The most advanced corporate performance measurement systems, such as balanced scorecards, are now built around "business models" or "strategy maps" that incorporate a number of beliefs or assumptions about cause-and-effect relationships between and among the measures. In most companies these business models are developed intuitively and their validity is rarely, if ever, subjected to formal, empirical tests. If some of the beliefs underlying their model are wrong, managers could then focus on the wrong things. They could endeavour to improve performance factors that are not important, or possibly even harmful.
But how should managers test the validity of their business models? Is it easy to do? Our CIMA-spon-sored study sought to test one company's business model to provide insights, both about how to conduct these tests and what to expect from them.
Our site was a medium-sized medical test equipment manufacturer with a single operating unit. We gained access to the entire set of data that was monitored on a quarterly basis by the company's board of directors and top management over an eight-and-a-half-year period (1Q98-2Q06). Conditions seemed favourable for conducting business model tests. The company operated in a single line of business with only one business model (or strategy), so the overall corporate performance measures were not distorted by shifts in cross-business sales mix. The company's top management, its strategy and its business model remained constant for the entire period of our study. And since the company's stock was publicly traded on the New York Stock Exchange, we were able to test whether the elements of the business model were, individually and collectively, leading indicators of both financial performance and shareholder value creation.
The data to which we had access comprised only a "dashboard" because the managers' understandings of how the measures were linked, and which were most important, were only implicit. Company management certainly had beliefs and understandings as to what measures were important to monitor, but they had not expressed relations between and among the measures as a formal business model. Before we began our tests we conducted interviews with top management and directors to make explicit their beliefs about what elements in the dashboard described the company's business model and how those elements were related. This business model is shown in Figure 1.
This company developed, manufactured and sold equipment used for performing medical diagnostic tests. The instruments (that is the name used for the test equipment) were "closed systems", meaning that they worked only with the company's own test kits (called "reagents"); they could not use other manufacturers' reagents. The strategy the company followed is commonly referred to as a "razor/razor blade" strategy. That is, it sold the instruments at a small mark-up. It then made most of its profits selling the reagent kits needed to perform the tests.
We subjected the managers' model to formal statistical tests and generated three primary empirical results. First, while management believes that there are four important "performance drivers", or leading indicators (shown by the highlighted boxes in Figure 1), only two (R&D expenditures and instrument placements) were consistently associated with future financial performance. We found that the other two (test reagents approved and changes in gross margin percentages) provided little or no incremental information useful for predicting future financial performance. Second, we examined the specific paths by which the different leading indicators in the company's business model relate to each other in a time-dependent causal sense and found support for only one sub-path (R&D expenditures - instrument placements - revenues - operating income). Finally, we found that the leading indicators in the company's business model contain little or no information about its stock returns once we take into account other predictors of stock market valuation. …