Follow us on LinkedIn
In my last post I raised the question of reductionism versus holism in modelling the enterprise. So which kind of model is more useful to us, in terms of the reality it represents and our ability to work with it effectively?One of the starting points for the development of Business Process Models is the use of the context diagram. The purpose of the diagram is to identify and document all entities that have a specific impact upon the process. In defining the ‘impact’ of a process, they are deemed as being either suppliers or customers of the specific process. The context, a static picture, sets the scene for the subsequent breaking down (‘decomposition’) of the process into discrete activities. In decomposing the model, we seek to reduce it to its constituent parts for more detailed analysis and so on.
As an approach, this method is particularly interesting. In creating this determinate view we also find ourselves at the very dichotomy (false or otherwise) of science. In the realm of science we find the reductionists and the holists.
Reductionism is defined as being an attempt or tendency to explain a complex set of facts, entities, phenomena, or structures by another, simpler set: “For the last 400 years science has advanced by reductionism… The idea is that you could understand the world, all of nature, by examining smaller and smaller pieces of it. When assembled, the small pieces would explain the whole”.
Holism, on the other hand, is the theory that living matter or reality is made up of organic or unified wholes that are greater than the simple sum of their parts.
The ‘whole’ refers to what I would call a complex system: “A group of interacting, interrelated, or interdependent elements forming a complex whole”. We can bring this to life by relating how that translates to Complex Adaptive Systems (CAS) we are familiar with such as the human body, natural phenomena like ecology, weather systems and migration patterns, as well as economies and indeed large, complex organisations.
Descriptions of complex systems are determinate and complimentary, entirely dependent upon the observer. Systems move and morph through points of equilibrium as they adapt and self-organise according to their environment or context and, in this sense, control and order is emergent rather than predictable. This makes modelling them a challenge.
The search for defining models of complexity is an inquiry to build fuzzy, multivalent, multi-level and multi-disciplinary representations of reality. When we think about trying to model an enterprise taking a systemic approach, it can feel overwhelming. But remember, holism is not necessarily mutually exclusive from a reductionist approach. The two can be complementary and there are disciplines such as cybernetics that can help us with that.
At Innovation Arts we understand and embrace the complexity in your organisation. Our approaches are designed to help you model your complex systems, and work with these models to rise to whatever challenges to face.