Esko Kilpi on Interactive Value Creation

The art of interaction, the design of digital and the science of social complexity

Tag: complex causality

Complexity

The way we want to make sense of the world around us often has to do with causality. The question we ask is what caused “it” to happen. The mainstream approach is that an arrow, or arrows, can be drawn. There is a variable, the “it”, that happened, that is now to be explained. In scientific study this variable is regarded as dependent. An independent variable, or variables, that cause it are then sought. Causality means that X causes Y. If there is more X there will also be more Y. This is the if-then model of management. In organizations, a familiar explanation for success is that a particular manager or a particular culture caused it.

But there is something significant happening today. Scholars are increasingly pointing out the fact that this view of the relationship between cause and effect is much too simplistic and leads to a very limited or even faulty understanding of what is really going on.

Cybernetics recognized a much more complicated causality. In this kind of system the arrows, the links, between cause and effect can be distant in terms of time or place. The system can be highly sensitive to some changes but very insensitive to some others. For the first time, it was understood that it is a non-linear world.

Complexity challenges the assumption of earlier systems theories that movement in time can be predictable in the sense that X causes Y, or that the movement follows some archetypes. The modelling differs significantly from all previous systems models.

Complexity means a different theory of causality.

The most important insight is that it is often not possible to identify specific causes that yield specific outcomes. Almost indefinite number of variables influence what is going on. The links between cause and effect are lost because the tiniest overlooked, or unknown, variable can escalate into a major force. And afterwards you can’t trace back, you can’t find the exact butterfly that flapped its wings. There is no trail that leads you to an independent variable.

The future of a complex system is emerging through perpetual creation. Complexity is a movement in time that is both knowable and unknowable. Uncertainty is a basic feature of all complex systems. It is a dynamic in time that is called paradoxically stable instability or unstable stability. Although the specific paths are unpredictable, there is a pattern. The pattern is never exactly the same, but there is always some similarity to what has happened earlier.

In the end it is about the combination and interaction of the elements that are present and how absolutely all of them participate in co-creating what is happening. None of the elements cause the end result independently. From this standpoint a lighted match does not cause a fire. Rather, the fire took place because of a particular combination of elements of which the lighted match was just one. In the same way, a rude remark does not start a fight. The argument starts as a combination of an offensive remark and a coarse response.

The big new idea is to reconfigure agency in a way that brings complex relationships into the center. The task today is to see action within these relationships.

Complex relationships cannot be understood through spatial metaphors such as process maps or network charts. Unhelpful or wrong models and metaphors are often a big obstacle to moving our thinking forward after the technological constraints are gone.

We need to move towards temporality, to understand what is happening in time.

An organization is not a whole consisting of parts. There is no inside and outside. An organization is a continuously developing or stagnating pattern in time. Industrial management was a particular pattern based on specific assumptions about communication, causality and human psychology.

Recent developments in psychology/sociology have shown that human agency is not located or stored in an individual, contrary to what mainstream economics would have us believe. The individual mind arises continuously in communication between people.

The focus of industrial management was on the division of labor and the design of vertical/horizontal communication channels. The focus should now be on cooperation and emergent interaction based on transparency, interdependence and responsiveness.

Looking at communication, not through it, what we are creating together.

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Thank you Ralph Stacey, Ken Gergen, Doug Griffin, Jim Wilk, Marko Ahtisaari and Katri Saarikivi

Business and complexity

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.

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John Hagel on “harnessing the power of randomness” and “resilience