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Brent DykesDirector of Industry ConsultingAdobe Systems |
A while ago one of our consultants shared a copy of Moneyball: The Art of Winning an Unfair Game, by best-selling author Michael Lewis. Though I don't consider myself to be a hard-core baseball fan, this consultant still encouraged me to read the book. He felt it highlighted common problems that both companies and industries struggle with when it comes to becoming more data-driven.
In case you’re not familiar with Moneyball, Lewis chronicles the surprising success of the small-market baseball team the Oakland Athletics, which competes against large-market teams with much deeper pockets, such as the New York Yankees and Boston Red Sox. In order to maximize his player budget (a fifth of the size of larger teams’ budgets), Oakland A's general manager Billy Beane broke with tradition and applied an analytical approach to baseball’s flawed and subjective scouting system. His staff drafted young, inexpensive players and obtained unwanted, affordable veterans with high on-base percentages, as well as unorthodox pitchers who generated a lot of ground outs. Using statistical analysis known as "sabermetrics," the Oakland A's were able to level the playing field and proceed to outsmart and outperform much richer teams. All of the MLB teams had access to the same data; however, the Oakland A’s identified inefficiencies in how the data was being used and capitalized on them.
Parallels With 'Marketingball'
As I read the book, I made five observations about baseball’s challenges that paralleled marketers’ struggles to become more data-driven. Like baseball, marketing has a history of being surrounded by data, but failing to leverage it very effectively. Former PepsiCo and Apple CEO John Sculley is attributed with the statement, “No great marketing decisions have ever been made on quantitative data.” No doubt, many marketers would agree with him--and that’s OK because this traditional marketing viewpoint gives data-driven marketing organizations an opportunity to fly under the radar--like the Oakland A's--and gain market share from less-savvy competitors. Here are my takeaways.
1. Intuition Instead Of Analysis
Traditional baseball scouts relied on several sight-based scouting prejudices: “The scouting distrust of right-handed pitchers, for instance, or the scouting distrust of skinny little guys who get on base. Or the scouting distaste for fat catchers.” Beane’s staff went against baseball scouting’s conventions by evaluating young college players (who had more data available than high school players) not by what they looked like, or what they might become, but by what they had done. Marketers have their own prejudices and gut-driven practices. Too many clever marketing campaigns have been launched without any consideration of what other similarly clever campaigns accomplished. Too many Web sites have been entirely redesigned (at significant cost) with no more than a quick glance of reports showing their past performance.
2. Data To Justify Decisions (Not To Inform Decisions)
Lewis shared an interesting story about how the Houston Astros asked sabermetrics consultants to analyze the effect of moving the Astrodome's fences in closer. They believed more homeruns would sell more tickets. After performing the analysis, the consultants found that the Astros would actually lose more games because their opponents were more likely to hit long pop flies. Suddenly, the Houston Astros wanted the consultants to cover up the information: “They didn’t want the information to inform the decision. They’d already made the decision.” The same practice of justifying or defending a decision with data happens in marketing. For best results, analysis should precede marketing decisions and inform them--not the reverse.
Next: Overcoming organizational inertia Florida Marlins-style.
