Identifying Growth Potentials with Internal Benchmarking across Product Categories and Markets

A common question facing many multicategory, multi-market vendors is: “How much potential for growth is there for every product category we sell in each market we serve?” Answers to this question are important because they help managers focus attention and prioritize efforts in their search for growth opportunities. We propose a modeling framework that allows the firm to benchmark its sales in one market and category against its own sales in all the other markets and categories, factoring in observed as well as unobserved variables that might influence sales potential. Our approach extends stochastic frontier regression to the multivariate case, leading to a factor-analytic frontier analysis that leverages on the correlation pattern in performance data across product categories and markets. This multivariate factor-analytic approach produces a measure of relative sales efficiency, reflecting the gap between observed category sales per customer in a market and an estimated "sales frontier,” which is largely shaped by observed sales per customer across all categories and markets. Such cross-category crossmarket internal performance benchmarking approach is novel as well as practical, because it allows firms to identify short-term growth opportunities by product category and market, using readily available data from their own customer databases.

Keywords: internal benchmarking, category management, retail performance, sales

efficiency, multivariate factor-analytic stochastic frontier regression, market