Last week the movie Moneyball was released, starring Brad Pitt. I have not yet seen the movie, but I did read the book, and believe me, it tells an extremely compelling story. In the late 1980's/early 1990's the manager of the Oakland Athletics baseball team chose to throw away the old manuals as to how teams are run and seek to find the answers in data - statistics about player's performance. So he set out to hire analysts and statisticians - with very little background in pro baseball - to study the game from the ground up. It turns out that many of the old rules were wrong - and concluded that an entrely different set of overlooked peformance metrics were the correct ones to use. The manager set about recruiting players based on these new statistics and - voila - the team excelled in the seasons thereafter, blowing past teams with 3X their payroll.
A great come-from-behind-by-ignoring -conventional-wisdom story to be sure. But what lessons does this hold for those of us on the front lines of business strategy and decision-making? Answer: a lot! Let me tick a few of them off here:
1. How many industries are there that apply the same old business rules over and over again without question? Knowledge and experience is vitally important, but shouldn't such rules be tested every now and then to determine if shifts in the marketplace have changed the game?
2. What kind of person is best suited to build models of companies/industries? Time and time again the answer keeps coming back...it is the person with very little background in that industry! Only such a person will ask the naive (and probing) questions needed to uncover important patterns in the data.
3. Moneyball was made possible because of MLB's inherent devotion to data. I can pretty much get any statistic I want about a player's or team's perfomance for free and within a few minutes. They measure EVERYTHING...the temperature the day of the game, who sang the national anthem, attendance, concession sales. They conclude, correctly, that measurement is (almost) free and then measure virtually every parameter.
The real star of Moneyball was not Brad Pitt, but rather, a little known statistical method called Data Envelopment Analysis or DEA. In short it is a "fair value" way to calculate the efficiency of production units, in this case baseball players, but could just as easily be applied to sales professionals, retail branches, or production plants. Too bad DEA doesnt get co-star billing.
How many companies are trapped in the traditional ways of looking at data? How many could reap the rewards of a clean slate approach to performance measurement? Could this be your company?
Let us all learn from the Moneyball story and take the kind of bold action necessary to take our firms to that next level of performance. Have the conviction to shrug off the naysayers and defy conventional wisdom. A 20 game winning streak could be your reward.
Play ball!