An Exploratory Investigation of Multiunit Restaurant Productivity Assessment Using Data Envelopment Analysis

Abstract

SUMMARY Conventional approaches to assessing unit-level productivity, such as labor-cost percentages or basic ratio analysis including sales per labor hour, are limited in utility because they integrate too few operational characteristics to portend true operational efficiency. Moreover, current parametric approaches impose a functional form relating independent variables uniformly to dependent variable(s) and provide only an average by which other operations are compared. Data envelopment analysis (DEA), a linear-programming-based benchmarking technique that explicitly considers weighted outputs and inputs, is introduced as an alternative. DEA does not require any assumptions about functional form and calculates a maximal performance measure for all units in the population. As an exploratory investigation, data from 38 same-brand midscale restaurants were analyzed. Results, which include relative-to-best efficiency valuations, suggest that data envelopment analysis offers considerable potential for managers looking to accurately assess productivity. The viability of key variables as part of the DEA application is also discussed.

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