A Case Study

A case study that involves a leading credit card issuer operating in both the United States and various other parts of the world illustrates the concept of decision equity. The company wanted to identify ways to build stronger relationships with its credit card holders, in order to foster more favorable customer behavior, such as greater card usage, without an increased risk of defaults and bad loans. In order to meet this goal of greater customer centricity but with limited default rates, the firm formulated a research program. As the program unfolded, the firm did not limit itself to finding a solution within any specific, existing paradigm, such as product enhancement, that would improve card features and enhance perceptions of quality. Instead, it encouraged a paradigm-free discussion, not leaving any strategic options off the table.

Unlike in paradigm-driven discussions, this process generated a wide variety of often-unrelated strategic options with very different downstream consequences. The short-listed ones included the traditional product-centric options such as making changes to card features and including customized designs and a cash back bonus. A completely different strategic direction that focused on enhanced service was also on the table. This option envisaged the introduction of completely new services such as travel assistance and insurance offerings. A third option was a customer-specific reward and penalty system that included waiver of occasional late fees for heavy and responsible cardholders. A fourth option was to make changes in advertising and promotional messages with a view of modifying the brand’s positioning. A fifth option was to review the processes and employee engagement levels at the company’s call centers in order to improve the service resolution experience.

What is noteworthy is that, even with a simple and common overall goal, a paradigm-free approach generated a superset of actionable options that was far greater that what would have been possible with narrower mental models focused on product, or service, or brand, or employees. Instead, every conceivable solution was given fair consideration to assess its viability during the initial stage of the research program. While deliberating on these alternate and not mutually exclusive solutions, it also became apparent very early on that the research would need to span across multiple organization silos to unveil the pathways to achieving the terminal business objective of favorable enhanced card usage among the current customers.

In the next stage, the research team followed multiple routes to estimate the likely financial impact of each alternative course of action. It delved into the operations of the call centers and critically reviewed the employee practices that were under the aegis of the human resource function. It also reviewed the marketing plans and customer loyalty practices within the organization. It dug deep into the financial and accounting data pertaining to customer behavior. It talked at length with the team responsible for designing and reviewing card features and policies. And finally, it held extensive discussions with innovation teams tasked with introduction of new services to enhance revenues for the organization.

Based on these widely different and often unrelated explorations, the consideration set of potential strategic options was narrowed down. The next step was to examine the linkages across the various decision domains using the available data. These linkages constituted the cause-and-effect chains tied to each specific decision. For instance, one solution that was tested involved the decision to modify the processes at the customer call centers. In order to estimate the effects of the action, linkages were developed first between the levels of employee engagement within a call center environment and the employee ability to resolve customer issues effectively and efficiently. Simultaneously, the links between efficient resolution of customer problems and customer loyalty and between loyalty and subsequent customer usage of the card were examined. The short-term and long-term equity associated with a decision to change the policy to enhance call center employee engagement was then estimated on the basis of the strength of this sequence of linkages (Figure 5.1). While the short term focused mostly on the higher costs associated with the process revisions in the call center, the long-term equity estimation included the benefits that accrue from improved customer loyalty.

In sharp contrast, the discovered linkages associated with the strategic option relating to a modified penalty structure for late fees were completely different. In this case, the exploration focused on the impact of late fees on subsequent customer perceptions of the credit card issuer. Specifically, the research focused on the differential impact of late fees and customer perceptions and usage of the card across transactors (those that pay off entire outstanding balance every month) and revolvers (those that do not pay off full amount every month). The net impact or the equity related to the decision of using the alternative fee structure was estimated by comparing the changes in the resulting behaviors of the two segments of customers. A similar process was repeated for all alternative decisions to discover the linkages between the action and the likely consequences. The results from each exploration were then used to assess and compare the value or equity associated with the respective decisions. Needless to say, the linkages associated with each decision were remarkably different from those for every other. Yet the alternatives could ultimately be compared on a common scale based on the decision equity associated with each.

Overall, the portfolio of analyses provided the necessary decision support to management by allowing them to objectively compare alternate strategic options under consideration using the power of data, linkages, and decision equity. Such a comparison was possible because the research project was paradigm free and spanned and linked multiple decision domains. It favored the estimation of the impact of each potential strategic decision and a computation of the decision equity through a process of data-driven verification. At the culmination of the process, all the functional managers were able to compare a diverse set of strategic options using a common language of linkages and dollars and cents. This was in sharp contrast to what we normally observe in either a paradigm-based or a silo-based culture of decision making. In this case, the call center managers did not focus exclusively on improvements in productivity within their operations or changes to the first-call resolution performance. The human resource managers did not talk about their silo-based set of metrics that tended to focus largely on employee productivity and training. Instead, the focus on decision equity drew linkages across these functional silos to unveil the impact of a diverse portfolio of decisions, each with their own unique linkages, on the strategic goals and bottom-line performance of the organization.