Posted by Ryan on 22 Jul 2008 12:28 am. Filed under General Business
For the first blog entry ever in the history of the story of my life, I’ll talk about something that is of great interest to me. I’ve been on this kick lately of reading business books related to social economics and statistics. It started with the usual suspects of Freakonomics and The Tipping Point and has grown from there. I received a great recommendation from a VP at Amazon (yes, that’s a little title-dropping) to read Moneyball by Michael Lewis. Here is the link even though I won’t receive any commission (thank me later, Amazon).
My main takeaway from the book is about looking for ways to use data more effectively to make better decisions. Even though Moneyball focuses on baseball, a sport which I am not a big fan of, it is nonetheless highly entertaining and a valuable read. One of the main characters of the book is Bill James, a big baseball fan who started looking for a more reliable way to predict how many games a baseball team will win in a season. Baseball is a sport that lends itself to this type of analysis since each team plays 162 games a season, and each game lasts many, many (sometimes too many) innings during which tons of measurable events occur. A virtual pioneer, James discovered the most important drivers of scoring runs, statistically determined the best coaching strategy for all situations, and developed formulas that more reliably measured an individual player’s contribution to a team’s victories. By examining the data from the game itself, these great insights were revealed to him.
The most amazing part of this story is that NONE of the so-called baseball experts analyzed the game in this way. I doubt many of them had even considered it since this kind of thinking takes a truly insightful person. Baseball experts relied on conventional wisdom and “gut” feelings to evaluate players and decide on strategy. Among the fallacies revealed by the data was that a sacrifice bunt or fly is actually NEVER the right move because protecting an out is a team’s most valuable play. James also showed the myth of the “clutch” hitter–there is no such thing statistically speaking–and that relief pitchers are extremely over-valued.
I could go on and on about what James found in the data that the so-called experts thought was “right” for years and years, but there are a few other points that I wanted to make. First, after James’ ideas made it into baseball circles, they were dismissed as coming from someone outside of the baseball circle and therefore not valid. How could anyone who hasn’t played baseball possibly tell the experts something they didn’t already know? Years and years of clubhouse experience had supposedly shown the experts how to successfully evaluate and draft the best players–even though the experts were right about only 10% of the time. However, one baseball exec did take notice (Billy Beane of the A’s) and used methods based on James’ work to evaluate and draft players, and direct the team’s Manager in strategy. This explains why the A’s are one of the most successful teams in baseball despite their tiny payroll when compared with the giant payrolls of Mets, Yankees and Cubs. Using these methods they drafted players that didn’t even appear on other teams’ radars. There was one problem, however. Once these players became all-stars, as the methods predicted, the A’s couldn’t afford to keep them anymore.
That’s where the Boston Red Sox recent success comes in. If anyone wonders how 28-year-old Theo Epstein became the GM of one of the most popular teams in baseball (and sports), it was because Billy Beane turned down the offer and Epstein was one of the few others who knew how to use James’ ideas to win games. However, the difference between the A’s and the Red Sox success is as follows. Because the A’s had a small payroll, they had to evaluable minor league players–the only players they could afford. Although the statistical methods they used increased the probability of selecting players most likely to generate wins, using minor league data isn’t as reliable as using major league data. It isn’t apples to oranges, it’s more like apples to pears. Because the Red Sox could afford to sign the big players, who had accumulated major league statistical data for analysis, Boston could use this more reliable major league data to determine which players would generate the runs required to win enough games. Some might say that once in the majors it is easy to see who is good. That is true, but just because someone is good doesn’t always mean they contribute to wins, and that is what these methods reveal. Boston selected the all-stars that would help them win, not just the all stars that were “good.”
So that’s the story of Bill James and Moneyball. It really is an “outside of the box” type of adventure. I love stories about people going against established thinking to create something truly unique and successful. So in business or in anything else see what data is available or what data would help you make better choices. With the Web, there is so much data available, it is worth thinking long and hard about this issue. Some of the most successful online companies like Google and Amazon are awash in data and use it successfully to continually improve their businesses. Data, it’s what’s for Dinner.