Seth Godin describes an example today on his blog that shows that “just because you can measure it doesn’t mean it’s important.” It reminded me of a great book about measurements – indeed, one of the best non-fiction books I’ve ever read.
Have any of you read Michael Lewis’s book, Moneyball: The Art of Winning An Unfair Game? (Even if you couldn’t care less about sports, you’ll enjoy this book.) It’s a fascinating story that provides a perfect example of how “knowing what to measure” can have a dramatic impact on an organization’s results.
A few years ago, the general manager of the Oakland A’s, Billy Beane, set out with some MIT stat geeks to figure out what player statistics correlate most closely to “scoring runs.” What they discovered enabled them to compete on a different level in the game of selecting players. While every other team pursued players with high “batting averages” and “home run totals,” the A’s had figured out that these stats weren’t actually the most important when seeking players who would help you WIN (which is, of course, the ultimate goal).
They learned that “high on-base percentage” and “high slugging percentage” were the statistical qualities that contributed most to winning games — and that many of the players with the best stats in these areas were either overlooked by other teams (who had their eye on the wrong measurements), or undervalued in terms of salary. So, on one of the smallest budgets in all of baseball, the A’s put together a team that competed for the World Championship several years in a row.
How’d they do it? They asked the right questions, did some analysis, and figured out the right things to measure to identify players who could help them achieve their ultimate goal of winning – then they adjusted their game plan accordingly.
What if you could engineer a surge in your results in your own field, similar to the A’s surge in victories, by starting to measure the right things?