Why the Non-Superstar Might Be the Most Important Team Member
Superstars get all the attention, but other team members can be the ones who make a group really tick.
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Competing With Data & Analytics
Just like in chess, where pieces other than the dominant queen still have critical roles, certain people in organizations just make everyone else perform better.
Image courtesy of Flickr user Tristan Martin.
You’ve seen this at your workplace: some groups of people just perform better than others. The question is: Why?
It’s easy to focus on a team’s hotshot, or those with the best numbers who jointly raise their group’s overall performance.
But some teams do well because there’s a special alchemy among the team members. Alchemy is intriguing because it’s difficult to pin down. It could come from a team member who’s good at keeping other team members focused, or a member who has an upbeat personality that lifts everybody else’s energy.
Fortunately, there’s a way to measure which team members make a group work so well.
It’s called “plus/minus” analysis, and it involves looking at not just individual performance but at performance in context — understanding, through data, how a team of people does overall when one person is part of the mix, and when they’re not.
It’s a lesson that businesses can borrow from professional sports, where this kind of performance assessment is becoming more common.
Writing in the Summer 2014 issue of MIT Sloan Management Review, Thomas H. Davenport says that some U.S. teams in the National Basketball Association, Major League Soccer, and Major League Baseball have become more sophisticated in using analytics to measure team and player performance. Plus/minus analysis is used in sports for looking closely at how a team does when a particular player is playing and when he’s not, writes Davenport, in “What Businesses Can Learn From Sports Analytics.”
“Even if a particular player doesn’t generate impressive individual statistics, he may still be invaluable in a game if the team tends to perform much better when he’s playing,” Davenport writes. Teams are using analytics to look at how they do with both individual members and with different combinations of players.
Davenport cites basketball player Shane Battier, who retired earlier this year, as a notable plus/minus hero. Battier’s team, the Miami Heat, simply played better when he was on the court.
Companies would do well to use this kind of data to understand which of their own team members boost overall group effectiveness.