Insurance is a tough business today and carriers face myriadcompetitive pressures. Customers are better informed and have morechannels to shop for insurance than ever before. And thesecustomers expect instant and special service—online access to theirinformation, instant ability to file claims on mobile devices,quick settlement of claims—all at the lowest possible cost tothem.

Meanwhile, investment returns have been at historically lowlevels for the past several years, which spotlights the importanceof underwriting results, adds pressure on expenses, and increasesthe prioritity of new initiatives. And as consolidation within theindustry continues, insurers look to decrease expenses, invest innew technologies and grow their market share in the broad market.For those insurers that are not one of the industry behemoths,survival means establishing strategies that focus on portions ofthe market that require unique products, specialized insights, orcustomized service. The bar of competition in personal linesinsurance has been raised, and there's little prospect for it toget easier in the future.

What is the secret to competing in the increasingly challengingpersonal lines markets? Is it enough just to work harder than theother guy? No. Don't work harder, work smarter. It's more importantthan ever in today's environment to make decisions—or those greatinnovative leaps—only after quantifying, understanding andevaluating the inherent risks. Working smarter means makingdecisions based on solid data and information derived from a robustdata and analytics capability.

Analytics investments that find knowledge will give acompetitive edge, which is what Verisk Analytics refers to asn+1, and should be a top priority for insurers. The goodnews is that many carriers in the marketplace have invested inanalytics to some degree, especially in the area of ratingrefinement. The first-movers in the rating analytics arena a decadeor so ago were able turn their unique insights into strongcompetitive advantages. They "right-priced" the risks that themarket may have "overpriced" and left the potentially "underpriced"risks to their competitors. But with the increased use of ratinganalytics throughout the industry, the first-mover advantage hasdecreased over the years. Rating sophistication is now table stakesto play the insurance game successfully. Rating isn't then+1 that will provide a competitive advantage. Yet most ofthe analytics effort in personal lines continues to be in makingincrementally better loss cost models.

For those insurers that have a good handle on their loss costs,the n+1 will come from applying that same discipline ofdata-based decision making to other areas of the business.Ratemaking may have been the most obvious place to start, but allparts of the insurance company value chain are open to comparableimprovements through the use of similar advanced analyticstechniques. Customer lifetime value (CLV) analysis, for example, isan analysis that has proven extremely useful in other industrie,sbut is largely underused in property/casualty insurance. At a highlevel, the purpose is to help an insurer understand which segmentsof a book of business actually add economic value to the insurerand which customer segments drain value away. CLV does that bylooking at the total value of the customer relationship with acompany over the total length of that relationship, rather than thepolicy-centric way insurers have traditionally evaluatedprofitability—that is, how profitable a particular policy was overthe policy term.

CLV done right is a major analytic exercise, but it can alsohave wide-ranging strategic implications for an insurer. Thatanalysis can often uncover that a company's best customers areactually destroying its value, what the company believed was itstarget market does not constitute most of its book, or customersegments that have been ignored are more valuable than originallyconsidered.

But CLV analysis is only one example. Perhaps your company'sn+1 will be found in claims models. Fraud is a pervasiveissue for the industry. If you could identify more suspiciousclaims while sending fewer honest claims for investigation, couldyou turn that information to your advantage? Or in productdevelopment, once you've discovered that your customer is really ahousehold and you understand the characteristics of your targethousehold, could you develop a set of policies and options thatbetter fits the needs of your target customers? You may find thatyour target customers prefer the high-touch personalized serviceand expertise they get from a local insurance agent, or you mayfind the opposite—they demand the instantaneous 24/7 self-serviceoptions that the Internet provides. Analytics can also help informinvestment decisions—for example, whether to spend more resourceson expanding an agency force or improving the company's Internetpresence.

The point is there's plenty of opportunity for insurers to findtheir n+1 by focusing analytic efforts in those areas thathave been traditionally under-resourced in the insurance area.Insurers that can be effective first-movers in those areas willfind they may develop a competitive advantage—for a time. But thelandscape will continue to change. Another good thing about being afirst-mover is that it doesn't take size—in fact, being small,agile, and adaptable can be a definite advantage.

Phil Hatfield is modeling data services executive at ISOInsurance Programs and Analytic Services. ISO is a Verisk Analytics(Nasdaq:VRSK) business.