Complex Adaptive Systems

We wish to acknowledge and thank all those scholars, scientists, researchers, academics and others for their continued work on 'complex adaptive systems' from which we draw.

The main focus of western thinking has been underpinned by the work of Newton.  The Newtonian approach to understanding systems is to break them down into their distinct parts.  These parts are then analysed and if possible improved.  The view being that if the parts are improved, the whole would work better.  This thinking is based on a linear, mechanistic and predictable world.

This Newtonian approach first applied to science, was subsequently applied to the study of other systems such as human and organisational development.  This thinking system provides some understanding of how things work and may provide insight into improvements but when it comes to complex, non-linear, unpredictable systems its not an effective model.

About 40 years ago science moved away from this simple Newtonian view to that of ‘complexity science’. Through studying living systems a different evolutional pattern was observed, the 'complex adaptive system'.

The term ‘complex adaptive system’ describes more fully how systems are, complex, non-linear, multi-dimensional and dynamic.  To be understood they need to be studied in their entirety. Previously very distinct disciplines are coming together to develop this work.  They come from the fields of management consulting to earth scientists to pure mathematics and computing.  As a 'new science' it is still coming to grips with terms and definitions. Keeping that in mind, this is our researched version of the properties involved:

Some Properties of Complex Adaptive Systems...

Co-evolution or adaptive: systems exist within environments. They change in response to the environment and the environment changes in response to the systems, not simple cause and effect.  There is a constant 'dialogue' that informs the development.
Requisite Variety: the greater variety within the system the stronger it is, the more likely it is to have the capacity to adapt.  With increased variety comes greater complexity and contradiction.
Self Organising: there is no strict hierarchy or command and control line.  The system constantly self organises for maximum effective performance.
Emergent: In looking at systems the elements of any system are termed 'agents'.  Agent's interactions appear to be random, patterns emerge, and these patterns inform the whole.  An example from nature is a bee hive emerging from the work of all the agents (bees) within the system. There was not one bee with a blue print of the hive which all the other bees aligned to.
Connectivity: the relationship between the agents within systems provides feedback and in a sense is more important than the agents themselves.
Edge of Chaos: any system could be in variety of states from equilibrium, to chaos.  A system in equilibrium does not possess the internal dynamics to respond to its environment and will die; a system in chaos ceases to function as a system.  It is therefore on the edge of chaos that a system is at its most dynamic and responsive.
Simple Rules: despite the complexity of how the patterns emerge, they are based on simple rules, e.g. all the waterways in the world share one rule; water finds its own level.
Sub-optimal: a system does not have to be perfect in order to thrive in its environment. It only needs to be slightly better than its competitors.  For a team to win the world cup, they don't need to score hundreds of goals more, just one.  Any more would not be an efficient use of energy.
Control: they can be destroyed by outside control.
Holistic or Nested Systems: systems sit inside other systems, systems overlap.  Agents can be members of many different systems at the same time.
Iteration or the Quantum Effect: small changes can create massive results (often referred to as the butterfly effect).  A bucket posed to tip fills up drip by drip, at the end it is only one drop that causes the bucket to tip and massively change the status quo.

At Facilitating Results we believe human beings and the organisations they work in are more aligned to 'complex adaptive systems', than in linear predictable Newtonian science.

We need to see them as a whole and assist them to adapt and to creatively co-evolve. Part of that process is to understand the whole organisation and its environment for example: the core business, the vision and values, the desire/actual business results, the overall strategies, the department/systems (e.g. Accounting, HR, IT etc), how each department interrelates, the staff/ culture, the external stakeholders, the external economy, the impact of the organisation on society as a whole etc.