Given the persistence of the trope that insurers are laggards when it comes to technology, it's instructive to shine a light on the ample evidence to the contrary.
This seems especially so in the case of "Big Data," a term currently in a death struggle with cloud computing for most overused IT buzzword of the decade. Yet, as is often the case, past the annoyance factor resides the prospect of real value.
A new report from the McKinsey Global Institute (MGI) attempts to cleave through the hype surrounding Big Data, and offers a workable, if subjective, definition of the term. "Big data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze," McKinsey states. "We assume that, as technology advances over time, the size of datasets that qualify as big data will also increase."
And, man, are datasets increasing. MGI estimates that globally, enterprises stored more than 7 exabytes of new data on disk drives in 2010 (picture 7 million of those 1-terabyte hard drives you have been eyeing at Best Buy). Thus the challenge surrounding Big Data is primarily one of scale. Yet, considering 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 seems surmountable.
Moreover, the steady stream of advances in hardware and software will help insurers keep apace of this rapidly inflating digital universe. For example, the increasing use of GPUs in the server space raises the prospect of many computationally dense problems being solved in parallel rather than sequentially. Computer graphics maker NVIDIA recently announced a partnership with HP to include up to eight high-end Tesla GPUs in HP's ProLiant servers. "The ability to store, aggregate, and combine data and then use the results to perform deep analyses has become ever more accessible as trends such as Moore's Law in computing, its equivalent in digital storage, and cloud computing continue to lower costs and other technology barriers," McKinsey states.
However, a shortage of the analytical and managerial horsepower, not technology, is the more immediate concern for insurers. McKinsey estimates the United States faces a shortage of 140,000 to 190,000 people with deep analytical skills, as well as 1.5 million managers and analysts to analyze big data and make decisions based on their findings.
Indeed, 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.
