From tracking this year's flu epidemic via social media, to Google's Instant searches, Amazon's recommendations and predictive keyboards on smartphones, businesses everywhere are embracing predictive analytics.

In the broadest sense, the goal of computer technology has always been to enable better decision-making. And yet, writing about predictive analytics was difficult, chiefly because my interview subjects and I first had to agree on a definition of predictive analytics in the context of their businesses or applications suites.

It wasn't a matter of overreach or misrepresentation on their parts, either, but rather an indication of several technology trends, such as business intelligence and customer relationship management, maturing and converging in the service of business technology's ultimate goal: more effective, cost-efficient decisions, based on facts and data.

As Matthew Josefowicz of Novarica told me, predictive analytics is a strange concept for the insurance industry, because it's really an evolution of what the industry has always done, which is: collect data, build models and try to predict the future.

That set of assumptions, though, led to several discussions as to whether a particular technology left a decision-maker better informed, or whether the technology went beyond gathering and shaping the data, performed an analysis and offered a statistics-based prediction.

That difference manifests in several ways, the former is essentially backward looking, whereas the latter is future focused, leading to yet another series of sidebar conversations on the importance of data.

It used to be that the information advantage was held by corporations, which had more processing power, connectivity and of course, data. However, with the advent of continuous connectivity, data is now ubiquitous, so the ability to make informed decisions quickly and accurately based on that data has become the latest differentiator.

Whether we like or not, the world is changing and insurers need to thrive, not survive in a much faster-paced marketplace.

Can analytics get them there? Join our LinkedIn group and tell us.

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