You’ve been promised collective intelligence, but there’s more. Complexity is both the problem and -- if properly understood -- the solution.


Two Forces Compelling a Business Shift

So there are these two things going on. The first you’ve definitely heard of -- it’s the great reawakening of the white-collar and consumer world as their value and participation and voice are released from the anonymity of the command and control corporate model thanks to nifty new social technologies.

The second is about the exponentially increasing complexity of the world. Everything that touches anything sets off another thing and so on. Social is accelerating complexity and vice versa. The very best of us and even our technology are daunted by the challenge of understanding issues and taking action in such an environment.

This is why the future has become ever more unpredictable, and engaging in planning is generally a highly optimistic pursuit. [There’s a third -- all this reawakening stuff has nudged us to look hard at some things that had been left unexamined for too long, like leadership, collaboration and certain exploitative forms of capitalism, but that’s a different discussion.]

The Big Shift & The Path to Social Business Enterprise 2.0

In his classic work, "The Structure of Scientific Revolutions," Thomas Kuhn describes a period of “crisis” that precedes a scientific revolution. The crisis is a period where a field of math or science becomes dramatically more complicated, while yielding diminishing, incremental returns.

If John Seely-Brown and John Hagel are right, and the average Return on Assets has dropped by 75% since 1965, then we may be seeing an analogous crisis in business that leaves us ripe for a business revolution (they call it the Big Shift).

Business is changing to a new model -- Enterprise 2.0 -- both because people are demanding it AND because a centralized command and control model that uses process and efficiencies of scale to achieve superhuman feats has limits to what it can do.

A new model of applying networks of sensors and capabilities (people) onto complex problems to achieve uniquely human feats, can solve problems that hierarchies cannot. Calling it “social” business is missing half of the point. Business isn’t going “social” because it wants to hold hands and sing Kumbaya.

[Note - I’m officially, if temporarily, moving back to Enterprise 2.0. I dislike the term Social Business, and I’m taking my ball and moving on, until such time as someone finally coins a term worth using.]

Complexity Beyond Reductionism

Our gut instincts tell us, based on 400 years of Newtonian reductionism, that if only we work hard enough, with enough intelligence and discipline, nothing is beyond our ability to deconstruct it into its component parts. Everything can be understood by examining how those pieces fit together. Our notion of business and process design (among many other things) depend on this idea, but it is -- if not exactly wrong -- limited.

The reason strategy is hard, the reason R&D is hard, the reason marketing, support, sales, innovation, operations, design and gun control are hard is because they are multifaceted challenges that involve many interrelated, unpredictable, often external forces.

When you wade into address these challenges, adding and changing dynamics, they become even more complex.There is no definitive right or wrong answer, there is only better and worse.

These types of problems are often referred to as “wicked.” Wicked problems defy systematic, top-down solutions. Our Command and Control organizations have done many things well, but we are now entering an era dominated by the kind of problem they don’t do well.

There are well defined mechanistic processes going on within, but they are just a part of a story. The rest of the story is complex. The rest of the story needs a mesh of minds -- a complex system -- to address.

But complexity makes people nervous. Its not part of our basic education. By definition, complex problems are hard or even impossible to understand. BUT is understanding really necessary to progress? Surprisingly, no.

1. Knowledge-less-ness: We can find solutions to problems that we do not (and can not) “understand”

There is a field of math/computer science known as Computability Theory (I hovered here as an undergrad). It’s the study of how to solve logical and mathematical puzzles, how to classify these puzzles into different types, based on their difficulty, and how to rank solutions by how efficient they are. Solutions usually involve clever methods for changing a hard problem to look like an easier problem.

There is a class of problems, however, known as NP-Complete. (You do not care what that means for the purposes of this discussion, but Wikipedia has a decent definition if you really must.) Let’s just say that these problems are the ones where you can’t find a nice tidy algorithm for efficiently solving the problem.

One of the canonical examples of NP-Complete problems is known as the Traveling Salesman problem. [You can tell I took a math course in college because I can say “canonical example.”] The traveling salesman problem goes like this. A salesman has to visit each of a list of cities exactly once. What is the shortest path he can take through them?

It turns out that it is impossible to simplify this problem using traditional analytic methods, and the only way to find out the optimal answer is to try every possible combination of cities, check how long it takes, and pick the shortest. This is no big deal if the number of cities is 5 or 25, but the effort required to solve the problem grows exponentially as the number of cities grow. We have no clever solution.

So I’m eyeball deep in this stuff, and I read an article -- a little “Computer Recreations” column in Scientific American by A K Dewdney, describing Flibs. It was a mind-altering, possibly life-altering article.

Flibs solve the traveling salesman problem. Easily.