Business Insight Zone

Michael Lewis’s terrific book Moneyball is as much about management and innovation as it is about baseball. So whether you’re a baseball fan or not, please stick with me for a second as I talk about one of Moneyball’s lessons.

In the book, Lewis describes how Billy Beane, the general manager of the Oakland Athletics, identified on-base percentage (OBP) as the key underpriced asset for major-league hitters. If you wanted a hitter with a high batting average or lots of home runs or lots of runs batted in (RBIs), you paid a premium for that hitter. But you could get players who lacked those things — yet who had high OBPs — on the cheap.

(For the non-baseball fans in the crowd, the crudest definition of OBP is this: it’s the percentage of the time that a batter doesn’t make an out, regardless of whether he walks, gets hit by a pitch, drives a ball into the centerfield seats, or whatever.)

Why OBP?

What made OBP so special, back in the late 1990s when Beane isolated it as a key metric? Two things — one positive and one negative:

1. The positive: OBP is the hitting statistic that maps most linearly to runs scored. Higher OBPs translate directly to more runs scored — in all settings, and regardless of the types of hitters involved.
2. The negative: For a variety of reasons, OBP is hardly as glamorous as the “triple crown” statistics of batting average, home runs, and RBIs. Therefore it was routinely overlooked as a differentiating factor for hitters . . . even though the list of the top 50 all-time OBP leaders includes a high number of the top 50 all-time hitters.

A little more on that second point: The home-run binge that ran from the mid-1990s through the mid-2000s demonstrates the abiding fascination of baseball fans for the home-run hitter — a point made initially, and most forcefully, by one George Herman Ruth. And over the course of many years, MVP voters have disproportionately rewarded the hitters considered “run creators” for their high numbers of RBIs.

The old love affair with batting average.

Across the game’s history, compiling an average of .300 — that is, getting a hit in three of every 10 at-bats — has been seen as an unquestioned mark of a good hitter, regardless of whether the hits were singles or doubles or triples or homers. And in the early days of the game, that made sense: extra-base hits were hard to come by and walks were regarded as an aberration rather than a beneficial outcome in themselves, so batting average really did express a lot about a hitter’s worth.

In Honus Wagner’s heyday, runs were hard to come by,
and extra-base hits were much rarer than today.

Thing is, the math changed in the 1920s, when Babe Ruth and other power hitters started showing a more modern approach at the plate: more patience, more power. The thinking should have changed, too, so that the emphasis fell to OBP and slugging average (essentially, what fraction of a base a batter averaged per time at-bat). But the old triple-crown stats — batting average, homers, RBIs — were already firmly engrained, they were easy to grasp, they were easy to compute, and they seemed to capture enough information for evaluating a hitter.

What helps us WIN?

Fast-forward seven decades to Billy Beane. He and his mentor, Sandy Alderson, understood that they would never have the budget to hire proven home run champions, RBI champions, batting champions. Yet they could find out-of-the-way hitters who didn’t do anything flashy in the triple-crown categories, but who quietly racked up the OBP, and therefore quietly — and cheaply — helped a team win.

The formula worked. Although the Athletics never made it to the World Series in the 2000s, for several years running, they made the playoffs alongside teams with payrolls two and three and four times as large. They did this in large part because they abandoned the old, easy-to-measure, not-very-meaningful ways of evaluating hitters, and replaced them with smarter, more-meaningful, out-of-the-ordinary ways.

Now, here comes the business application: What do you measure in your organization? How do you evaluate your people, especially in roles outside of sales that often lack clear yardsticks?

Do your measures have real meaning?
Or are you just continuing to measure what you’ve always measured?

Many companies, in my experience, have their own version of “batting average” that they like to point to, even though there’s some more-meaningful “OBP” metric that they should be using.

What about you?

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(Moneyball cover via Wikipedia; Honus Wagner image via Wikimedia Commons.)

Category: Management, The business of sports