Drivers and modulators

September 1, 2009

Photograph courtesy of Daynoir

I’ve been involved in a few interesting email exchanges of late with people using the Cynefin model in both academic and practitioner contexts I always find these exchanges useful, especially where people have taken on and developed the original ideas. One thing that came up this morning (well overnight as the exchange is with an Australian) is the difference between drivers and modulators, or rather the different implications of the two terms.

OK this is a semantic difference, but such differences are important in understanding new concepts and ideas. Drivers are commonly used to describe various aspects of a system which are driving behaviour. With that statement comes an implication of linear causality and attribution. You can see examples of this everywhere. Human behaviour is attributed to drivers such as power, intentional goal orientation, linked to these various drivers is assumed.

Now I don’t want to say that this is not the case, but I do want to say that it is not complete and some of the implications are, shall we say, not helpful. A different way of looking at this is the replace the word driver with modulator. So what does this mean?

One way I have been explaining this of late links back to the photograph which illustrates this post. Imagine that you have a round flat table and around that table are a series of electro-magnets. They can vary in strength and also polarity. Some you control, some are controlled by people you know and some appear to change at random. In the middle of the table are a lot of iron filings. Now as long as the magnets don’t change, the iron filings will form a complex stable pattern. However as the magnets fluctuate in strength the pattern changes. if some of them change polarity then change is sudden and drastic before a new stability emerges. At the same time some of the iron filings get magnetised in turn as they pass through electric currents, making the situation even more complex. I may not even be aware of some modulators until they suddenly come into play and their impact is seen.

The magnets in this case modulate the system. They interact with each other and with the system as a whole, they make it inherently unpredictable. Understanding what modulators are in play will help us understand emergent behaviour of the system, but not to predict its future state. Attributing cause to a limited number of dominant modulators (that is what I think people mean by drivers) is a mistake as the level of interaction is too much. I can build models to simulate the behaviour of the system, however simulation does not lead to prediction.

There are some interesting links here. If you show american students a set of objects they will talk about the most prominent object. If you do the same with Chinese students they will talk about the relationship between objects. The whole driver mindset is seeking to find something to which we can allocate causality. However its not like that, so tempting as it is its dangerous.

Hence the switch from talking about drivers, to modulators. it also opens up interesting issues of representation (landscapes can show modulator impact) and also new ways of assessing risk; how much of the past can you explain by the modulators of which are are aware. The difference is the dark matter (more accurately dark energy) component. If high, then risk is high, if low then its less and you scan the field in different ways.

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The Cynefin Company (formerly known as Cognitive Edge) was founded in 2005 by Dave Snowden. We believe in praxis and focus on building methods, tools and capability that apply the wisdom from Complex Adaptive Systems theory and other scientific disciplines in social systems. We are the world leader in developing management approaches (in society, government and industry) that empower organisations to absorb uncertainty, detect weak signals to enable sense-making in complex systems, act on the rich data, create resilience and, ultimately, thrive in a complex world.

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