This may sound pedantic but in general a, ‘theory’ strongly suggests some consistent set of tenets, paradigms and mathematical models that are capable of explaining some phenomena. Not only that but in the scientific world, ‘a theory’ is also generally accepted by the community and has a significant level of experimental verification. None of this is true for the study of complexity and the problem is that calling what we have a theory makes it sound so much grander, authoritative and useful than it actually is.
What we do have is ‘complexity science’. This is a multi-disciplinary science that includes research into the complex behaviour of a large and diverse range of systems from many disciplines. The disciplined study of complexity has only been around for a few decades, but some general constructs and definitions have been abstracted from across the extremely wide gamut of systems. However we must always remember that these general constructs have to be fully understood in terms of the particular context in which they are being applied. It seems to me that in the context of project behaviour and organisational change the general concepts of complexity are being applied with little understanding of their full contextual meaning and therefore the conclusions being drawn and advice being promoted is less than ideal.
Part of the problem is also perception. Our understanding of the constructs from complexity science such as chaos, edge of chaos and emergence and many others are not the same as the more defined and quantifiable views of complexity science. This means for example that we perceive chaos when in fact it is firmly in the domain of normal complex behaviour, and we perceive emergence when it is in fact behaviour that we could have predicted from the system components and interaction and therefore not emergent at all. This is of key importance because complexity science suggests that certain complex behaviours are associated with characteristics of such systems, for example:
- Sensitivity to change is associated with bifurcation cascade (extreme complexity)
- Complex behaviour is associated with feedback and non-linearity.
- Self-organisation with the region between bifurcation cascade and chaos (edge of chaos)
- Emergence with highly complex behaviour (approaching bifurcation cascade)
- Predictably and stability with lower level complex behaviour and periodicity.
If an analysis shows that our understanding of these behaviours and constructs is different for projects than other systems studied in complexity science, and that our perceptions of complex behaviour are far different from those of complexity science then it follows that such projects may have less complex behaviour than we assume. This may suggest that some of the characteristics of self-organisation, emergence and predictability are less relevant and less common than we believe.
This is an area of research we will be following on this website.