Measuring supply chain performance: the triple E model

• Published in: International journal of productivity and performance management 2022-08, Vol.71 (7), p.2951-2969
• Main Authors: Simão, Luiz Eduardo, Somensi, Karine, Dávalos, Ricardo Villarroel, Rodriguez, Carlos Manuel Taboada
• Format: Article
• Language: English
• Subjects: Business metrics; Carbon dioxide; Carbon dioxide emissions; Circular economy; Customer services; Cycle time; Discrete event systems; Distribution centers; Effectiveness; Efficiency; Electric motors; Emitters; Environmental impact; Flexibility; Inventory; Inventory control; Literature reviews; Manufacturing industry; Objectives; Performance assessment; Performance evaluation; Performance measurement; Strategic management; Suppliers; Supply chains
• ISSN: 1741-0401; 1758-6658
• DOI: 10.1108/IJPPM-06-2020-0291

PurposeThis work aims to measure the performance of an electric motors supply chain (SC) by using the Triple E performance measurement model to assess three performance dimensions simultaneously: efficiency, efficacy and environmental impact.Design/methodology/approachThis research presents a real case of a Brazilian company as an example for applying the Triple E performance measurement model and the discrete-event simulation to assess the performance of an SC.FindingsPerformance measurements for the three dimensions were the following: (1) for efficiency, a high inventory cost in the SC, driven by the distribution center (DC) (49.7% total cost); an order cycle time operating with an average of 21.7 days and a logistic channel transport capacity of 88%; (2) for efficacy, a service level of 98% for all channels; (3) for environmental impact, the SC emits a total of 395,733 kg of CO2 annually, with the DC and the regional distribution center (RDC2) being the largest emitters.Originality/valueThis work allowed to measure the performance of an SC interface (manufacturing process, a DC and three regional distribution centers). It was possible to measure the inventory holding cost and out-of-stock inventory costs, order cycle time, SC service level, transport capacity utilization and CO2 emissions in the transportation process of each SC stage and the whole SC. This study can be used as a decision support guide for academics and practitioners to measure and improve the SC performance.