Closest Point of Approach

Closest Point of Approach

Moneyball

The road to hell is paved with intentions. Not just good ones.

Chand Sooran's avatar
Chand Sooran
Dec 31, 2025
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“The strategy for the discoverers and entrepreneurs is to rely less on top-down planning and focus on maximum tinkering and recognizing opportunities when they present themselves. So I disagree with the followers of Marx and those of Adam Smith: the reason free markets work is because they allow people to be lucky, thanks to aggressive trial and error, not by giving rewards or “incentives” for skill. The strategy is, then, to tinker as much as possible and try to collect as many Black Swan opportunities as you can.”

- Nassim Taleb, The Black Swan

A complex system is unpredictable.

Bureaucracy is full of experts who use specialized, narrow knowledge to predict outcomes and to design processes that benefit their sponsors. In a democracy, their sponsors are (presumably) the people. In a company, their sponsors are (presumably) the shareholders. In a non-profit, their sponsors are (presumably) the donors.

Yet, we do live in a complex, adaptive system. More accurately, we exist in multiple, overlapping complex adaptive systems.

Here’s Farnam Street quoting Taleb, again from The Black Swan, on complexity:

“I will simplify here with a functional definition of complexity—among many more complete ones. A complex domain is characterized by the following: there is a great degree of interdependence between its elements, both temporal (a variable depends on its past changes), horizontal (variables depend on one another), and diagonal (variable A depends on the past history of variable B). As a result of this interdependence, mechanisms are subjected to positive, reinforcing feedback loops, which cause “fat tails.” That is, they prevent the working of the Central Limit Theorem that, as we saw in Chapter 15 , establishes Mediocristan thin tails under summation and aggregation of elements and causes “convergence to the Gaussian.” In lay terms, moves are exacerbated over time instead of being dampened by counterbalancing forces. Finally, we have nonlinearities that accentuate the fat tails.

‘So, complexity implies Extremistan. (The opposite is not necessarily true.)’

We all depend on one another. Our actions affect our environment in trillions of imperceptible ways. Not only in the here and now, but across time. These interdependencies vary in influence over time and space. Understanding this would require almost infinite computing power. Making exploitable predictions is the stuff of science fiction.

Bureaucracy succeeds when it is localized. We can make policies about a finite, limited set of interactions. When it is hyper-specialized and not influenced by values, it is more accurately described as process engineering.

Values here means interests. Some people benefit from the policy while others suffer; it is a transfer of some sort of resource or power or status.

One example of process engineering might be a company optimizing the way it pays its vendors. They automate the process, reducing the cost and energy involved in executing this vital but unglamorous task.

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When our bureaucratic betters make policy costing hundreds of billions of dollars, affecting millions of people, and spanning years, there will be unintended consequences. That is the only thing of which we can be sure.

One ironic consequence of all this bureaucracy is that, even as it is meant to improve the lot of the greatest number of stakeholders, it may lead to perverse outcomes.

Healthcare policy designed to push people into insurance coverage ends up pricing them out of it or leading to an equality of poverty in outcomes. Policy to help the economy recover from a recession or financial crisis promotes instead a dramatic increase in inequality that dwarfs the marginal improvement in what would have been an inevitable recovery. A company’s decision to have a strong human resources department ends up crushing innovation as people avoid taking risk.

The road to hell is paved with intentions. Not good intentions. Just intentions.

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