Analytical and Simulation Models as Decision Support Tools for Supply Chain Optimization - An Empirical Study

Decision support tools for supply chains that are unreliable due to uncertainty over the best tool to utilize, whether it be analytical or simulation, can result in inefficiencies, higher costs, subpar customer service, and lost business prospects. The performance of a supply chain can be increased by implementing an efficient system, which can also improve decision-making and streamline procedures. The objective of this study is to compare the use of analytical models and simulation models in the analysis and improvement of supply chain operations. A few cases of application of both decision support tools were evaluated. The comparison was implemented by considering factors such as level of details, cost, speed, time reference, metrics, and the kind of problem to be solved. The result of the analyses reveals that both types of models improved the supply chain understudied. However, to have a more robust and resilient supply chain optimization, it might be beneficial to apply both models simultaneously.