Recent articles in the trade and business press suggest that the latest buzzword in the Data Management community – Big Data – has big implications for insurance executives. Hardware and software are required. But the real key asset – grey matter – might be in short supply.
Wikipedia defines Big Data as: “a term applied to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Big data sizes are a constantly moving target currently ranging from a few dozen terabytes to many petabytes of data in a single data set.”
What are these data? A recent column in The Economist provides a good summary of a few drivers: “Last year people stored enough data to fill 60,000 Libraries of Congress. The world’s 4 billion mobile-phone users (12% of whom own smartphones) have turned themselves into data-streams. YouTube claims to receive 24 hours of video every minute. Manufacturers have embedded 30m sensors into their products, converting mute bits of metal into data-generating nodes in the internet of things. The number of smartphones is increasing by 20% a year and the number of sensors by 30%.” In other words, Big Data are the stuff of day to day business and personal activities; the stuff that insurance professionals are increasingly relying on to for marketing, underwriting, risk management, claims handling.
There is some good news for insurers regarding the raw processing power required for Big Data: According to Bill Kenealy writing a recent post in Insurance Network News, “the relative maturity of the use of business analytics in insurance, not to mention the considerable investment insurers have made in data warehousing, this challenge (handling Big Data) seems surmountable.” So, if we’ve invested intelligently in data management over the past decade or so, we have, or at least understand, the required foundation.
But will we be able to use the data? Kenealy notes that “a shortage of the analytical and managerial horsepower, not technology, is the more immediate concern for insurers.” The Economist notes: “Big data has the same problems as small data, but bigger. Data-heads frequently allow the beauty of their mathematical models to obscure the unreliability of the numbers they feed into them. (Garbage in, garbage out.) They can also miss the big picture in their pursuit of ever more granular data.”
In short, insurers need a blend of grey matter: experienced common sense managers and analysts who understand the business, the data, and the processes to complement statisticians with deep technical skills. Kenealy provides a final cautionary note: “unless insurers are willing to make the outlays to secure the human capital necessary to turn these increasingly vast amounts of information into insight, they may find Big Data too big to swallow.”