Complex Adaptive Systems

 

  Complex adaptive systems are those with individual members that can interact with other members of the system and can adapt in response to changes in their environment. Their title comes from the adaptive nature of the system and that they exhibit the properties of complex systems. Systems of this type have been shown to have certain properties and OE uses this learning to help in understanding the way in which organisations work. It is important to understand that in these systems individual members are free to choose how to react to other individuals and to changes in the environment. Individuals influence others and are in turn influenced by them. For this to happen there has to be some connectedness (communication) between them. All systems exist in some sort of environment and the ability of the individual and system to respond to these changes determines whether it survives or not.

 The key properties that these systems exhibit are:
unpredictability/non-linearity,
emergent behaviour,
dynamic (always changing),
dispersed control,
communication.

Unpredictability


Complex systems are not predictable in the sense that we cannot say given what happened in this moment what will happen in the next. However, overall patterns arise from these systems (see emergent behaviour). The system is non-linear; there is not a simple, direct relationship between input and result. This property is described by complexity theory which is built on chaos theory.

Emergent Behaviour

CASs are not predictable from moment to moment but patterns can be seen by standing back from the system. This was seen in the pictures made to represent mathematical models that exhibited chaos. <see  >. In the case of CASs, the patterns are shown in the behaviour of the system as a whole and is called emergent behaviour. The behaviours are not apparent from the behaviour of the individuals nor are they controlled or imposed from outside. They arise spontaneously as a result of the interactions inside the system.

 This feature is very important because it gives us a way of understanding how to influence organisations.

 A commonly quoted example of a system that shows emergent behaviour is that of a flock of birds. The flock wheels and turns in unexpected ways but remains coherent and seems to be obeying some complicated rules about where to go, when to change direction etc. In fact it is possible to simulate this behaviour in a model where the only rules are three very simple ones that each individual obeys (usually). <see

Dispersed Control

There is no central control, no directing force. The behaviour of, and outcomes from, the system are as a result of the actions of individuals reacting within a complex system.

Communication

In order for the system to work, there has to be a level of communication between individuals in the system. The communication, though, is diffuse and not handled through control structures.

This actually occurs in organisations but usually through unofficial channels (the coffee machine syndrome). The information passed through these routes is often based on shared experiences and personal understanding and so is relevant and easily passed on. Official communications have an important role but this ‘shadow organisation’ is very important in allowing the organisation, and in particular parts of it, to adapt to new inputs.