Fuzzy Signals

Hidden Simplicty in Complex Worlds

Check out the Spring 2004 issue of Strategy + Business. Lots of interesting stuff, including a Thought Leadership interview with Philip Bobbitt, the chap I've been mentioning who wrote The Shield of Achilles. (Notes on this weighty masterpiece are in "The Problem: The Subtlety of the Problem" blog entry.)

Here is another highlight, "Power Laws & the New Science of Complexity Management" by Mark Buchanan. He is the author of Nexus: Small Worlds and the Groundbreaking Science of Networks (2002) which is one book of many in recent years popularizing network theory.

Understanding social networks and network dynamics, a subset of complexity science or non linear dynamics, became fashionable after Al-Queda came crashing through our perceptual radar screen. Networked organizations turn out to have a very different logic than hierarchical ones! Of course, this field of study has been around for a long time and has cousins in many different scientific and social science disciplines, which makes understanding and aggregating the collective insights generated thus far a big project. Even so, we need more people digesting and making-sense of the implications of this emerging literature for business and policy. We need to start translating these ideas into practical tools and processes so that people can make better decisions for the future.
(Another large project waiting to be funded.) This article is a baby-step towards that end, and here are some things that stood out for me:

"Does the specter of ever-increasing complexity mean senior executives must succumb to rising unpredictability, uncertainty, and loss of managerial control? Not necessarily. During the three decades of its development, complexity science has not only chronicled the phenomenon of interdependence: It has also opened paths to understanding and handling its challenges. Although complex systems are frequently unpredictable — inevitably so, in many instances — they also exhibit precise regularities. Relatively simple patterns, known as power laws and observed in disparate settings from astrophysics to evolutionary biology, as well as in  human society, suggest strategies by which well-managed organizations can deal with uncertainty and navigate the discontinuities of contemporary business.

Modern science has moved well beyond a fixation on exact prediction and control; it has learned to accept unpredictability as an unavoidable and, at times, even beneficial aspect of the world, as a resource that can sometimes be harnessed. Businesses can also learn to adapt to complexity, in ways that can help them both reduce risk and expand opportunities."

Buchanan then goes on to describe several failures, such as the infamous sinking of Long-Term Capital Management (LTCM), attributing their demise to relying too much on narrow risk assessment tools such as "VaR". These tools are increasingly failing us because their underlying assumptions are based on "normal" distributions or bell-curve statistics where unusual events are very rare and deviate from the mean. ( The Economist recently covered similar ground in their "Survey on Risk", Jan 22/04.) Bell-curves work best in describing predictable realities, when the components of the system are acting independently from each other. But many systems in life are complex and interdependent and full of unexpected shocks and events. These systems tend to follow power law curves with "fatter tails". (There is a nice graph showing the difference.)

"Power laws reflect a pattern of organization and change that is typical for complex systems. Hence, familiarity with their properties offers some clues to the expected character of any complex system — including the modern business environment. Systems that follow power laws defy our intuitive expectations in surprising ways."

All this means is that large events take place far more often than one would expect. "Large disruptive events are not only more frequent than intuition might dictate, they are also disproportionate in their effect." Not recognizing these kinds of dynamics is one of the main reasons why our risk assessment tools are so weak.

And later on...

"Learning to deal with discontinuity requires more than mere diversification or efficient exploration of possible products, of course. It often — if not always — means that individuals and organizations face the difficult task of thinking differently; of breaking habits and questioning long-standing conceptual and cultural commitments. David Snowden, director of IBM’s new Cynefin Centre for Organisational Complexity in Cardiff, Wales, points out that “the entrainment of thinking” is a common problem. Ideas and practices that have proven effective in the past become akin to accepted norms; they acquire inertia, and often for a very good reason. On-the-fly experimentation in the real world is a dangerous thing; hence, we naturally cling to ideas that have worked before. “We do this in order to survive,” says Mr. Snowden. But this pattern of behavior also leads to serious maladaptation in times of rapid change and crisis; it is most dangerous precisely during those moments of discontinuity that define the critical episodes of change in most complex systems. "

Scenario thinking, my stock and trade, is part of the solution here, which Buchanan doesn't mention. (I'll be sure to ping him about this.) If done well, scenario thinking is an insurance policy against big surprises. Unlike conventional methods, scenario thinking is a more robust risk assessment tool because it puts those decisions within a broader context, including discontinuities and uncertainties as well as things that are "locked in" or given—obvious drivers that people need to prepare for regardless of what future emerges. Most risk tools just drop the uncertainties off the table, and shy away from anything not quantifiable. Yet many (most) things requiring intelligent foresight are unquantifiable because historical patterns are not reliable predictors of future developments.

What I find most intriguing, however, is the potential of complexity modeling (and power law analysis) to advance the scenario methodology and practice, and by extension, our ability to help the people make better decisions for the future. For starters, this thinking may help us better identify and assess "predetermined elements" or "givens", the other rather neglected building block of the methodology. Today most practitioners focus on framing the uncertainties, which is what was needed at the time, a time when hubris about predicting the future still reigned supreme. Framing uncertainties paradoxically helps us anticipate the future better. But Pierre Wack, one of original gurus within Royal Dutch Shell, was primarily interested in given. Unearthing deep structural insights was exactly the kind of strategic advantage he was looking for. Now, there is a school of thought that's highly suspect of "givens" because they believe that these are epistemologically impossible—that the only certain thing in the future is uncertainty. I agree with this view beyond a certain time frame. But within certain parameters and with a better understanding of how complex systems work, we may be able to underneath a hidden simplicity or structural dynamic that will be predictable. We already do this with systems dynamics, but what if we can get some empirical legs to this as well? Again, there will be resistance to this, but I think it's an important place to look to evolve the foresight practice. I think Pierre Wack, if was alive today, would be most intrigued with this emerging field which may help us describe our reality much better than our current mental map.

Posted by nicole at March 6, 2004 09:49 AM