When you walk into a claim office, you can easily spot the best adjusters. Glowing letters from delighted customers paper the walls. Conversely, managers all learn about the bad apples when they field complaint calls from a policyholder who is either being treated unfairly or is receiving poor service.

Let's consider, however, the vast majority of employees flying below the radar. How does a company decide if their mediocre customer interactions typically result in customers being either "somewhat satisfied" or "somewhat dissatisfied"? Insurers may spend a lot of time and money on customer surveys that are inconclusive in determining why the customer is thrilled or dissatisfied. Did the adjusting staff influence their opinions, or did someone in your chain of service providers leave a lasting impression? There are many people in the auto claim-handling process that could potentially impact your customers' sentiments. These include the agent, call center representative, damage evaluator, liability adjuster, personal injury adjuster, body shop service advisor, or rental facility representative.

How do you fix a problem if you don't specifically know which party is causing it? Even if you ask your customers directly during satisfaction interviews, they often mislabel an adjuster as an agent and vice versa. So how reliable is that information? You certainly can't use such sketchy information for performance management. Instead you resort to a broad-brush approach that reinforces service standards across your entire team or at the leadership level of your suppliers.

Of course, it doesn't have to be that way. If the management team is armed with rich sources of data, then the insurer could analyze that data using relationship analytics. This would enable the company to not only get to the root of claim-handling problems but also to identify the bad apples within an organization for whom others must compensate.

Benefits of Relationship Analytics

Relationship analytics were pioneered by SIUs to predict the probability of fraud when certain doctors, attorneys, or claimants are involved. Relationship analytics tools can similarly be used to reveal the individuals who are the sources of customer dissatisfaction within an organization. They can thus be employed to determine the best approach to solving a problem -- either through changes to personnel, processes, or vendors.

Relationship analytics can offer an insurer the capability to establish the impact of a specific individual's involvement on claim outcomes, policy renewals, customer defections, and claim-related litigation.

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

Once these persons are identified, the next step would be to review their individual processes to be sure they are consistent with company guidelines. If they are complying with company policies and procedures, then the problem may lie in their personal behavior. At this stage, the manager should set goals to reduce the number of times the employee is associated with customer defections. You may find that the individual had no clue that his or her behavior had such a significant impact on customer dissatisfaction, especially if the customers silently defected. Such information could be startling enough to reverse the behavior.

The Sentinel Effect on Performance

Tools that apply relationship analytics to operational performance have the power of providing a Sentinel Effect on employees and service providers. The Sentinel Effect helps ensure that behavior and outcomes improve simply with the knowledge that management can identify who is causing or contributing to the problem. Behaviors typically change when they are no longer cloaked in anonymity.

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

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

This may mean that the most cost-effective service provider may not necessarily be the best choice for customer satisfaction and long-term growth.

Customer Service's Missing Piece

We all know that it is more costly to secure a new customer than to retain an existing one. Relationship analytics can provide the missing pieces necessary to identify and confront the factors causing customers to defect, litigate, or simply become dissatisfied in their dealings with your company. It's time to stop spinning your wheels by second guessing why your customer satisfaction ratings are anemic. Insurance is a business of relationships and finally we have the tools that will enable us to evaluate and repair those relationships.

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

Special Reports /

Relationship Analytics in Performance Management

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