Moneyball: How Data Trumps Expertise
Posted by James Marland on Thu, Oct 13, 2011 @ 09:00
Moneyball asks the question: can a statistics-crunching machine really understand baseball better than a man?
For decades it had been accepted that spotting potential baseball stars was an art best performed by veteran scouts whose instincts had been elevated to near mystical levels after years on the road watching endless college and high school games. An alternative approach, pioneered by the Oakland As in 2001, relied on computer-driven analysis of previously neglected statistics to identify players that were under-valued and ignored by other managers.
The A’s started winning with the resulting team of misfits, and fans hailed the manager (played by Brad Pitt in the movie) as a visionary; a card counter in a casino full of fortune-tellers. The availability of in-memory analytical tools had suddenly brought advanced analysis into the baseball back office.
Those same tools can provide a similar winning strategy to Pricing Managers, allowing you to pass better financed rivals in the quest for profits. Instead of pouring over on-base percentage and slugging percentage, pricers are cranking up their analytical engines to look at Price Yield, Cost-to-Serve ratios, Price Realization, Defection Risk and a host of other metrics to come up with the optimal plays. Gross Margin? That’s old school.
Trouble is the cat is out of the bag and everyone understands the principles – you need to do this before your competition does. You don’t have Brad’s good looks to fall back on.