Sports is a funny thing. It weirdly unites us beyond borders while it also divides us by teams. While some view it as an obsolete invention to distract people from the actual problems, others see it as a much-needed break away from the mundane and often sad reality. Whichever way you see it, the parallels between Sports and Life is real and so are the parallels between Sports and Business.
While there are many lessons for Business that can be drawn from Sports, the second most important lesson is the way data is being leveraged across different Sports. The most important lesson from Sports would be how successful Sports teams invest in their teams to find their next Superstar. But we are going to focus on Data in Sports and what companies can learn from it.
Sports is one of those areas where there has been an explosion of data, especially about player performances. While the same could be said about a lot of businesses, it is not exactly true for employees. A player gets thousands of data points about their own performance after every single match. Successful teams help their players understand where they are good and where they have to improve. Good coaches watch the game reel with the players to guide them through how they could have played the game better.
On the other hand, an employee gets a single data point or a handful of data points after an entire year, riddled with systemic biases like the recency effect and personal biases of the evaluator. No manager sits and watches the game reel (or the performance appraisal sheet) along with the employee and helps create a game plan for the next season. The entire process is awkwardly wrapped on the day of the deadline. The only impact it has is on the compensation, the day on which it is revealed just adds to the weirdness of the office space. Creating data points of your employee performance is a paramount to creating champions and building a successful franchise.
Other key area where data is employed in Sports is by talent scouts to spot talent. No manager is getting a bonus for identifying Messi in 2020. Spotting Messi in 2000 is the real challenge and teams have started using data to answer these tough questions. Competing for the same talent with Google or any of the MAANG (formerly FAANG) companies might not be a fruitful strategy but figuring out what your “Messi in 2000” is like and going after them. A little bit of Sabermetrics (from Moneyball) cannot hurt either, finding your version of the On-Base Percentage and going after talent that makes a lot of sense for your company but not to others would be effective as well.
The last key takeaway is how data helps the Sports team manage their GOATs. No team just assumes GOATs are flawless and left alone, they just keep spinning magic. Even the likes of Sachin Tendulkar and Virat Kohli have their strengths and weaknesses, matchups, and days when they are not in touch and out of form. A similar view should be taken towards managing your champion employees. Keeping your champions happy is the highest ROI endeavor that your company could undertake. Identifying them as GOATs of the company and aiding them in the process of becoming champions with the help of data can help turn the fortunes of any dwindling franchise.