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Core features of a Complex Adaptive System

Complex Adaptive System

A complex adaptive system is a coherent system, where even a perfect understanding of its constituent parts is not cause‐effect related to the systems overall behavior. It is not possible to predict the behavior of the whole by knowing the behavior of the parts. The dynamic order (read viability) of a Complex Adaptive Systems emerges spontaneously, or, in other words, by self‐organized decentralize control. This does not mean there is no structure at all. It can just not be bureaucratic. 


What does emergence mean? To understand it better, we need to look at things from a different perspective. The next picture will help us with this. If you look at the picture, you see between the three PAC-Man's, the emergence of a triangle. It can only exist if you consider all three (which need to be correctly rotated or adapt the right position) and focus on their interactions. It emergence spontaneously from the interactions between the PAC-Man's. It is greater than the sum of the PAC-Men. In our model we assume viability emergence from system interactions.

Viability ratio

A very important feature of a Complex Adaptive System is the viability ratio. In our PAC-man example, these are the mechanics inside the governance PAC-man that are governed by a mixture of controls. Or another easier to understand example. The financial potential of a company is dependent on the ratio of equity and debts or leverage ratio. The right diversity between equity and debts allows a company to attract additional capital to respond to an investment opportunity. Why is the ratio so important? Viability represents the potential to recognize, adapt to and absorb problem disturbances without noticeable or consequential decrements in performance and value creation. The viability ratio is a critical ingredient for viability because it gives the system the requisite variety that allows responding to disturbances or opportunities.

Drivers and Modulators

In our model the viability ratio dependents on two independent variables, called drivers and modulators, that can change over time. Whereby one variable is more focused on stabilization than the other; as a result, there will be a permanent shift in the ratio because in a changing environment, stabilization creates more stabilization over time. The mixture (or the change ratio) of the independent variables creates diversity but can also destroy it if it is out of balance. Drivers and modulators are feature of the system; as there is not one variable that possesses enough capacity to represent the viability of the entire system in that variable itself. Therefore, you cannot reduce the ratio to only one variable; it can only be characterized based on the multitude of the ever-changing relationship between the variables.

Distributed minimum structure

Why is a distributed minimum structure important? Because the environment is complex and constantly changing as time is always moving forward. Having a distributed bottom-up intelligence in the organization improves the response time to disturbance from the environment. Going back all the time to the management team to ask for direction can disrupt the energy flow that is needed to quickly response to changes.