The amount of data being collected and retained by companies is increasing every year; in fact, a 2010 Gartner survey indicated that data growth was the most important challenge on the horizon for large enterprises.
There are plenty of risks of having a data-driven business, but the rewards can be substantial. While large data sets can be translated into useful information to make better business decisions, there is also the potential for problems arising from a focus on data collection and analysis. 
Data sets can become so large they are unmanageable. Data storage costs can quickly spiral out of control, especially if systems like a point-of-sale are collecting thousands of data points per day. There is also the significant risk that data will be collected for the sake of collecting data, that the firm will develop a culture that relies on proof rather than intuition and that no good decisions will follow due to a “paralysis-by-analysis” culture. Herbert Spencer once said, “when a man’s knowledge is not in order, the more of it he has, the greater will be his confusion of thought.”
Risks aside, those that efficiently and creatively use the data available to them can have a strong advantage. An interesting case study of successful synergy between information, technology and utility is the world of professional baseball. The history of scouting and strategy in professional baseball can be categorized into three different phases: the Classic Era, the New Metrics Era and the Analysis Era.
Classic Era
Scouts focused on the big hitters, hard pitchers and fast runners. Players spread out in the outfield and caught balls that came their way. If a batter had three balls and no strikes, he knew the safe play – a fastball up the middle – was coming next.
Once upon a time, it was all so simple. Pitchers pitched. Hitters hit. If the stars lined up, somebody with a glove caught what they hit. And that’s how baseball games were decided…
In the beginning, you didn’t need a Ph.D. from MIT to understand the art of pitch selection. If you had a good fastball, you threw it.
Basic statistics were measured and used to scout and compare players, but the subjective judgment of scouts and coaches was most frequently relied upon. Teams didn’t mind drafting a player out of high school if he showed promise.
New Metrics Era
Michael Lewis, author of the book Moneyball: The Art of Winning an Unfair Game, details how the Oakland A’s started another movement in professional baseball with a renewed focus on objectivity and measuring of new or previously unimportant metrics. In 2002, the Oakland A’s’ budget was about a third of that of the New York Yankees; they simply could not afford to pay the best players in the game. By revisiting the previous metrics used to evaluate players, management was able to devise some metrics that they felt gave them two advantages: players were measured based on their defensive or offensive contribution to the team rather than their individual statistics, and players were able to be signed when they were undervalued and traded away for a profit after their value had increased due to positive performance.
The New Metrics Era was closely tied to the growth of Sabermetrics (SABR coming from the Society for American Baseball Research), which were alternative measurements for talent and success in baseball. Since the publishing of the book, several teams have hired full-time Sabermetric Analysts.
Analysis Era
According to Jayson Stark of ESPN, batting averages and runs per game have drastically declined in recent years. He says that information technology, specifically the iPad and the vast amounts of video playback archives, has swung the game in favor of the pitchers. Players are now able to drill down into statistics for any player in the league based on a large number of criteria: date range, left- or right-handed pitcher, type of pitch, count – the list goes on.
But you think it stops there? Oh, no — all those stats are synced to a video database of every one of those pitches. So if you want to see how Lee reacted to every slider, low and away, that a right-hander has thrown him in a 1-and-2 count since 2006, that’s now possible. You don’t just have to read about it. Tap the screen on your iPad and watch it.
Pitchers are not the only ones who are able to benefit by analyzing historical data to look for weaknesses. The entire defensive strategy has shifted so that teams can analyze where certain players hit the most balls.
Thanks to companies like Baseball Info Solutions, all 30 teams know exactly where every hitter in baseball tends to hit the ball. So when you look out at the field and see third basemen practically playing up the middle, shortstops on the other side of second base and second basemen set up on the outfield grass, 75 feet beyond the infield dirt, that’s not guesswork, ladies and gentlemen.
That’s The Information Age at work in modern baseball.
Conclusions
What caused the tremendous growth in strategic pitching and defensive strategies in baseball, and how can they be applied to business? Three forces converged upon professional baseball to cause these recent changes:
- A wealth of available data
- Useful ways to manage and view that data
- Data being accessed by technology-savvy end users
When it’s broken down like that, it becomes clear how a business could leverage this same philosophy. Collect accurate data, access it in a useful manner and give it to the front-line employees out in the field.
Sources:
Welcome to the Information Age – by Jayson Stark at ESPN
Moneyball
The Problem with Perfection – by Ron Ashkenas at Harvard Business Review
