<![CDATA[Efficient supply chain management in the retail sector is crucial for cost reduction and enhancing customer satisfaction. This study analyzes and optimizes inventory management using a data-driven simulation approach. By leveraging data on customer demand patterns, replenishment cycles, and delivery times, the research develops simulation models to evaluate inventory strategies under various scenarios, including high demand and seasonal fluctuations. The findings reveal optimal inventory strategies that minimize holding costs while maintaining product availability. Key performance metrics, such as fill rate and stockout levels, show significant improvements when simulation-based strategies are implemented. For example, under high-demand scenarios, the proposed model achieved a 20% reduction in holding costs and a 15% increase in fill rates compared to traditional methods. These results highlight the importance of integrating simulation techniques into retail supply chain management to enhance decision-making and operational efficiency. This research contributes to the literature by providing a practical framework for inventory optimization and offers actionable recommendations for retail managers to adopt technology-driven approaches. Future research should explore applying these methods to retail sectors with diverse demand characteristics. ]]>
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