Interactions and Systems

This discussion goes to the heart of a subject which we don’t discuss nearly enough and that is interactions.

In a predictive model there are typically what statisticians call ‘main effects’. A good example in medicine is the effect of particular medications. But sometimes medications in combination potentiate (or neutralize) each other. In other words there is another effect caused by the combination of medicines that changes the outcome. That is the idea of an interaction. A catalyst in a chemical reaction might be another example.

One of the aspects of systems is that the parts of them interact. So it is with SOPK. Each of the pillars interacts with the others to produce effects that none produces alone. Marc Hersch’s continuing references to reductionist thinking is getting at this point. The “System of Profound Elephants” is a metaphor for the fact that one cannot understand an elephant to be a collection of components.

Consider a pile of sand. With a shovel you can divide it in two and have two smaller piles of sand. Cutting a cow in two does not produce two small cows.

Consider an example Deming loved to use; that of the symphony orchestra. An orchestra is not a collection of soloists. Two orchestras can play the same piece with the composition of the orchestra being the same and every note played being identically, but what a difference there can be. It’s how they play together that makes a difference. That is, it’s the sound of the individual and the interaction of the components that creates the sound.

On a more mundane level we can have team working on a task. A new member is added and suddenly the team’s progress accelerates markedly. A positive interaction at work. Or a different team after adding a person suddenly grinds to a halt. It’s how the team (a system) works together. The first instance we call “Good chemistry”.

Successful managers understand these interactions, how they work and they manage them as well as the main effects.