In some ways insurers have been leaders in the use of data analysis, but they lag in achieving the enterprise grasp of data infrastructure analytics capabilities to optimize their ability to be analytical competitors. Pat Saporito, Senior Director of SAP’s Global Center of Excellence for Analytics has written “Applied Insurance Analytics: A Framework for Driving More Value from Data Assets, Technologies and Tools,” published by Pearson/FT Press to help insurers on the road to that optimization. The book is available at Amazon.com, along with reprints of Saporito’s Best’s Review Technology Insights columns on analytics that she has written over the years.The former industry analyst and long-time evangelist of the potential of data and analytics for the insurance industry recently talked to Insurance Innovation Reporter about the book’s contents and its mission for the industry.

Insurance Innovation Reporter: Pat, could you give us a summary of the book?

Pat Saporito: Sure. It’s a practical guide with leading practices, frameworks, use cases and case studies written primarily for business professionals on how to get the most of their data and technology investments and how to work effectively with IT. It is useful for IT as well, especially the use cases and case studies.

IIR: Certainly there’s a lot of talk and buzz about big data, little data, the internet of things and analytics in general.  What was the catalyst for you to write the book?

PS: Two things. First of all in working with customer I see a consistent gap in a lack of enterprise analytics. Insurers have been fairly good at basic analytics, primarily reporting, in individual functional areas but aren’t leveraging analytics, data or business rules across functions. Secondly, there are a number of books on analytics in insurance but they are focused on risk management or other functional areas, e.g., pricing; there is no enterprise analytics view for insurers.

IIR: What do you attribute this lack of an enterprise view to? What do you see as the barriers?

PS: Largely it’s the lack of an enterprise BI or analytics strategy (not just a technical strategy) and programmatic approach in which both IT and the business are partners. I lay out a strategic framework to address this which includes Strategy Objectives & Scope; Business Needs; Business Value or ROI; Information Architecture, Taxonomy and Tools – I know it sounds technical! –  and Governance.  Each of the chapters explains these areas and the business’ role in each.

Two other key areas are a lack of executive sponsorship and a lack of an analytic culture. Most of these barriers can effectively be addressed through governance in a BI or Analytics Competency which deals with four key elements – people, process, technologies and data.

IIR: Can you discuss a bit more about the best practices and frameworks?

PS: There are Analytics Evolution Charts for property/casualty and life/health that can help insurers assess their analytics maturity at a high level across functional areas and see them in the whole across areas. This a great place to start a dialogue. They are analytics actionability frameworks that help insurers view the top 2-3 analytics objectives by functional area, along with supporting business questions, actions and metrics. Lastly there are analytic dimension templates that look at metrics and the business dimensions. All of these are useful frameworks to help business and IT communicate better and define requirements more concisely. Over 75 percent of business users have a hard time defining requirements. What I see is IT asks the business what they need, and the business says give me all the data and creates additional data silos and data chaos.