I’m sure many, if not all of you who have been in the corporate world have heard sports analogies applied to business situations on several occasions:

• You’ve heard your boss talk about taking on small tasks in an efficient manner such that the cumulative effect of these efforts completes a major project – “We’re not here to hit home runs. If we just hit a bunch of singles, we’ll see the light at the end of the tunnel before you know it!”
• Your co-worker pulls an all-nighter completing a requirements document so the team can define the next steps the following day – “Wow, thanks! You really took one for the team!”
• Your company was just engaged by a new client who is struggling to meet project deadlines – “We really need your help setting realistic timelines based on all the work we have on our plate. We just seem to keep dropping the ball.”
• The team you are managing has many milestones coming up and the group seems a little frazzled in the weekly status meeting – “I know we have a lot going on, but if we just keep our eye on the ball, we’ll be fine.”
• Sometimes, it can even be negative. A competitor called you out of nowhere and asked you wide-ranging questions that did not seem to have a common link – “I just got off the phone with one of our competitors. I don’t know what the point of the call was, but they were clearly on a fishing expedition.”

The number of metaphors is endless. And these metaphors have been employed for longer than most people can remember. I would call this a one-way street with business borrowing from the sports world; however, over the past decade that one-way street became a two-way street as analytics began driving decision making in the sports world. The influence of business on sports has become far-ranging—analytics are now used to make decisions in most sports, including the most popular (baseball, football, basketball, and hockey). They are employed at the professional, college, and even high school levels.

A popular example of the marriage of sports and analytics was detailed in Michael Lewis’s book, Moneyball. Moneyball dates back to the 2002 Oakland A’s and their general manager, Billy Beane. Beane used analytics at both the team and individual player level to create a competitive, playoff caliber team while having one of the lowest payrolls in baseball. Another example of the growth of analytics in sports is the MIT Sloan Sports Analytics Conference. Starting in 2007, MIT has brought together many of the innovative minds in the world of sports analytics. The event debuted with 175 people in attendance in 2007. That number has now grown into the thousands.

While sports analytics has only recently gained prevalence, business analytics has been in use as far back as 1954 and has permeated into every business sector. Whether businesses are using forms of Business Intelligence, Data Governance, Data Management, Regression Analysis and Predictive Analytics or Big Data (the list goes on and on), they all spawned from the basic idea of analytics, which put simply is using data to drive more informed decisions.

It seems that within this two-way continuum, sports is benefitting from business more than vice versa. However, this symbiotic connection is starting to turn the other way. MIT’s Analytics Leadership now points to areas where the use of sports analytics is returning the favor and helping out businesses:

• Align Leadership at Multiple Levels: some sports teams have put their analysts in constant contact with the coach or manager. Data analysts are in pre-game meetings providing matchup evaluations used during the game, and performing analyses based on a coach’s direct requests. From a business perspective, some executives are bringing in analysts to consult collaboratively during major business decisions.
• Focus on the Human Dimension: sports analytics has come up with more complex metrics that point to how certain players perform alongside other players, or how certain players perform under certain conditions. Business analytics tended to focus strictly on how the business is doing. Borrowing from the sports world, businesses are now starting to look at how their employees perform conditionally, comparing their output when working with one employee compared to another.
• Exploit Video and Locational Data: Major League Baseball teams record every pitch of every inning of every game to look for tendencies in how certain teams will defend a hitter based on the pitch count. Businesses, like banks and retailers, have adopted this approach by analyzing customer lines and interactions with employees to minimize wait times and maximize customer satisfaction.
• Focus Analytics on the Individual: Professional athletes are now taking whatever data their teams can provide to analyze their own tendencies for self-improvement. Employees of businesses are now using their own data from Customer Relationship Management (CRM) tools to determine how much time they are spending on certain phases of new client acquisition life cycles, and then breaking that time down to see where they are getting the most value and where they can improve.

Kenway has experienced this sports-to-business reversal in multiple capacities. A great example points to the use of analytics focusing on the individual. Kenway helped a leading global provider of financial services build and automate a “Scorecard” that allowed the provider to evaluate their bank managers in regards to bringing in new business. The “Scorecard” aggregated such data as revenues, loans, deposits, and client relationship activities that resulted in a grade for the bank manager. The end result helped leadership determine what amount of compensation should be awarded to the manager.

This two-way street between sports and business continues to ebb back and forth with each side providing value to the other. Is it business’ turn to switch gears and provide that new value to the sports world? Only time will tell, but history shows that these two competitive arenas will continue a give and take relationship leading to the betterment of both landscapes.