Cross-posted at Philosophy on the Mesa.
The excessive risk-taking by banks and investment firms that caused the economic meltdown was in part the result of the skewed incentive structure of their compensation packages. Because their compensation was based on how well their company’s stock did over the relatively short term, they had every incentive to take on excessive, long-term risk if it would boost their short-term profits.
What was bad for the health of the firm was good for the stock trader or manager who pocketed immediate benefits.
NPR’s Scott Horsley, referencing a recent NY Times article by Michael Lewis on NBA star Michael Battier, compared Wall Street’s approach to compensation to compensation based on individual statistics in the NBA. Players often take poor shots in order to pad their stats, even though passing the ball would be better for the team, and many players virtually ignore defense, an essential part of the game, because it is more difficult to represent in statistical measures. If a player’s compensation is dependent on individual statistics only, they are rewarded for actions that often hurt the team.
These skewed incentives indicate a disturbing trend in contemporary society. We tend to form beliefs around data that is pervasive only because it is easy to acquire. It is easy to count and assign individual responsibility for baskets or sales minus expenses. These are convenient ways of keeping score.
However, the fact that a bit of data is easy to gather does not mean that it is providing a comprehensive, accurate measure of the health of the firm (or a basketball team). Stuff that isn’t easy to measure is not part of the calculation.
So why do hard-working, serious people take the easy way out when trying to measure performance? Isn’t it obvious to management (whether in sports or business) that the way the measure performance can be incomplete?
In a recent post, I argued that our economic problems were the result of an epistemological crisis. Our Wall St. wizards created lots of investment vehicles they didn’t understand and could not analyze.
But this tendency to form beliefs and hence policies around easily accessible data suggests another epistemological dimension to this crisis that explains why we take the easy way out.
Jerry Z. Muller writes:
From the point of view of top management, the diversity of operations means that executives were managing assets and services with which they have little familiarity. This has led to the spread of pseudo-objectivity: the search for standardized measures of achievement across large and disparate organizations. Its implicit premises were these: that information which is numerically measurable is the only sort of knowledge necessary; that numerical data can substitute for other forms of inquiry; and that numerical acumen can substitute for practical knowledge about the underlying assets and services. A good deal of our current economic travails can be traced to this increasing valuation of purportedly objective criteria, so denoted because they can be expressed and manipulated in mathematical form by people who may be skilled at such manipulation but who lack “concrete” knowledge or experience of the things being made or traded.
This is a theme that I emphasize in Reviving the Left. The pursuit of objectivity, and the resulting abstract representations, often leave out crucial data we need in order to act well, especially where human beings are concerned. Sensitive, situational knowledge that sometimes involves feelings and intuition is essential for guiding human action, but it is not well represented by mathematical models. Yet the “cult of accountability” is fast spreading throughout society. From finance and basketball to education and health care, every activity is being measured by a metric that may not capture crucial components of the activity—with sometimes disastrous consequences.
