Options for Operationalizing Decision Equity

We conceptualize decision equity in terms of the present value of the future incremental cash flows that result from a managerial decision. While the underlying premise of this concept may be familiar, appealing, and powerful, its implementation is often not as simple or straightforward. This should not come as a surprise because the range of strategic decisions and the flowprints of their downstream consequences vary significantly across industries, firms, and over time. In each case, one of the early questions that comes up is the definition of the benchmark relative to which the value of decision equity will be computed. In other words, as a firm prepares to implement a new action plan and wishes to measure the cash flows attributable to that decision, the question always is what reference level should it use to estimate the benefit it can achieve from the proposed implementation?

In our experience, there are typically two options available to decision makers. The first is adopting the status quo as a benchmark. This approach sets up the floor for the computation of decision equity under the assumption that doing nothing would result in no incremental changes in the ultimate outcomes and would therefore have decision equity of zero. The second option is to compare the decision equity associated with a particular action plan with equities associated with similar other action plans that might be implemented. This way, decision makers can estimate the equities associated with multiple decisions, and then compare and evaluate them on common downstream metrics.

Estimating Decision Equity Relative to the Status Quo

The easiest way to understand the status quo approach is to go back to the flowprint discussion earlier in the chapter, and imagine that none of the interconnected parts is undergoing any movement from the current state. In other words, everything that the organization did in the previous time period will continue to operate identically, and continue to provide some downstream results. Now imagine that the decision maker decides to make a change to a particular area of performance. As a result, much like a series of gears connected to each other, the change will generate movement in the web of relationships. This movement will eventually move the final node of the web, the chosen downstream metric, in a positive or negative direction, by a certain magnitude. The change in intermediate markers throughout the web of relationships, and eventually in the downstream measure, such as cash flow, can then be evaluated over a period of time to estimate the equity associated with the change.

When the status quo is a benchmark, it is important to recognize that if a decision maker alters one node, it is unreal to expect everything else to stay the same. For instance, if a firm invests in improved distribution of its product, competition might undertake an action, such as price reduction, which can influence the focal firm’s effort to increase market penetration through increased distribution. A model generated through a comprehensive flowprint will account for these consequential or conditional effects and not assume that the world would not respond to an action chosen. In our example, the firm would perhaps need to account for a potential price drop by a competitor when estimating the decision equity associated with the change in its own distribution.

Under this approach, we assume that the current state of affairs or the status quo represents the starting point. If an action results in an incremental increase in future cash flows, then there would be some positive decision equity associated with it. In other words, decision equity is measured as the incremental change in the present value of the future cash flows resulting from an action. The challenge is establishing both the starting point and the change resulting from the action under consideration. A part of the reason for the challenge is that most managers and executives do not have information on the cash flows associated with the status quo, and do not necessarily plan with cash flows as a primary metric. However, it can be computed at the start of a linkage analysis project.

In order to delve deeper into this issue, let us consider the case of a leading property and casualty insurer in the United States. The firm was performing relatively well and was aspiring to grow very aggressively. However, management was unsure whether future growth would come more from acquiring new customers or increasing the rate of retention among existing ones. Field agents strongly influenced customer management at this firm, and were, in turn, influenced by the structure of their bonus payments. The bonus computation and agent ranking system that was in place at the firm for a long time was designed with customer acquisition in mind. It rewarded agents with strong acquisition capabilities and therefore promoted an acquisition-centric culture across the organization. However, over time, the pool of available customers shrank, and the firm was forced to review its customer management strategy. The new strategic thinking gave more weight to retention than the previous mind-set.

The finance department of the firm weighed in on the strategic decision to shift from customer acquisition to customer retention. However, in its assessment, the impact of the new customer orientation was contingent on which metric was to be used to make the strategic call. Continuing with an acquisition focused strategy was still a superior alternative from a revenue or premium perspective. However, retention seemed to be more promising from a margin or profit perspective because the cost of acquiring customers at this firm was more than that of retaining them.

Now because this firm had an existing acquisition-oriented customer management program, the current practice and the cash flows resulting from it would be considered the status quo or the starting point. The identifiable strategic shift was the decision to switch from an acquisition orientation to a retention orientation. The specific action associated with this intended shift was a change in the compensation structure of the field agents. The change could result in a rise or fall in the cash flow stream generated because of changes in customer margins, retention versus acquisition costs, bonus payments, and other cash costs. The discounted present value of these incremental changes would therefore constitute the decision equity related to the strategic action of switching from customer acquisition to customer retention, and altering the bonus structure for field agents. On the other hand, if the management of the firm were to choose to continue with its customer management strategy, there would be no equity associated the strategic choice because it did not deviate from the status quo. In this case, the analysis revealed that the switch from an acquisition to a retention orientation would have resulted in net positive decision equity because of higher margins and smaller customer management costs. Consequently, the firm realized that the current strategy of revenue growth was coming at the expense of profitability and made the switch toward the new orientation.

Now as an aside, let us imagine what would happen to the customers of the firm following the decision to switch the customer management strategy. The firm’s customer base could possibly shrink relative to what it would have been under the existing system. It is also possible that the value of each of the remaining customers would be higher than what it was under the current environment of high customer churn rates under an acquisition oriented strategy. The question we should ask ourselves is whether there was a change in the lifetime value of the firm’s individual customers and their collective customer equity. In other words, did the customer equity go up or down? The answer in this case could be that the average lifetime value of the remaining customers would perhaps be higher than before. However, it could very well be the other way around in a different context. The important question however is whether the equity associated with a proposed action is positive or not. The lifetime value of the customers is a consequence or a beneficiary of the action and should be a secondary consideration. It may go up for some high equity decisions and may go down for others. However, in either case, customers are not the residence of the change in equity.

Estimating Decision Equity Relative to Other Options

In reality though, an organization has multiple decision makers and functional areas, and each of them is constantly making changes, small or large, in their daily operations as well as their strategic plans. From a flowprint perspective, one can imagine that the web of relationships among actions and consequences is constantly changing. In the world of pharmaceutical manufacturers for example, three plans might be implemented simultaneously. The sales team might invest in initiatives that can increase sales force knowledge of the drug as well as the therapeutic category. The brand team might invest in new promotional materials. Finally, the managed care team might work on improving physician access to the drug under various health insurance plans. Each of these decisions will have an influence on the cash flow of the organization, and under a properly specified model we can estimate them fairly accurately. The relative equities of each of these decisions can then be compared to identify the one with the greatest potential.

In our experience, this particular method of estimating decision equity seems to be the most prevalent. Decision makers are often interested in estimating the financial returns associated with alternate investment options, and juxtaposing them next to each other on common downstream metrics. Such comparisons are often done using simulators, wherein decision makers use information derived from robust statistical analysis, and couple it with their experience to estimate the equity of multiple decisions. The ability to compare them on a common metric, such as the future cash flows, makes the comparison more equitable. While some inputs to these estimations might not be completely scientific, such as the selected time period over which the proposed benefit will accrue, the analyses still offer very valuable guidance to decision makers when comparing alternate and hitherto noncomparable investment decisions.