Optimization of Supply Chain Performance through Simulation Modeling: A Discrete Event Simulation Approach

In today’s competitive marketplace, companies must meet uncertain customer demands by delivering quality products on time and efficiently, demanding proficient supply chain management. However, supply chain management is complex and faces many challenges in practice. Trade-offs among its network components such as providing enough products to customers and the cost associated with keeping them in stock, constitute one of its main challenges. This study addresses this challenge by optimizing customer service levels with possible minimum inventory costs in the multi-echelon supply chain context. Considerable improvements were observed by leveraging a discrete-event simulation approach within the downstream supply chain of Saba Dimensional Stones Plc (SDS) and using the OptQuest optimization tool embedded in Arena. Customer service levels increased from 58.81–70.18%, whereas stock-out rates decreased from 39.8–24.52%, significantly reducing inventory costs by approximately 28.8 million ETB. In addition, remarkable decreases in lost sales and backorder levels at DCs and buffers highlight the efficiency of the proposed approach. In addition to addressing the trade-off between customer service level and inventory-associated costs, this study highlights the broader implications of simulation modeling in enhancing overall supply chain performance. These findings demonstrate that maximizing their customer service level with a possible minimum cost of inventory that focuses on customer demand fulfillment is fundamental to survival in market competition. It acknowledges, however, the need for consideration of additional factors such as environmental, social, and ethical concerns. In conclusion, this study offers valuable insights for future endeavors in supply chain optimization, providing practical recommendations to enhance managerial decision-making and ultimately determine business success.