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Data Analytics: Why Insurance Is in a League of Its Own

Baseball may seem like the same sport it was a hundred years ago, but the rise of data analytics has transformed the game. Learn why you should use the same tools to take your insurance game to the major leagues.
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It’s that time of year again. The leaves are changing and baseball season has reached its peak. For many casual fans, the game appears unchanged across history. The wind-up, the crack of the bat, the atmosphere of the ballpark and the hunt for a World Series appearance all remain the same.

This month, the World Series completed its 115th incarnation, and while baseball still seems like the same game it was a hundred years ago, it’s also a completely different game today.

Before the players ever set foot on the baseball diamond, something else has transformed the game behind the scenes: data analytics. Not only has data analytics revolutionized baseball, it’s done the same for practically every industry—including insurance.

From America’s Pastime to a Data Analytics Showcase

The first baseball game took place approximately 180 years ago. A few decades later, the first box score—a two-line chart that reports each team's run totals by inning, and total runs, total hits and total errors on a line—was developed to give fans a way to keep track of games and player statistics. Through the second half of the 19th century and the first half of the 20th century, baseball statistics had little to no influence on how the game was played, yet box scores stuck around.

Baseball and data analytics crossed paths in the 1960s and ‘70s when first hobbyists and then researchers began to ask specific questions about in-game activity. They started collecting and summarizing the data in what became known as Sabermetrics, the empirical analysis of baseball—a term coined by writer, historian and statistician Bill James.

James gave a voice to quantitative measurements of batting, pitching and higher mathematics statistics, such as value over replacement player (VORP) or wins above replacement (WAR), replacing simple ratios like earned run average (ERA) to give a more complete view of what’s really happening on the baseball field.

While the box score and other early statistics work put a metaphorical runner on first base, James’ pioneering work on data analytics in baseball loaded the bases for the grand slam to come: the emergence of predictive analytics.

In 2002, Sabermetrics hit the big stage as the Oakland Athletics under general manager Billy Beane went on a 20-game winning streak in a season where they implemented unpopular techniques to put players on base and score runs.

Oakland’s feat was not the sole deciding factor for teams to consider changing their approach to the game; multiple teams experimented with the ideas implemented by the A’s prior to the 2002 season. However, the team’s ability to earn runs that year was a clear success story for Sabermetrics. The season was immortalized in Michael Lewis’ 2003 book “Moneyball: The Art of Winning an Unfair Game” and the 2011 film “Moneyball,” starring Brad Pitt.

Playing the Long Game

Data analytics has experienced a meteoric rise across different industries in the past few decades. For insurance agents, the long timespans of baseball games and seasons make them feel right at home.

Baseball teams invest considerable capital, both fiscal and human, to ensure their team is prepared for upcoming seasons to attempt to win the World Series. Likewise, agents invest significant amounts of time and money to earn business from new customers and then develop and maintain trusting relationships with clients through seasons of renewals. When an agent earns new business or increases retention, the feeling can be akin to hitting one out of the park.

Optimizing operations and relationships is not always a home run. It’s hard work every day—you may hit a single by discovering a new lead or strike out after a client leaves you unexpectedly. However, there are tools you can implement today that’s a real game-changer in insurance: data analytics.

From the Minors to the Major Leagues with Data Analytics

Implementing a successful data analytics strategy within your business can put you in a league of your own compared to other independent agencies. Data-powered businesses are five times more likely to make faster decisions than their peers, according to a study by Bain & Company.

Data analytics tools level the playing field by maximizing the value of your agency’s data. By becoming a data-powered business, you can gain a competitive edge through enhanced decision-making, insight discovery and process optimization.

Data analytics can bring value to your business by:

  • Reinforcing decision-making processes with rich sources of external data analyzed with machine learning.
  • Cutting claims handling time and costs with predictive analytics.
  • Eliminating fraud through enhanced, artificial intelligence-driven identity verification techniques.

These tools allow you to obtain powerful graphical business insights from your existing management system data to drive greater employee productivity and increase profitable relationships with clients and insurers.

In baseball, teams use data to predict outcomes and make strategic decisions. In insurance, as our tools become more AI-enabled and future-predictive, we can make more informed business decisions and identify new market opportunities.

Are you still using yesterday’s reporting tools in today’s highly competitive insurance marketplace? Like baseball, the game of insurance has changed. By making data analytics a part of your playbook, you position your agency to hit a home run.

Brian Wood is vice president of Data Products Group for IVANS, a division of Applied.