By now everyone surely knows the story of Moneyball, and how about a decade ago Billy Beane of the Oakland A’s recognized that On-Base Percentage projects Runs Scored better than Batting Average and subsequently built a team on the cheap because the market for players undervalued OBP. What fewer people know, though, is that Moneyball is ancient history.
A decade ago, teams could do a pretty good job of designing a roster by analyzing players’ statistics in a spreadsheet, like Cliff Lee’s below. But today teams can’t rely on Excel ninjas in the front office, they need computer scientists who can make sense of databases with millions of data points.
Baseball’s Mountain of Data
When you watch a baseball game, you might see the “K Zone” show up during some at-bats to show you exactly where the pitch was located relative to the strike zone. This is a nice perk for viewers, but behind the “K Zone” is PITCHf/x, the video system designed by SportVision that takes nearly 20 pictures of every MLB pitch to track the rotation, velocity, and trajectory of the ball.
Instead of recording a single row of statistics in Excel for each game a pitcher appears in, teams now have a database with a row for every pitch thrown. Teams can use this data to track where a pitcher is releasing each pitch or how severely his curveball is breaking. And that’s just the pitches!
There’s also HITf/x that tracks ball flight off the bat and FIELDf/x that tracks each player’s movement in the field. By the end of the season, teams now have mountains and mountains of data. And this is the case for most businesses now.
Since business is so digitally based today, businesses have the opportunity to collect amazing amounts of data on consumers. Thanks to services like Salesforce.com, firms can also keep records for each individual customer. And thanks to applications that plug into Salesforce.com, firms can also keep records of each prospective customer’s actions. Even small businesses can see heat maps of their marketing emails to better understand what recipients are most interested in.
Consider also how many online orders or credit card purchases are processed every day for even a single mid-market retailer. Think of the extraordinary amount of data points that are available for analysis!
Harvard Business Review and MIT’s Sloan Management Review have both been focusing much of their recent issues on Big Data. They both express the need for businesses to quickly figure out how to control the explosion of data and mold the data into useful chunks that can be properly analyzed.
An Opportunity for Business Schools
The biggest problem with the information explosion is that most people don’t yet know how to turn a mass of data into value for consumers. They can’t get their digital arms around the data, let alone gain insight from it. Thus, HBR published an article called “Data Scientist: The Sexiest Job of the 21st Century.”
As an MBA student who would love to work in the front office of the 11-time World Series Champion St. Louis Cardinals, I dearly wish I was a brilliant data scientist, but alas computer science and programming isn’t in the cards for me.
Yet whether or not Busch Stadium becomes my office someday, I do know that my business school peers and I will assuredly face business decisions about investing in data solutions or about how to harness the data our companies have access to. This isn’t some baseless prediction either. Big Data is already here and it’s only going to become more of an issue, it’s absolutely going to pervade the future of business.
Because of this clear and present reality, I would like to see business schools quickly begin developing curriculum around Big Data. Most MBA candidates will never be data scientists, but we need to be aware of issues surrounding the information explosion.
Additionally, it would be fantastic if business schools would begin to partner with computer science programs. Whether it be undergraduate or graduate, the same school or a different school, business schools would serve their students well by connecting future business leaders with technical talent.
How valuable would a combined course be in which MBA students and computer scientists had to work together to harness a mound of data and create value for a prospective consumer?
Not only would it expose the computer scientists to the business side of their work and the business students to the technical side of data management, it would provide each student with a valuable contact. How great would it be for MBA students to not only learn business skills and gain a network of business colleagues, but also graduate with a network of technical colleagues who they could partner with for new ventures?
It shouldn’t take a lot of work for schools to create these partnerships, but they could create a great payoff for both sets of students and for the reputation of the school.
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