Big data. Surely you’ve heard this little two-word catchphrase over the past few months.
Companies in all industries are seeking out new ways to gather, interpret and leverage the massive and ever-growing collection of personal information now available about consumers, thanks largely to smartphones, GPS and social media.
I first became intrigued about the power and potential of big data while reading the 2003 Michael Lewis bestseller “Moneyball: The Art of Winning an Unfair Game.” The book examined how General Manager Billy Beane’s Oakland A’s mined statistics to identify undervalued players, allowing the small-market franchise to successfully compete against big-market clubs with budgets several times bigger than their own.
“Moneyball” asserted that the way baseball organizations — scouts, coaches, managers and the front office — evaluated talent over the past century was subjective and often flawed. Too much emphasis was given to traditional statistics like batting average, runs batted in and stolen bases. The A’s used sabermetrics — specialized analysis of baseball through objective evidence, especially statistics that measure in-game activity — that demonstrated on-base percentage and slugging percentage are better indicators of offensive success.
Using this revolutionary approach, the A’s, with a team payroll of $41 million compared to $125 million for the New York Yankees, made the playoffs in 2002 and again in 2003.
This is a great example of an organization taking advantage of available (big) data to make better decisions that significantly enhanced organizational success.
The insurance industry has begun to use similar principles in very tangible ways. What immediately leaps to mind is Progressive’s patented, proprietary Snapshot. Some of the company’s auto insurance policyholders voluntarily plug the little device into their cars and it measures their driving activity, like how often they slam on the brakes, miles driven, and how often the car is driven in the more dangerous time between midnight and 4 a.m. It doesn’t care how fast or where people drive.
But the “better” users drive, the more they can save — up to 30 percent compared to their original rate (which can’t go up because of Snapshot).
See also: How Progressive’s Snapshot works
As Chris Stehno, senior manager, Deloitte Consulting, mentioned in a recent session about predictive analytics at the LIMRA Life Insurance Conference, auto insurers had basically tapped out existing data sources about policyholders, so they came up with this data creator that provides additional, very accurate data that can help identify and reward “good” drivers. I would think this kind of real-world data would be a lot more helpful than figuring in a driver’s credit score.
Next page: Predictive analytics in life insurance
Stehno also mentioned that smartphones are becoming a consumer’s Snapshot for other miners of data. A smartphone provides a ton of information about its user and his or her lifestyle, and much of that information is being collected and analyzed, whether consumers realize it or not.