5 MLB Analytics Practices That Work For Businesses
Best practices now embraced by baseball managers can be used by executives in all lines of business.
For the modern business, context should be critical, especially given the growing types of data, such as social media, that aren't created in a vacuum. Understanding the context within which a data set was created is as critical as the data itself.
One way this occurs is through sentiment analysis, which helps data analysts understand the human emotions behind statements made in social media, product reviews and other forums. So rather than just relying on static information such as sales data (RBIs, if you will), organizations can now gain a nuanced understanding of what people like and don't like about their company, and tailor products and communications accordingly.
4. Make Predictions
Baseball teams used to evaluate -- and therefore compensate -- players on their past production. The better a player produced in the past, the more he was paid, not only in the present, but in the future as contracts started to lengthen. By the end of a long-term contract, teams were often paying big money for players who were no longer producing like they used to. With the increased use of analytics, however, teams are better predicting players' future performance, and tailoring contract offers accordingly.
Likewise, businesses should combine traditional business intelligence with modern predictive analytics. With all the data now available, companies can make decisions not because of what's happened, but what's likely to happen based on the patterns data can illuminate.
Some universities, for example, are now using analytics to identify student behavioral patterns that predict future dropouts. So whereas in the past, an administrator might have evaluated "what happened" after a student dropped out, with predictive analytics administrators are now intervening with counseling and tutoring before the student reaches that point.
5. Declare WAR
The most controversial baseball metric spawned by the analytic revolution is WAR, or "wins above replacement," a statistic that determines how many wins a player will add if you employ him rather than a league-average player (usually a minor leaguer or bench player). In short, WAR makes it easier for GMs to weigh the cost of each player against the expected benefit.
While the jury is still out on WAR within baseball, the underlying concept of comparative analytics is one all businesses should embrace. Maybe you're comparing the price versus benefits of two marketing campaigns rather than two players, but now you have the ability to use data to weigh the options.
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