Businesses are increasingly competing on the strength of market intelligence and the insights they can derive from information. This is -- or should be -- especially true with the data-rich insurance industry. But, as discussed in "The Two Second Rule: How to Win by Seeing the Future, Just Enough," an upcoming book by Vivek Ranadive, founder and CEO of Palo Alto, Calif.-based TIBCO, even the best analysis won't help if your competitor arrives at the right conclusion first.
That kind of thinking jibes with the technology strategy adhered to by Akhil Tripathi, SVP and CIO of Harleysville Insurance ($1.1 billion in net written premium). [Editor's Note: Tripathi left the company at the end of July; Jon Griggs has been named the carrier's acting CIO while Steve Byrne has stepped into the role of acting CTO.]
According to Tripathi, data is the foundation for competing on the basis of analytics, so he and his team have developed and continue to work on capabilities aimed at enabling the Harleysville, Pa.-based super-regional P&C carrier to do so. Harleysville not only uses internal data for analytical purposes, he notes, but increasingly draws on external sources to power its predictive models.
"We use predictive models that employ our extensive transactional data, supplemented by external data, to evaluate the risk of most of our new and renewal business," Tripathi relates. "These predictive models and an underwriting rules engine are integrated with our rate, quote and policy issuance systems. The entire process is real time and allows us to leverage the latest information about a particular risk and our appetite for that risk."
Making the right decisions, Tripathi adds, means getting the right data, in the right form, to the right place at the right time. And given the way data continues to proliferate within the insurance enterprise, leveraging one's data assets for competitive advantage today is, in significant measure, a matter of identifying the data that really matters, he counsels.
"You can't take thousands of data elements and say, 'I'm going to clean it all up and create a giant data warehouse,' " Tripathi cautions. "You have to narrow the focus to identify which data elements are truly strategic to the business and decide how to use internal and external data sources to validate that information."
As an insurer builds its data strategy, it must identify the strategic attributes within the vast data sources that represent the highest impact for its business strategy and their relative importance to the business. "Insurers need to identify their competitive capabilities with respect to customer, product, distribution and market," Tripathi insists. "Only when they understand their enterprise's business strategy can they build a data and information strategy. The enterprise is then able to identify which components of the data are critical to delivering business value.
"We call these 'conformed dimensions,' " he continues. "The dimensions in the repositories need to have business definitions and valid values along with the rules for their relationships to other conformed dimensions." Once the identification of critical data elements is completed and conformed dimension tables are built, Tripathi asserts, it is easier to extract value from the data.
Rethinking How Business Is Done
Building an effective data strategy, however, remains easier said than done for many carriers, in part because it requires a fundamental shift in thinking about how business is done, contends Joseph Merten, managing director of LECG SMART, a Devon, Pa.-based global business advisory services firm. "As an example, we work with a number of companies that struggle with data from [managing general agents], so they don't have good optics into how the business is performing," Merten says. "As the data cascades through the organization, by the time you get to finance, the data needs to be reconciled -- and that introduces more time and more cost."
Culture has as much to do with the problem as technology, and recent start-ups often make the same mistakes as established companies, Merten reports. "In part it's because that's the way business has always been done: 'Let's just get it done and we'll figure it out later,' " he explains. "But if you haven't captured the right data once business has begun to flow, you make it very difficult to close books effectively and understand where you are as a company."
This lack of transparency hinders business speed and strategic agility, Merten says. "In many companies it's a systemic problem," he relates. "Because they lack data standards and controls, insurers pay a significant operational penalty."
In addition to operational costs, carriers' data deficiencies can result in a severe disadvantage relative to their competitors that have successfully modernized their systems, suggests John Koepke, a Chicago-based senior executive with Accenture who specializes in core systems conversions. "The tier-one players are at the point where they are predicting what will happen, not generating insight into what already happened," Koepke comments.
Companies that aspire to compete on analytics need years, if not decades, of policy and customer data, which means effective conversion of data from legacy systems, Koepke observes. "The only way to get the full picture of a book of business is to create a common data governance framework and common definition of data entities across your enterprise," he adds. "And any transformational or policy admin rationalization effort is only going to be as successful as the conversion of the data moved to the new target platform."