Innovation Through Chaos, Really

Posted: June 26, 2014 in Change, educate
Tags: , , , , , ,

fractal1With all the buzz around some wonk dashing some other wonk’s theory on disruption, I thought I’d go back to the theory I like to use in change and process management: Chaos Theory.

Chaos Theory or Complexification was all the rage some 20 years ago. No one even talks about it anymore (well someone does, just not everyone). Which is a shame, though I think a lot of that is due to confusion about what it was really about.

Chaos Theory was never really about chaos per se. It was about trying to understand complex systems. Excuse the rather academic quote below to explain:

The term “chaos” currently has a variety of accepted meanings, but here we shall use it to mean deterministically, or nearly deterministically, governed behavior that nevertheless looks rather random. Upon closer inspection, chaotic behavior will generally appear more systematic, but not so much so that it will repeat itself at regular intervals, as do, for example, the oceanic tides.

The point I took from this to inform my own chaos philosophy in change management was this: systems may appear chaotic but can have an order of sorts if looked at from the right perspective.

For those of you who missed the fad, here is a good intro. You should read it now.

Finished? OK, let’s move on.

Back to the chatter about disruption and my chaos philosophy. Fellow change masters Jen Frahm and Gail Severini both posed in different ways the questions about disruption or innovation in change management. I attempted in an earlier post to make a point about innovation often occurring when you intersect disciplines (a concept I certainly did not make up).

So here is an example of intersecting disciplines: change management and chaos theory. The complexity of an organization certainly falls into the realm that chaos theory is interested in. So I thought I would use some of the bullet points in the intro to chaos theory above that you just read to illustrate the possibilities. I’ll just pick a few of them.

  • The Butterfly Effect

We’ve all heard of this one. A butterfly flapping its wings in Brazil can cause a hurricane in China. This is a good one to remind us that it’s not always large sweeping changes that affect the world. In fact system is often designed to buffer large sweeping changes as part of its self-preservation mode.  For example, a massive deluge of rain can cause water to course ragingly through rivers and streams. But rarely do the rivers and streams change their course because of this. But a lone beaver working slowly on its dam can change the course of a stream in a couple weeks. Sure, small changes can just as well be assimilated by the Borg, but there is the possibility that small changes affecting the right variables can move mountains. And how much more often do we have the capacity and authority to make small changes rather than large ones?

  • Unpredictability

You cannot know well enough all the initial conditions and variables in a complex system to accurately predict long term effects. You have no choice but to be comfortable with the fact that the outcomes of your choices will be difficult to predict too far into the future. While you’ve basically been given a pass here to not know the future, the upshot of this is that you need to focus on more contained and visible short-term changes. You need to simply focus on the next single obstacle. Because if that works many of the initial conditions and variables will have changed, so any prior efforts you made to see far into the future have all been made pointless.  It’s like mapping sand dunes. It’s just pointless. So one thing at a time is actually a credible strategy. Just make the best you can with the knowledge you have available.

  • Feedback

Feedback has significant influence and impact on a complex system. Just look at the stock market. All the noise from media, rumors, boards of directors, etc., can have massive impacts on stock prices. The same thing happens in organizations. Pay attention to the feedback loops in your organization. I mentioned incentives as a big influence the other day. Whether monetary or attempts to please or not displease management, these feedback loops can totally skew behaviors for good or bad. Of course here’s an opportunity for more structured feedback loops, like PDCA. Find the right feedback points and you find your influence.

OK, you get the point. A seemingly unrelated discipline offers us insight on how to affect change. If chaos theory is not for you, look to another discipline. Go read about innovations in biology or artificial intelligence or space flight of whatever. Oh, the places you can go.


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