Counting What Will Count: How to Empirically Select Leading Performance Indicator

Facing information overload in today's complex environments, managers look toa concise set of marketing metrics to provide direction for marketing decisionmaking. While there have been several papers dealing with the theoretical aspectsof dashboard creation, no research creates and tests a dashboard using scientifictechniques. This study develops and demonstrates an empirical approach todashboard metric selection. In a fast moving consumer goods category, this researchselects leading indicators for national-brand and store-brand sales and revenuepremium performance from 99 brand-specific and relative-to-competition variablesincluding price, brand equity, usage occasions, and multiple measures of awareness,trial/usage, purchase intent, and liking/satisfaction. Plotting impact size andwear-in time reveals that different kinds of variables predict sales at distinct leadtimes, which implies that managerial action may be taken to turn the metrics aroundbefore performance itself declines.