A Framework for Thinking in General – Part 3: Organicism

In the last two posts we looked at two of Stephen Pepper’s World Hypotheses. Formism helps simplify the world by grouping objects into categories but does not explain how things work. Mechanism explains the world in terms of parts that mesh together like the gears in a machine. The idea that everything can be described in terms of absolute or probabilistic cause and effect was so powerful that for at one point many scientists believed that it was only a matter of time before we would have an explanation for everything we see around us. This remained the basic assumption up till the beginning of last century.

But there were some observations that the mechanistic approach could not explain. First, we learnt that there are fundamental uncertainties that are unresolvable. It is impossible to both pinpoint the location of an object and measure exactly its velocity at the same time. What we thought were waves of light sometimes acted as if they were particles. We know when an earthquake is likely but it is impossible to tell when it will happen. Disease-causing bacteria can exist in our bodies but are kept in check in such a way that we don’t display the symptoms of the illness they are thought to cause. Second, it is necessary for mechanistic models to draw a boundary between what’s ‘inside’ the machine and its external environment and to treat the latter as irrelevant. But the real world doesn’t quite work that way. As Lorenz put it, the flap of a butterfly’s wings in Brazil can set off a tornado in Texas. Third, unlike machines, living systems are not only influenced by their environment, but they also adapt to it. Plants grow towards the sun and mice can negotiate mazes to find food.

The mechanist or world-as-a-machine view helps us understand systems that might consist of a number of parts, but behave in ways we can predict by examining those parts. On the other hand, phenomena such as earthquakes or the flow of water in a river cannot be predicted with precision no matter how much we know about them. They are complex (Latin plectare for weave) as opposed to complicated (Latin plicare for fold) systems in that they display emergent behaviour i.e. they behave in ways that we cannot deduce by examining their parts. They are unpredictable, but their behaviour can be governed by certain rules. We know that if we plant an avocado seed and take of it, it will grow into an avocado tree, that its leaves will have a distinctive shape and that it will bear avocados, but we cannot say exactly what the tree will look like. The development of the avocado tree may not be completely predictable but it does follow certain broad rules. Pepper suggested we use the living organism as the metaphor for complex adaptive systems.

Despite recognition in the scholarly and practitioner literature that that organisations are complex adaptive systems, the practice of management remains largely rooted in the mechanist way of looking at the world. For example, we focus on setting budgets and trying to meet them, we use hierarchies to achieve control and we base our reward systems on the assumption of a linear relationship between financial incentives and performance. Since mechanist assumptions cannot explain complex adaptive systems, it is not surprising that typical attempts at bringing about change don’t work at all or at best work only in the short-term.

But that’s not all. There are situations in which the even metaphor of the living organism is insufficient to describe the behaviour of systems, specifically those that involve human beings. Pepper suggested a different metaphor for such systems. In the next post we’ll take a closer look at this fourth of Stephen Pepper’s World Hypotheses.

If you are interested in learning more about organisational alignment, how misalignment can arise and what you can do about it join the community. Along the way, I’ll share some tools and frameworks that might help you improve alignment in your organisation.