Improving project-profit prediction using a two-stage forecasting system
Computers and Industrial Engineering
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Arguing that GAAP is ill suited for estimating the future profitability of intangibles, the accounting literature (e.g., Kaplan and Norton 1996, Lev 2001) has recently proposed alternative measurement models. These models view intangibles as composed of a set of fundamental business activities and use multiple financial and nonfinancial metrics causally interlinked to profits to represent this view. Using a unique and proprietary cross-sectional data set of the retail banking industry, we provide some of the first tests on the empirical validity of such measurement models. We characterize the core deposit intangible, an important retail banking intangible representing a bank's relationships with its customers, using financial and nonfinancial metrics on price, service, customer usage, and customer satisfaction. We find that the metrics do not individually predict future earnings, but gain individual significance in a collective setting, increasing the predictive power substantially. We argue that this result occurs because the activities underlying the measures are causally interlinked to profits and explicitly illustrate these linkages with a structural path model. Our measurement model also predicts significant interactive effects in the way our measures are informative about future profits, and we document such effects, not just among the individual measures, but also across the measures and environmental factors such as the bank's strategy. In sum, our measurement model illustrates the key drivers, measures, and interactions in retail banking customer relationships.