An integrated benchmarking approach to distribution center performance using DEA modeling

Abstract This research proposes an integrated benchmarking framework illustrated in the context of a large supply chain system comprised of 102 distribution centers (DCs). We employ recent extensions of data envelopment analysis while addressing difficulties often associated with empirical data in real life settings. The study measures DC productivity in a large scale setting, evaluates and identifies DCs with consistent best performance using facet analysis, and detects performance trends using window analysis of 4 years’ data. This extensive evaluation of the empirical production frontier and of “role model” DCs provided very interesting insights for strategically managing operations. Our approach opens up possible new directions for examining supply chain DCs or other activities where explicit knowledge about the relationship between the inputs and outputs is not well known.