Most people have probably heard of the book, now feature film, Moneyball. A story of how the Oakland Athletics front office harnessed the power of data analytics to build an absolute enigma of a baseball team. This all began with the goal of then general manager, Billy Beane, who had an objective to maximize player output while minimizing the overall budget spent on players. Beane was ultimately able to achieve this goal, having reached the playoffs four consecutive years in a row and leading the A’s to become the first team to win twenty consecutive games in baseball history during the 2002 season. Sports teams from all around the world started to notice what Oakland had accomplished using data analytics and began to emulate similar strategies within their own organizations. With the goal of gaining an advantage over their opponents, sports organizations were able to leverage data analytics to acquire high value players, adjust their lineups more effectively, and develop winning game plans. So, what can we learn from sports analytics and how is that applicable to your business? Similarly, in business these strategies are used to gain a competitive advantage as well as answer questions like, “how can we improve x process?” or “how do we solve x problem?”
Close Relationships
We have learned that analytics can play a pivotal role in determining where and how teams can improve. When analysts work closely with executives, there can be a greater sense of clarity within the organization. In 2011, the Dallas Mavericks made a legendary NBA Finals run, securing the team’s first ever NBA championship. While one would credit the players and coaches for the championship, there is reason to suggest crediting some people who you’ve never heard of. One such mystery man is Roland Beech, an analyst for the Mavericks who provided analytical insight while sitting bench-side with the team during games. While he wasn’t a coach, he was strategic asset in their chase for championship glory. Owner Mark Cuban, who endorses the use and applications of analytics, had this to say about Beech:
“Roland was a key part to all this. I give a lot of credit to Coach Carlisle for putting Roland on the bench and interfacing with him and making sure we understood exactly what was going on: knowing what lineups work, what the issues were in terms of play calls and training.”
What we can learn from this is, keep your analysts close. Having analytics insights available to executive decision makers can further bolster strategic efforts and more efficiently push a team or organization that much closer to their goals.
Individual Performance
A key aspect of sports analytics that you might not necessarily think about in business is a focus on individual elements. Analytics in business tends to focus on overall operational and marketing issues whereas in sports, the analytics are often focused on the players. For instance, while Billy Beane was rebuilding the Oakland A’s, he broke down performance data on each player and determined their value based upon certain gritty statistics other than the popular and glamourous ones. Around that time, the baseball players getting paid the big money were the ones with high batting averages, great speed, and strong arms. However, Beane instead focused on “on-base percentage” which he considered to be a better indicator of the true value of a player. With this new player evaluation tactic, he was able to target great ballplayers for a low price rather than more popular ballplayers who were available at a premium.
Another example of an individual statistic that holds much weight in sports analytics is the “plus/minus” metric. In basketball and hockey, plus/minus is the point or goal differential of a single individual while they are on the court or ice. For example, if a hockey player is on the ice when their team scores but also gets scored on twice, this player’s plus/minus is -1. Sports analysts use this statistic opposed to other basic ones such as points and assists because a player might be an awful shooter, but he or she could have an excellent plus/minus value making that athlete a great team player.
Many lessons from individual statistics in sports can be applied to business analysis. In business, evaluating individuals will lead to conclusions that you wouldn’t necessarily find simply by looking at an entire organization. For example, if an executive notices a drop in sales numbers instead of looking at the sales team as a whole the executive can check individual performance and act on the relevant findings. Additionally, if a company is hiring data analysts, the hiring agents can analyze the applicants individually and do a better job of finding suitable candidates. Some candidates perhaps won’t have qualifications like a senior level data analyst, but they may still show proper underlying traits of an analyst revealing strong hiring value for the company.
Cameras and GPS Capabilities
Spearheading a practice that has now been normalized in the NBA, the Houston Rockets were the first NBA team to introduce using cameras and GPS tracking for analytical purposes. The idea was simple: the Rockets set up six cameras around the court to track passages of play and effective shooting locations. Daryl Morey, a statistical consultant who is now the general manager of the team, used the data gathered to improve his team’s offensive efficiency. Looking at the film and statistics, Morey noticed some interesting data about three-pointers: they have a 50% uplift in points received compared to two-pointers, and corner threes have a higher percentage of going in versus any other three-pointer. Morey also discovered that long two-point shots were the least efficient shot types taken by the team. Using this information, he was able to compose a gameplan that revolved around these findings. The results? Well, that season the Rockets led the league in combined shots taken inside the restricted area and three-pointers at 81% and broke the record for most three-pointers made in a single season. Along with these accolades, the Rockets made it to the Western Conference Finals that year ultimately losing to the deadly three-point shooting team of the Golden State Warriors.
An important objective in business is to ensure customer satisfaction, and one-way businesses can achieve this is with cameras and use of GPS tracking. Companies can track shipping routes using GPS to ensure packages are delivered on time and to the standard of the customer. Retailers can use video to study the patterns of shoppers; with this data, they can then alter marketing strategies to the actions of the shopper. They can also study shopping lines from video and use that data to figure out more efficient ways to get customers on their way satisfactorily. With video and GPS use, companies can now study more data and trends than ever before, which can provide detailed information for many companies ranging from the smallest mom-and-pop shop to the largest corporation.
Overreliance on Data
Although we can learn a lot of positive, beneficial aspects of analytics from sports, there is one aspect that people might get carried away with: overreliance on data. With the Oakland A’s, Billy Beane pioneered the philosophy of finding value in athletes at a low cost. However, this had its downfalls; in the Oakland Athletics stretch of consecutive playoff appearances from 2000 to 2003, they never advanced past the first round. To quote Beane, “My job is to get us to the playoffs. What happens after that is luck.” Beane’s words are an important reminder that succeeding in sports is much more than just analytics. There is a human impact that is unaccounted for in data which I like to call the “Tom Brady Factor”: after Tom Brady’s trade to the Tampa Bay Buccaneers, the team wasn’t projected to be as great as most people expected. In fact, in Brady’s first season the Buccaneers were 7-5 through week 12 of the regular season and analytics showed that they were on track to miss the playoffs entirely. What those analytics didn’t account for was the human aspect, or this “Tom Brady Factor,” as the Buccaneers then would go undefeated on their way to Super Bowl glory.
A sports leader who glorified Beane’s philosophy was English cricket coach, Andy Flower. He used statistical analysis to determine lineups and strategy for his team’s matches. Flower would find success in his analysis leading England to be the number one ranked team in the world as well as winning Coach of the Year in 2011. He saw dominance for the next two years until his team got embarrassed by Australia which started the downfall of his strategy. ESPN commentator Tim Wigmore summarized the situation well:
“Flower ultimately got the balance between trusting people and numbers wrong. He was in good company. In the brave new world, those who thrive will not be those who use data most—but those who use it most smartly.”
Applying this to business, there is an important lesson we can learn: data analysis is vital to any organization, but the results should always be considered alongside context and human intuition when making important decisions. As Beane and Flower’s experience shows us, blindly following every little piece of data may not lead one to all the rights answers.
Conclusion
The field of business analytics can learn a lot from watching how data is currently being used in sports. Billy Beane taught us about exploring more into individual statistics and performances to solve bigger problems inside of an organization. Roland Beech’s story showed that having a strong, close relationship between analysts and executives should guarantee success. The introduction of new analysis methods using cameras and GPS technology opens a wide door of possibilities for any business ranging from small businesses to mega-corporations. Lastly, it is important to remember not to be over reliant on data and to always weigh analysis with the context of every situation. With all this information learned from sports analytics, businesses can apply these lessons to improve their own practices and see substantial results in their future. If your business is looking for smart analytics using custom, creative, and visually appealing applications, contact us at Bear Cognition today.