Benchmarking in the Supply Chain Using Data Envelopment Analysis and System Dynamics Simulations

Nowadays performance evaluation is necessary for selecting a proper combination of all the supply chain resources in the best possible way, to provide products and services in the market. One approach for measuring the supply chain efficiency is the data envelopment analysis (DEA), which involves the use of past and present inputs and outputs to evaluate the supply chain performance. Therefore, the outcome of the DEA evaluation is not suitable for providing a benchmark for the future. Hence, managers are not able to improve the activities of their subset by using the results of DEA model directly. For this purpose, we forecasted the data of the units under evaluation using system dynamics simulation and then we presented a proper model to formulate strategies for improving performance using the proposed DEA model. Finally, we implemented the designed algorithm in the milk industry of Fars province (Iran), and proper strategies for improving the efficiency of this industry were developed.