instability. This level where simultaneous coherence and novelty are experienced is called the edge of chaos.
Classical physics took individual entities and their separate movement (trajectories) as the unit of analysis in the same way we have analyzed and rewarded individuals. Henri Poincaré was the first scientist to find that there are two distinct kinds of energy. The first was the kinetic energy in the movement of the particle itself. The second was the energy arising from the interaction between particles. When this second energy is not there, the system is in a state of non-dynamism. When there is interactive energy, the system is dynamic and capable of novelty and renewal.
Interaction creates resonance between the particles. Resonance is the result of coupling the frequencies of particles leading to an increase in the amplitude. Resonance makes it impossible to identify individual movement in interactive environments because the individual’s trajectory depends more on the resonance with others than on the kinetic energy contained by the individual itself.
We are the result of our interaction. We are our relations.
The conclusions are important for us: firstly, novelty always emerges in a radically unpredictable way. The smallest overlooked variable or the tiniest change can escalate by non-linear iterations into a major transformative change in the later life of the system.
Secondly, the patterns are not caused by competitive selection or independent choices made by independent agents. Instead, what is happening happens in interaction, not by chance or by choice, but as a result of the interaction itself.
The new social technologies have the potential to influence connectivity and interaction as much as the sciences of complexity are going to influence our thinking. The task today is to understand what both social business and complexity mean. The next management paradigm is going to be based on those two, at the same time.