Business intelligence projects can come into play across most of the functional areas of an organization, according to Steve Callahan, practice director for Robert E. Nolan Co. Today, BI tends to apply to dashboards and executive scorecards, but Callahan believes the industry is shifting to more predictive analytics, the next generation of BI, which he feels gives organizations the opportunity for competitive differentiation.
“I loom at analytics almost as a cube with three dimensions,” says Callahan. “One dimension is the type of analytics—it can be trends, ratio comparisons, scenario models, simulations, sensitivity analysis. The second dimension would be the functional area it’s applied against—agent effectiveness arena, market profiling, product performance, underwriting risk or the most common area, claims. The third dimension is the depth of the data. Here we look at the top level being the scorecards and the dashboards. You start drilling down to greater detail and the detail across variables as opposed to the density around a given variable.”
Business intelligence allows insurers to gain a lot of detail around expenses, but Callahan believes if you want to use predictive analytics you have to get detail around the attributes of your customer or the different attributes of the claims environment.
“If you consider the shift to customer centricity that the marketplace is moving toward, it’s such an increasingly diversified marketplace that there’s an enhanced awareness and understanding of customer attributes required in order to be able to achieve competitive advantage, more so than when it was a vanilla marketplace—a product being sold across a relatively generic population,” says Callahan.
Today there is more globalization and ethnic diversity, five generations in the marketplace looking for income and within each given generation or ethnic segment there are behavioral characteristics that bring with them shopping ability for finding the right solution.
“The onus is on the insurers to really understand their customers in order to provide them with a solution,” says Callahan. “That means having the data available to dig into. Data is critical but it’s not just data. It’s also the variability, the depth and breadth of the data and, of course, the quality of the data.”
One of the biggest challenges facing companies trying to move to the next level of business intelligence is what Callahan calls management bandwidth.
“The ability to develop models requires senior-level management insight, perspective, and collaboration to discuss the specifics of what they are looking at,” he says. “Management is overburdened now, so finding the management bandwidth to dedicate to a project like [BI] is difficult.”
The second major challenge for insurers is finding the expertise to understand how the different components of data inter-relate. Callahan maintains it’s an expertise in which a lot of companies don’t have much depth.
“The bandwidth issue is truly a matter of prioritization,” he says. “Companies that are moving forward in predictive analytics and business intelligence are recognizing [those tools] can provide them with competitive differentiation and they are prioritizing their efforts and allocating resources to focus on a particular area.”
The ones that have been successful with BI are ones that are picking an area to focus on. In the property/casualty area there has been a lot of focus on claims because the leverage of the claims dollar is so high. In other areas it may be on customer segmentation because insurers are moving into a differentiated market.
“They realize profitability varies with each customer so they are going to focus on the most profitable customers,” says Callahan.
In terms of developing the expertise from the existing staff, Callahan feels there are people within organizations that have worked with the data, particularly in the actuarial department or the information reporting department that have the necessary awareness.
“You can supplement that if you get toolset expertise that comes with the [software] installation and development of the first project, so you need knowledge transfer to your internal experts,” he says. “If you are trying to leapfrog the process you can contract the expertise if necessary to get your first project in house. The goal would be to get the knowledge transfer in place so you have your own staff develop the data awareness to take you to the next level.”
Traditionally, historical trend analysis served as the business intelligence for the insurance industry. Insurers have been doing such analysis for a good number of years and Callahan feels there are three realities to deal with.
- The law of large numbers has mitigated some of the issues with data quality. When insurers do a look-back it can be less effective in making predictions because the sensitivity in predictive models is much higher with data quality.
- Secondly, there is a comfort level in thinking the historical perspective is sufficient. What companies need to realize is reactive strategic actions they take will not be as competitively advantageous as being able to proactively put strategies in place.
- There needs to be an awareness of importance moving forward. You are watching through the rearview mirror, but what you would like to be able to do is look through the windshield and drive to where you want to be—achieving profitability in the first pass.
“There’s a sense of comfort some companies have with their approach to analyzing the data,” says Callahan. “They are thorough. They have dashboards, scorecards, a whole department that does historical analysis, and they can become comfortable in that perspective. When they move to the next level they have to move forward with building the predictive side where they can target their next steps and strategies rather than just analyze previously taken steps and strategies.
The Direction
Callahan points out the economy hasn’t been kind to major projects such as business intelligence and it’s not bouncing back enough to give insurers excess profitability where they have the luxury of exploring solutions at their leisure.
“We have the pressure of achieving sales growth and profitability in an environment where expense reduction doesn’t contribute as much as it could in the past,” he says. [Carriers] have to find out how to be more profitable. To do that, they have to look more closely at their products, their market segments, and their risk exposures. That’s going to drive the greater use of tools to achieve profitability. They have to look at their business with a magnifying glass. They can’t cut any more expenses; they have to become smarter."
