Demand uncertainty is one of the major challenges in operations and supply chain management, as it significantly affects the effectiveness of inventory management. Unpredictable fluctuations in demand may lead to excess inventory (overstock), inventory shortages (stockouts), increased operational costs, and a decline in customer service levels. This study aims to analyze various inventory management strategies that organizations can implement to address demand uncertainty and to evaluate their implications for operational performance. The research employs a systematic literature review by examining a wide range of scholarly articles, academic books, and recent studies related to inventory management, demand forecasting, supply chain resilience, and digital technologies in inventory management. The findings indicate that effective inventory management strategies include the implementation of demand forecasting, safety stock, reorder point systems, ABC analysis, supplier collaboration, multi-sourcing strategies, and the adoption of digital technologies based on artificial intelligence and big data analytics. The implementation of these strategies enhances operational efficiency, reduces inventory costs, improves customer service levels, and strengthens supply chain resilience. This study provides a conceptual contribution to the development of operations management theory and serves as a valuable reference for practitioners in designing adaptive inventory policies to cope with dynamic business environments.
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