Time and space efficiency in storage systems: A diagnostic framework

Warehouse management and optimization aim at improving relevant metrics of performances and associated costs. To meet these goals becomes hard when scarce data are available, and the supply chain is not vertically integrated. This is, often, the case of 3PL providers whose customers are not willing to share data. Nevertheless, storage managers always need benchmarks of warehouse time and space performances to identify whether a storage system is performing well. Benchmarking of a storage system is rarely considered in warehouse science, for this reason it is the focus of this paper. This study aims at illustrating a decision support framework to (1) assess the behaviour of the storage system, to (2) quantify metrics and key performance indicators (KPIs), to (3) benchmark the nature of the storage system, and to (4) diagnose issues and criticalities even when a limited amount of data is available to storage managers. This framework is made of a set of tools that all lie on the picking data records, which are typically available at any warehousing system. The tools calculate KPIs easy-to-read by practitioners who want to investigate the behaviour of the SKUs and the criticalities of the storage system. The framework is applied to evaluate KPIs in a 3PL case study. Each KPI is linked to a practical issue and gives advices to practitioners to address it. The framework is implemented using Matlab and its outputs are presented, described and discussed in the paper through graphical and numerical analysis aiming at the improvement of the storage system performance.