Back in the 15th Century, Leonardo da Vinci, the great genius of the Middle Ages, said that “simplicity is the ultimate sophistication.” Most modern managers would agree. Every good operation works hard to streamline its processes down to the barest essentials.
However, the world is a complex place and it’s only getting more so, which is why many management thinkers have been urging businesses to embrace complexity, to become, in effect, system thinkers rather than reductionists.
As Richard Straub noted in a recent article in HBR, that effort has largely failed and we shouldn’t be surprised. Executives are paid to be accountable and are understandably reluctant to give themselves up to the complexity Gods. In truth, complexity is not something we need to embrace, merely something we need to accept and manage.
What Is Complexity?
Before we can manage complexity, we first need to understand it and much of the literature on the subject obscures more than it reveals. In actuality, the term is used to refer to three very different things and if we are to understand complexity, we need to account for all three:
The Complexity of an Entity: Technically known as Kolmogorov-Chaitin complexity, the complexity of an entity is defined through the amount of information it takes to describe it. So a huge entity like the number googol (i.e. 1100) can, in fact, be much simpler than a relatively small prime number (like 842,293)
Good managers have an intuitive feel for this type of complexity and work hard to reduce it. Operational excellence is strongly correlated to the ability to simplify complex entities.
Nonlinearity: Most of the things we deal with in operations are linear. If we sell 10 widgets a month, we expect to sell 120 in a year. However, many important aspects of business are non-linear and that’s hard for many managers to accept, especially with respect to accelerating returns.
Nonlinearity can be extremely dangerous for an incumbent company faced with an disruptive competitor. What looks relatively small and inconsequential can get big in a hurry and upend even the most dominant of firms. Innovation researcher Tim Kastelle recently wrote a great post about this phenomena in connection with electric cars.
Emergent Complexity: This is probably the most confusing form of complexity, because unlike nonlinearity, it’s not simple matter of accounting for rates of change, but of understanding how interactions between entities (even simple ones, such as transistors or neurons) can give rise to something completely unexpected (like intelligence).
I think it was this type of complexity that Mr. Straub was referring to in his article and he points to some good reasons why managers haven’t embraced it. Namely, that managers like to be in control, the tools we’ve had haven’t handled complexity well and that the new technologies of non-human decision making are unnerving.
And he’s right, managers have not embraced complexity and I strongly suspect many never will. So rather than expecting executives to embrace complexity, what we should be doing is coming up with strategies for managing it.
Managers vs. Executives
Most managers didn’t start out by managing. They worked their way up and got noticed because they were able to execute. This often entailed mastering complex information and working within a specific context of people, processes and competitive environment. Not surprisingly, they feel confident in their ability to bring order to chaos.
However, managing is different than executing. To manage effectively, you need to account for that which is beyond your understanding. You have to lead people who have expertise that you don’t, operate in market situations that you did not foresee and evaluate opportunities which are uncertain.
So the first step toward managing complexity is to think like a manager rather than an executive (unfortunately, many never actually make that leap). Simply getting a promotion does not make you a manager. Until you are ready to take responsibility for that which you cannot control, you are just someone with a title, not a leader.
Micromotives and Macrobehavior
A particularly unnerving aspect of emergent complexity is that interactions between factors under our control can often lead to phenomena that is difficult, if not impossible, to foresee.
Nobel prizewinning economist Thomas Schelling was probably the first to identify this problem with his segregation model, in which even those who prefer to live in mixed neighborhoods (but not to be outnumbered) can give rise to extreme segregation.
Another example is the Mandelbrot set, which uses a simple formula to create almost unimaginable complexity as does Stephen Wolfram’s Class IV automata. There is no evidence that working with simple, understandable elements gives us any more control, only perhaps the illusion of control.
So another thing that managers will have to accept is that their job is not about nodes, but about networks. Just because they are adept at managing entities doesn’t mean they understand the interactions between them.
Becoming Less Wrong Over Time
Managers are trained to deal in “hard facts,” to be data driven. They are supposed to research the market thoroughly, analyze with statistical rigor and make informed, rational decisions. Good managers know their numbers.
Unfortunately, our numbers are always wrong. They tend to be backward looking, based on small samples and are often gathered in a shoddy manner. In fact, a recent study in the journal Nature found that a majority of cancer research could not be replicated. If that’s true of matters of life and death, how accurate do you think marketing studies are?
I’ve suggested that we take a more Bayesian approach to strategy, where instead of assuming that we have the answers, we strive to become less wrong over time. Good strategy is never being, it is always becoming.
Seek Simplicity, But Distrust It
So while I agree with much in Mr. Straub’s article, I don’t believe managers will ever embrace complexity to a great extent. Complexity, is messy and uncomfortable. It’s fine and well to enjoy thinking about complexity as an intellectual exercise, but when you are accountable for results, it’s a nuisance.
However, while embracing complexity may be quixotic, ignoring it is not an option. We can factor down entities to make them more manageable, account for a wide variety of variables in our analysis and even deploy the latest big data technology to ensure the most robust examination of known facts possible, but we’ll still come up short.
So we should, as Alfred North Whitehead suggested, seek simplicity, but distrust it. We need to take a network view, manage what we don’t understand and become less wrong over time. Simplicity, after all, is not so simple.
In order to manage effectively in the modern world, we must not only hold ourselves responsible for those things that are within our control, but also account for that which is not.