Okay, before November ends I want to point out the must-read article of the month in Harvard Business Review. It is by David Snowden and Mary Boone, titled "A Leader’s Framework for Decision Making." The article connects complexity science with management. Scientists have been exploring "complex adaptive systems" for some time now, and many have been applying the lessons to organizations. Some of the basics of complex systems (the article has a better summary):

• Large number of interacting elements
• Interactions are non-linear: mall changes can produce big impact
• Hindsight does not lead to foresight, because external conditions and systems constantly change.

This seems to clearly describe the world of organizations today, yet I often see leaders acting as if they are in simple systems, rather than complex. But the article goes further to add some richness to the simple/complex discussion by talking about a framework of four different kinds of "contexts" in which organizational leaders can find themselves: simple, complicated, complex, and chaotic.

I particularly like the difference between complicated and complex. Very few leaders would argue their world is simple. There may be portions that have simplicity (the example from the article is order processing and fulfillment; if something goes wrong you can usually figure it out and fix it), but the big picture is more complicated.

Complicated, maybe, but not complex. The complicated context, according to the article, is certainly more complex than the simple, but it still assumes that there is a clear relationship between cause and effect. These contexts are tougher and require more expert analysis and problem solving. But there is still assumed to be an answer. If you can just get the right expert in there, and gather the right data, and do the right analysis, you will be able to determine the right answer.

In complex contexts, however, the right answer cannot always be ferreted out using that kind of retrospective analysis. The system is dynamic, so you may be able to discern "instructive patterns," but you do that by probing the system, sensing what is happening, and then responding (not by analyzing all that data and determining the right answer).

Regular readers know I like to push back against the "data driven" movement, so I will go ahead and reassure my data-focused friends up front: I think gathering and analyzing data is critical in BOTH complicated and complex contexts. But it’s done in different ways. Too often we treat data as the secret ingredient that will allow us to control the future. You simply don’t do that in complex systems:

In this domain, we can understand why things happen only in retrospect. Instructive patterns, however, can emerge if the leader conducts experiments that are safe to fail. That is why, instead of attempting to impose a course of action, leaders must patiently allow the path forward to reveal itself. They need to probe first, then sense, and then respond.

I really like the idea of fine-tuning one’s radar to be aware of the difference between a complicated context and a complex one, and then adjusting one’s approach accordingly.