Multi‐factor menu analysis using data envelopment analysis

Purpose – The purpose of this paper is to develop a multi‐dimensional, holistic model that: avoids the variable interdependency found in earlier tools; and integrates multiple factors that characterize menu item costs more accurately by considering more than gross profit. Design/methodology/approach – Using data gathered during a three‐month period from three same‐brand units of a full‐service chain restaurant firm, the paper applies data‐envelopment analysis (DEA), a non‐parametric approach that accounts for both controllable (discretionary) and uncontrollable (non‐discretionary) variables, producing a single relative‐to‐best index based on an efficiency rating calculated on a 0 to 1 scale. Findings – The findings suggest that the DEA‐equipped model, which is not constrained by the limitations of traditional matrix approaches, supports a more robust approach by incorporating more cost determinants than traditional menu engineering approaches. Research limitations/implications – The paper consists of only a single restaurant concept and the evaluation results are purely theoretical. Future research should include the application of the menu analysis recommendations to an actual menu to determine the effectiveness of the model on actual operation profitability. Practical implications – The research suggests that DEA is an effective tool in the evaluation of a restaurant menu by evaluating individual menu items based on attributes of labor and profitability factors. Originality/value – The paper shows that by combining DEA with traditional menu analysis methodologies, a more efficient menu analysis tool may be utilized to evaluate menu items without the arbitrary allocation of non‐food costs.