Analytics strategy and mobility goals for the CIO

Analytics strategy and mobility goals for the CIO

Date: Jul 05, 2012

At Capitol Insurance Companies in Middleton, Wis., the IT organization is amping up its contributions to the business with an analytics strategy and an emphasis on mobile technology.

In this video, filmed at the Fusion 2012 CEO-CIO Symposium in Madison, Wis., SearchCIO-Midmarket.com Site Editor Wendy Schuchart sits down with Troy Lethem, the insurance company's CIO and vice president of information services, to discuss how an analytics strategy focused on data repositories and predictive analytics has improved Capitol's business.

In the first part of this interview, Lethem discussed how outdated technology prevented the company from moving forward in its growth. In this video, he explains the analytics strategy devised to change this stagnant progress. Under his leadership, the company has embraced predictive analytics and developed a mobile mentality in order to reinvent the business.

Read a partial transcript from this interview below, and watch the video to learn more about Lethem's analytics strategy.

Wendy Schuchart: Can you tell me a little bit more about how you are using big data?

Troy Lethem:
I can't say we have big data when I look at other industries and when I look at other endeavors -- once again, we are a midsized company. But we are gathering increasing amounts of data; and the initial strategy we had, which will be familiar to most companies, is building a data warehouse, where we take the core information out of our core systems and bring that into a common [repository] that can be queried and reported against. This is where our management reporting is based, upon the data warehouse.

The next thing we are doing is bringing in predictive analytics -- and predictive analytics says we want to do a deep analysis of your current data as well as external data sources -- and that could be by ZIP code, that could be by crime statistics or weather patterns. There's a lot of external data we can bring in. Next, by combining that data and by doing very intense analytics looking backwards -- for example at our claim history -- predictive analytics can give us some factors in pricing and in underwriting that our underwriters really did not see because they are very, very complex patterns.

Let us know what you think about the story; email Wendy Schuchart, Site Editor. For midmarket IT news and updates throughout the week, follow us on Twitter @ciomidmarket.

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