There is no universally agreed definition of complexity science. However, complexity science is part of the study of complex adaptive systems (CAS).
The best way to describe complexity science is to view an organisation as a CAS.
Applied to organisations, CAS have the following characteristics:
Network: they are networks of various interactions among people or events (things that happen) resulting from interactions. There are connections of some form between the events and interactions, even if organisation members are not aware of this, hence the idea of a network.
Collective behaviour: the networks of interactions and events generate a whole, such as a group, that interacts to form a larger whole, eventually emerging as the entire organisation. These wholes are greater than the sum of the people they comprise, which means we cannot understand the whole’s effect by looking at individuals’ effects.
Complexity Links
- Overview
- Causation in Organisations
- The Illusion of Control
- What is Complexity Science
The organisation adapts: organisations are adaptive in that the individual and collective behaviour changes over time in response to new influences. The organisation learns as it functions.
Self-organising: organisations self-organise their structure in response to various interactions, singular events or combinations of events.
Nonlinear: a collision between a moving and a stationary billiards ball is an example of linear activity; the input (the moving ball) is proportionate to the output (the corresponding movement of the stationary ball). In CAS, outputs can be less or greater than inputs. Another way of putting this is that the relationships between inputs and outputs are not necessarily proportionate.
We can explain and manage individual, group and macro-organisational behaviour through the lens of Complexity Science, which entails viewing an organisation as a CAS. This approach enables us to create conditions that maximise an organisation’s resilience to shocks.
For example, we can apply complexity thinking to understand the supply chain to predict the behaviour of interconnected components in response to contextual influences.
The complexity perspective helps us to understand and optimise the processes of discovery, invention and innovation.
We can apply complexity principles to understand and manage issues such as the formation of behavioural norms, employee well-being, and potential conflict around gender, age and ethnicity, for example.
There is no limit to the resilience-related matters we can address once we see an organisation from a complexity perspective.
