Insurers: Data Science doesn’t need to be so complicated

There has been quite a bit of activity – if not outright hype – regarding the promise of big data and data science. In October, I had a chance to participate in a panel discussion on the promises and perils of data science, in which fellow panelist and digital thought leader Dion Hinchliffe predicted the eventual emergence of “data science as a service.” The time is coming when analytics and accompanying insights would be available online, without the need to hire a roomful of PhDs to help make sense of things.

This has interesting implications for the insurance industry. Along these lines, I recently heard from Mike de Waal, president and founder of Global IQX, and formerly an executive Manulife Financial, who sees data science as one of the most important developments yet for the industry – particularly an industry that increasingly is looking to data to better serve policyholders in new and innovative ways. Consider the many areas where data is playing a role these days: “telemetry, IoT, wearables, AI, chatbots and drones are tools that help group insurers better engage with customers and improve business processes,” according to de Waal. “There is one thing that all of these technologies have in common: data – personal data, to be precise.”

De Waal provides some practical advice to insurers looking to build their mastery in big data:

Don’t be intimidated. The key is not to feel overwhelmed by the bigness of big data. While the concept of data science may seem bewildering, it actually is based on a basic six-step process that de Waal describes:

1. Frame the problem 2. Collect raw data 3. Process the data 4. Explore the data 5. Perform in-depth analysis 6. Communicate the results

The 80-20 rule applies. Like many things in life, data science is an 80-20 proposition, with “only about 20% of the skills needed will contribute to 80% of the outcomes,” de Waal explains. By focusing on the core 20% necessary to achieve the results you’re looking for “will help simplify the process and keep IT departments focused on the goals you originally set out to achieve with the data.”

Stay laser focused on the business problem to be addressed. “They don’t call it big data for nothing,” de Waal says. “The amount is gigantic. New variables and trends that arise can easily lead you astray from the original question you set out to answer.