I think there is an important parallel between urban travel and social business. There is a now well-understood but counter-intuitive law in traffic engineering, called Braess’ paradox, where closing streets can lead to better traffic flow.
The brainchild of mathematician Dietrich Braess of Ruhr University Bochum in Germany, the eponymous paradox unfolds as an abstraction: it states that in a network in which all the moving entities rationally seek the most efficient route, adding extra capacity can actually reduce the network’s overall efficiency. The Seoul project inverts this dynamic: closing a highway—that is, reducing network capacity—improves the system’s effectiveness.
Although Braess’s paradox was first identified in the 1960s and is rooted in 1920s economic theory, the concept never gained traction in the automobile-oriented U.S. But in the 21st century, economic and environmental problems are bringing new scrutiny to the idea that limiting spaces for cars may move more people more efficiently. A key to this counterintuitive approach to traffic design lies in manipulating the inherent self-interest of all drivers.
A case in point is “The Price of Anarchy in Transportation Networks,” published last September in Physical Review Letters by Michael Gastner, a computer scientist at the Santa Fe Institute, and his colleagues. Using hypothetical and real-world road networks, they explain that drivers seeking the shortest route to a given destination eventually reach what is known as the Nash equilibrium, in which no single driver can do any better by changing his or her strategy unilaterally. The problem is that the Nash equilibrium is less efficient than the equilibrium reached when drivers act unselfishly—that is, when they coordinate their movements to benefit the entire group.
The “price of anarchy” is a measure of the inefficiency caused by selfish drivers. Analyzing a commute from Harvard Square to Boston Common, the researchers found that the price can be high—selfish drivers typically waste 30 percent more time than they would under “socially optimal” conditions.
The solution hinges on Braess’s paradox, Gastner says. “Because selfish drivers optimize a wrong function, they can be led to a better solution if you remove some of the network links,” he explains. Why? In part because closing roads makes it more difficult for individual drivers to choose the best (and most selfish) route. In the Boston example, Gastner’s team found that six possible road closures, including parts of Charles and Main streets, would reduce the delay under the selfish-driving scenario. (The street closures would not slow drivers if they were behaving unselfishly.)
It turns out that you don’t have to actually close streets off to cars to get these effects, you can institute what is called ‘shared streets’, where traffic lights and markings are removed, forcing drivers to operate on a more social basis: making eye contact with other drivers, bicyclists, and pedestrians. These approaches share a common basis: movement in the system requires multilateral agreement. In Braess’ world, unilateral optimization is blocked, and in shared streets, social interaction is made necessary.
My belief is that this is quite like the adoption of social principles in business.
The equivalent to these traffic analogies in social business is pretty direct. The most important decision in a connected world is deciding who to follow. And by picking people to follow, you are defining your pattern of connection to everyone else in the network, which is analogous to laying out the streets and boulevards through which information finds its way to you. The equivalent to shared streets is transitioning to open social communication models, where we are operating at social scale, eye-to-eye, not simply following the directions of traffic signals, without considering the other people we share the streets with.
And the paradox in social is this (Boyd’s Law): that by being willing to put aside personal goals momentarily and being willing to respond to others’ requests for help, we increase the productivity of the network as a whole. Since when I help someone make progress, they and the group they are working with then make progress, collectively. And that radiates outward, cascading across the entire network. This is like Braess’ paradox, since we drop the concept of the more selfish individual productivity as the highest good and instead aim for network productivity instead.