When I spoke recently with Novarica insurance practice principal Martina Conlon, I was surprised to hear that she thinks carriers are struggling to come up with a persuasive business case for investing in big data. "You can't easily quantify the benefits of enhanced customer experience or improved risk selection or risk management, so it is hard to quantify the benefits of a big data project," she told me, adding that this is one reason big data implementations aren't further along in the industry.
Really? It's hard to argue for investments in products and services that can help your company create more profitable products, do a better job of identifying and addressing risks, get a better return on its marketing spending, and provide a higher level of customer service that keeps policyholders happy and loyal? As we report in this month's issue of Insurance & Technology, a growing number of carriers already are tapping big data to improve these kinds of essential insurance business requirements.
It's also hard to believe that anyone could ignore the ways data -- or more specifically, the increasingly sophisticated ways businesses and governments are analyzing it to understand who we are, what we do and what we want, and to profit from that understanding -- is transforming all kinds of transactions and interactions. Why wouldn't any insurer want to gain that ability?
Skepticism, Lack Of Resources
A number of factors are no doubt contributing to the difficulty of making an effective business case for big data investments, ranging from skepticism about results to limited internal resources to the age-old challenges around business and IT alignment.
[Point-of-Sale Analytics Key to Better Insurance Distribution]
Another problem may be that companies (not just in insurance) appear to be launching big data efforts in an attempt to control the proliferation of data, as opposed to tying them to specific business goals. Nearly half (49%) of respondents to a recent study conducted by Microsoft said that growth in data volumes is the greatest challenge driving their adoption of big data products, followed by having to integrate disparate business intelligence tools (41%) and having tools that can extract the insights (40%). That doesn't sound very strategic.
While there clearly are operational and infrastructure aspects to big data adoption, it can't be viewed as an efficiency, productivity or automation project (although those may be eventual benefits). There is a creativity and openness related to pursuing big data that may be at odds with the ways insurance executives -- not only in IT, but throughout the enterprise -- have been trained to look at the business. Without this broader perspective, however, efforts to define a big data business case can only disappoint.