When you walk into a claim office, you can easily spot the bestadjusters. Glowing letters from delighted customers paper thewalls. Conversely, managers all learn about the bad apples whenthey field complaint calls from a policyholder who is either beingtreated unfairly or is receiving poor service.

Let's consider, however, the vast majority of employees flyingbelow the radar. How does a company decide if their mediocrecustomer interactions typically result in customers being either"somewhat satisfied" or "somewhat dissatisfied"? Insurers may spenda lot of time and money on customer surveys that are inconclusivein determining why the customer is thrilled ordissatisfied. Did the adjusting staff influence their opinions, ordid someone in your chain of service providers leave a lastingimpression? There are many people in the auto claim-handlingprocess that could potentially impact your customers' sentiments.These include the agent, call center representative, damageevaluator, liability adjuster, personal injury adjuster, body shopservice advisor, or rental facility representative.

How do you fix a problem if you don't specifically know whichparty is causing it? Even if you ask your customers directly duringsatisfaction interviews, they often mislabel an adjuster as anagent and vice versa. So how reliable is that information? Youcertainly can't use such sketchy information for performancemanagement. Instead you resort to a broad-brush approach thatreinforces service standards across your entire team or at theleadership level of your suppliers.

Of course, it doesn't have to be that way. If the managementteam is armed with rich sources of data, then the insurer couldanalyze that data using relationship analytics. This would enablethe company to not only get to the root of claim-handling problemsbut also to identify the bad apples within an organization for whomothers must compensate.

Benefits of Relationship Analytics

Relationship analytics were pioneered by SIUs to predict theprobability of fraud when certain doctors, attorneys, or claimantsare involved. Relationship analytics tools can similarly be used toreveal the individuals who are the sources of customerdissatisfaction within an organization. They can thus be employedto determine the best approach to solving a problem -- eitherthrough changes to personnel, processes, or vendors.

Relationship analytics can offer an insurer the capability toestablish the impact of a specific individual's involvement onclaim outcomes, policy renewals, customer defections, andclaim-related litigation.

Think about the powerful insight made possible from a list thatidentified customers who recently defected and all the individualswith whom they interacted. The list would include employees withinyour company as well as the service providers that are integratedwith your process -- all of whom represent your company in yourcustomers' eyes. Suddenly, common patterns would emerge that revealthe repeated involvement of specific individuals or providers.

Once these persons are identified, the next step would be toreview their individual processes to be sure they are consistentwith company guidelines. If they are complying with companypolicies and procedures, then the problem may lie in their personalbehavior. At this stage, the manager should set goals to reduce thenumber of times the employee is associated with customerdefections. You may find that the individual had no clue that hisor her behavior had such a significant impact on customerdissatisfaction, especially if the customers silently defected.Such information could be startling enough to reverse thebehavior.

The Sentinel Effect on Performance

Tools that apply relationship analytics to operationalperformance have the power of providing a Sentinel Effect onemployees and service providers. The Sentinel Effect helps ensurethat behavior and outcomes improve simply with the knowledge thatmanagement can identify who is causing or contributing to theproblem. Behaviors typically change when they are no longer cloakedin anonymity.

Think about how relationship analytics can be used to compareservice providers and quantify their impact on outcomes, renewals,defections, and litigation. Relationship analytics can show you thebigger picture and answer key questions: Are they helping you orhurting you? Have your service providers found ways to game thesystem based on traditional measurements?

In metropolitan areas where there are many choices for alternateservice providers, you need tools to help manage your business andsecure the best long-term outcomes.

This may mean that the most cost-effective service provider maynot necessarily be the best choice for customer satisfaction andlong-term growth.

Customer Service's Missing Piece

We all know that it is more costly to secure a new customer thanto retain an existing one. Relationship analytics can provide themissing pieces necessary to identify and confront the factorscausing customers to defect, litigate, or simply becomedissatisfied in their dealings with your company. It's time to stopspinning your wheels by second guessing why your customersatisfaction ratings are anemic. Insurance is a business ofrelationships and finally we have the tools that will enable us toevaluate and repair those relationships.

This article represents the last in a series about leveraginganalytics to improve business outcomes, claim efficiency, andcustomer service. Other articles include The Next Frontier: Straight-Through Claim Processing, Business Analytics Enable Better Leadership, and Redefining the Business Analyst.