A Performance Measurement System for Staff of the Logistics Section: A Case Study for an Oil & Gas Company

Abstract

Companies recognize the central role performance measurement plays in their success and are therefore becoming increasingly enthusiastic about their performance measurement efforts. Performance measurement indicators not only support the daily operation of the organization, but they are valuable in formulating any emerging problems as well. Logistics encompasses a complex set of activities that require an equally complex collection of metrics to adequately measure performance. However, many performance measurement systems have neither kept up with the changing role and scope of logistics nor have they been systematically examined or evaluated. Performance measurement systems should be evaluated at both the individual metric and system-wide levels in order to maintain relevance and effectiveness. This study aims to present the empirical findings and lessons learned from a field research on the development of the performance measurement system (PMS) for the logistics department of an Oil & Gas company. The implementation focuses on the procedure rather than on the structure of PMS offering a conceptual procedural framework with information and insights on how to design, implement, use, and assess a PMS, addressing an important gap identified in the literature. This research focuses on the evaluation of staff of the supply chain. Specifically, we propose a set of recommended criteria that can be applied to evaluate staff of the relevant department and demonstrate the use of these criteria through the evaluation of drivers’ performance. The primary motivation for evaluating performance at that level is that measurement systems guide management decisions. A well-crafted system of metrics will lead toward better decision-making by managers. The entire research effort lasted almost 6 months, involving multiple interactions between a researcher from academia and a practitioner from the company. Ultimately, the main findings are as follows: (1) how we can evaluate a drive; (2) the indicators and their parameters that contribute in revealing our assumptions about “good” and “bad” driver; (3) developing a prototype PMS; and (4) the use and review of the new PMS has led to improvements in people’s behavior, development of organizational capabilities, and improved performance results.