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Nationwide Taps Analytics to Deliver On Its Promise

Kathy Koontz, assistant VP of customer information management for Nationwide, tells Insurance & Technology that analytic and data technology is nice -- but it's the skills needed to interpret those analytics that really help data shine.

Effectively using analytics to mine big data requires more than just the latest technology, according to Kathy Koontz, assistant VP of customer information management for Nationwide ($274 million in Q1 2012 net operating income). While the Columbus, Ohio-based carrier uses an enterprise data warehouse and analytic tools from Teradata to power its data-driven programs, Koontz tells I&T associate editor Nathan Golia, building the skills needed to interpret those analytics and make the data shine required some cultural adjustments within the business.

What spurred Nationwide's investment in advanced analytics capabilities?

Koontz: We have always had within the culture of our organization a focus on serving our members. We recognized that the state of our customer information didn't really allow us to deliver against that in a consistent and scalable way. Nationwide had gone through a period of acquisitions of other companies, leading to some of the data silos that you see when companies go through growth. We recognized that as a risk. So the organization made a significant investment to improve the customer information so we could deliver on our "On Your Side" promise.

What did this require from a technology and systems standpoint?

Koontz: Nationwide has been doing big data for a long time -- in our claims organization, in our pricing organization and in our marketing organization -- prior to this initiative. What this did was create a central hub of customer information to which we could relate that big data, so that we could execute consistently in delivering our differentiated customer experience and in using big data and analytics to guide that. But it was really as much of a business process initiative as it was a tech initiative.

[Keeping the Customer: Analytics Driven Acquisition and Retention]

Can you explain what you mean by that?

Koontz: The real challenge for companies that are looking at some sort of master data management initiative is getting internal organizations that traditionally have been segregated comfortable with the concept of sharing data with others, while at the same time having their ability to share the data constrained because of impacts it might have outside that particular organization. So there was the element of consolidating the info into a single data source, but there was also focus on working with our frontline associates to more appropriately capture that information. That's not tool usage; it's analytic insights that help our customer-facing associates know how they can demonstrate to our customers we know them, we care about them and we are on their side.

Was the technology the easy part?

Koontz: I'm not going to say that, but it was a little more straightforward. We have a very experienced leadership team with managing projects that are used for both operational and analytical uses of data. As we were looking at the overall transformational program and where we saw risk to delivering on our organizational objectives, we knew that based on our experience and reading stories of failed projects in the past that not having a focus on change management was an issue. You want to put processes in place to make sure that changes in one area don't introduce risk in another area.

You started this project in 2007. How has the infrastructure prepared you for the current focus on data and analytics?

Koontz: People will have this push for Day One results -- from the first release of the app or the data utility -- without an eye toward the fact that it's going to be maintained over time and the organization can extract more from this data investment to get further competitive advantage. We wanted to ensure that this significant investment the organization made delivered significant long-term and ongoing value.

How do you measure that effectiveness?

Koontz: We're measuring the utilization of those insights within customer interactions. We deliver to our sales and servicing organizations prioritized insights on conversations they should have with our members to drive improved acquisition or retention: "Here are the proactive and reactive conversations you must have with our members to take our 'On Our Side' promise and make it real." It's so we can really understand all this data that we capture about how customers buy and how they interact with our customer service.

Nathan Golia is senior editor of Insurance & Technology. He joined the publication in 2010 as associate editor and covers all aspects of the nexus between insurance and information technology, including mobility, distribution, core systems, customer interaction, and risk ... View Full Bio

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