CASE STUDY:
Performance Support for Customer Service Call Center

Stanley E. Malcolm, Ph.D.

This case is adapted from a real situation as reported by Gloria Gery, a leading consultant in the field of electronic performance support systems (EPSS).

Before EPSS: A credit card company uses customer service representatives (CSRs) to take calls from card-holders. Some of those calls are from people who wish to cancel their accounts. However, it is in the company's interest to retain the "good customers" so it is not just a matter of doing what customers ask - at least not until the CSR has evaluated the customers' "worth" and made reasonable attempts to keep them if they meet the criteria of "a good customer."

For the sake of simplicity, let's say that a good credit card customer is one who maintains a balance and pays slightly late (so the company earns interest and late fees but ultimately gets paid). Of course the business "rules" are much more complicated than that, depending on how big a balance, how late, what interest rates are being charged, what regulations apply in a given locality, etc. Under a traditional training model, CSRs would have to learn all those rules, then apply them to customer information gleaned from various screens of "the system" in order to build a mental model of the customer's worth. Once CSRs had created that mental model, they would then have to know what they could offer to entice good customers to keep their account opens (e.g., a lower interest rate - but how low?).

What I've just described is a situation doomed to failure: Some CSRs will "never get the word" and operate from outdated rules about what makes a customer worth retaining. Others may know the rules but elect not to make the effort (perhaps they are measured on the volume of calls they handle versus quality of customers retained?). Imagine too what happens when the company's definition of a good customer changes: You can bet it will take months for training to reach the CSRs, meaning that for quite some time people will be "doing the wrong thing" from a business strategy perspective.

The EPSS Solution: Applying an EPSS approach virtually guarantees that every CSR will "do the right thing" every time. This factor alone - the ability to change business strategies literally overnight and have them 100% implemented the next day - is of enormous significance to the case for an EPSS approach.

An EPSS was built for the credit card company's CSRs. Now when the same type of call comes in, CSRs simply enter the card number and select the requested transaction type (cancel account). Given that information alone, the system can assemble the relevant facts from the customer's data, apply a set of rules about what makes a customer "good", and report the results to the CSR. The CSR sees a graphic representation that looks vaguely like a thermometer:

• If the thermometer is full (representing a good customer), text appears beside it saying "This is a good customer because... they maintain a balance... etc." It will also tell the CSR exactly what they can offer as incentives for the customer to retain their account.
• If the thermometer comes up empty (a "bad" customer), the advice would be simple: "Process the request, as follows..."

The design I've just described illustrates an important aspect of EPSS: It doesn't "dumb down" system users. Note how the system doesn't just give the answer. Rather, it explains it in a way by which users can come to understand the "rules."

Some people are wary of EPSS, fearing that the approach makes automatons out of workers. That certainly isn't the case here. What this EPSS does is allow humans to focus on what they do best, eliminating the kind of rote learning (e.g., on which screen to find which critical piece of information) that does nothing to enrich employees' lives or "empower" them to contribute more to the company.

About the Author: Stan Malcolm serves as a coach to companies wishing to develop or review their strategies for performance support, learning technologies, and/or corporate learning issues generally. Formerly, he headed learning technologies and performance support initiatives at Aetna, Inc. He can be reached at Stan@Performance-Vision.com or 860-295-9711.