A while ago one of our consultants shared a copy of “Moneyball: The Art of Winning an Unfair Game” by the best-selling author, Michael Lewis. While not considering myself to be a hardcore 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.
If you’re not familiar with Moneyball, Michael 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 or 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 Mr. Sculley — and that’s okay 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.
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.” Billy 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 websites 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)
Michael Lewis shared an interesting story of how the Houston Astros asked sabermetrics consultants to analyze the effect of moving the Astrodomes’ fences in closer. They believed more home runs would sell more tickets. After performing the analysis, the consultants found that the Astros would actually lose more games as 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.
3. Culture eats strategy for breakfast
In 1999, John Henry, a successful data-driven billionaire who used statistics to take advantage of inefficiencies in the financial markets, acquired the Florida Marlins. Henry once wrote that “people in both [baseball and the stock market] operate with beliefs and biases. To the extent you can eliminate both and replace them with data, you gain a clear advantage.” Despite Henry’s avid following of sabermetrics and best intentions, he faced an uphill battle and succumbed to the prevailing practices in baseball. “For a man who had never played professional baseball to impose upon even a pathetic major league franchise an entirely new way of doing things meant alienating the baseball insiders he employed: the manager, the scouts, the players. In the end, he would have been ostracized by his own organization. And what was the point of being in baseball if you weren’t in baseball?” It can be difficult for marketing organizations to become more data-driven when the culture is fighting the transformation process every step of the way. You need a concerted effort — rather than just good intentions — to overcome organizational inertia.
4. Wrong metrics
When baseball metrics were first invented in the late nineteenth century, they were flawed. British-born journalist Henry Chadwick, who introduced many of baseball’s metrics, decided that walks were caused by pitcher mistakes and had nothing to do with the hitter’s expertise. As a result, the main metric for evaluating hitting performance — batting average - excluded walks, and it also failed to place any value on extra base hits. Billy Beane’s scouting staff placed higher value on different metrics — on-base and slugging percentage — which enabled his team to find discounted players who actually achieved what the Oakland A’s needed — more runs per game (regardless of how they got on base). How many marketers are just doing what everyone else is doing? Rather than chasing the KPI-du-jour or whatever their competitors are doing, online marketers need to determine what KPIs are right for measuring their business.
5. Data numbness
Influential sabermetrician Bill James was disappointed that his statistical craft was being equated more often with reciting arcane baseball stats than its intended purpose — gaining a better understanding of baseball. James stated, “I wonder if we haven’t become so numbed by all these numbers that we are no longer capable of truly assimilating any knowledge which might result from them.” Sometimes marketing organizations appear to overcompensate and start leveraging all kinds of metrics and KPIs, becoming numb in the process. It’s important for marketers to focus on a few KPIs to deepen their understanding and better seize optimization opportunities.
The data-driven revolution that Billy Beane brought to bear on the established world of baseball is a compelling story. The same changes are happening within marketing today. Just like there were inefficiencies in baseball, there are also inefficiencies in marketing. The rewards will go to the baseball managers and marketing managers who can take advantage of those inefficiencies. I’d highly recommend picking up this thought-provoking book even if you’re not a baseball fan. If you’re a fan of Brad Pitt and don’t have time to read another book right now, you can catch the upcoming Moneyball movie in September (check out the trailer). If you’ve already read Michael Lewis’ Moneyball book, I’d be curious to hear what insights you gleaned from it.
Five Data-Driven Lessons from Moneyball
If you’re not familiar with Moneyball, Michael 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 or 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 Mr. Sculley — and that’s okay 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.
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.” Billy 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 websites 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)
Michael Lewis shared an interesting story of how the Houston Astros asked sabermetrics consultants to analyze the effect of moving the Astrodomes’ fences in closer. They believed more home runs would sell more tickets. After performing the analysis, the consultants found that the Astros would actually lose more games as 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.
3. Culture eats strategy for breakfast
In 1999, John Henry, a successful data-driven billionaire who used statistics to take advantage of inefficiencies in the financial markets, acquired the Florida Marlins. Henry once wrote that “people in both [baseball and the stock market] operate with beliefs and biases. To the extent you can eliminate both and replace them with data, you gain a clear advantage.” Despite Henry’s avid following of sabermetrics and best intentions, he faced an uphill battle and succumbed to the prevailing practices in baseball. “For a man who had never played professional baseball to impose upon even a pathetic major league franchise an entirely new way of doing things meant alienating the baseball insiders he employed: the manager, the scouts, the players. In the end, he would have been ostracized by his own organization. And what was the point of being in baseball if you weren’t in baseball?” It can be difficult for marketing organizations to become more data-driven when the culture is fighting the transformation process every step of the way. You need a concerted effort — rather than just good intentions — to overcome organizational inertia.
When baseball metrics were first invented in the late nineteenth century, they were flawed. British-born journalist Henry Chadwick, who introduced many of baseball’s metrics, decided that walks were caused by pitcher mistakes and had nothing to do with the hitter’s expertise. As a result, the main metric for evaluating hitting performance — batting average - excluded walks, and it also failed to place any value on extra base hits. Billy Beane’s scouting staff placed higher value on different metrics — on-base and slugging percentage — which enabled his team to find discounted players who actually achieved what the Oakland A’s needed — more runs per game (regardless of how they got on base). How many marketers are just doing what everyone else is doing? Rather than chasing the KPI-du-jour or whatever their competitors are doing, online marketers need to determine what KPIs are right for measuring their business.
5. Data numbness
Influential sabermetrician Bill James was disappointed that his statistical craft was being equated more often with reciting arcane baseball stats than its intended purpose — gaining a better understanding of baseball. James stated, “I wonder if we haven’t become so numbed by all these numbers that we are no longer capable of truly assimilating any knowledge which might result from them.” Sometimes marketing organizations appear to overcompensate and start leveraging all kinds of metrics and KPIs, becoming numb in the process. It’s important for marketers to focus on a few KPIs to deepen their understanding and better seize optimization opportunities.
The data-driven revolution that Billy Beane brought to bear on the established world of baseball is a compelling story. The same changes are happening within marketing today. Just like there were inefficiencies in baseball, there are also inefficiencies in marketing. The rewards will go to the baseball managers and marketing managers who can take advantage of those inefficiencies. I’d highly recommend picking up this thought-provoking book even if you’re not a baseball fan. If you’re a fan of Brad Pitt and don’t have time to read another book right now, you can catch the upcoming Moneyball movie in September (check out the trailer). If you’ve already read Michael Lewis’ Moneyball book, I’d be curious to hear what insights you gleaned from it.