Optimizing Inventory Management through Advanced Forecasting Techniques in Supply Chains

Abstract

Inventory management performance is a critical aspect of supply chain operations, impacting cost, customer satisfaction, and overall efficiency. Practices vary globally, with examples from the USA showcasing benefits of advanced forecasting, Canada emphasizing technology like RFID, Europe adopting JIT systems, and African countries leveraging technology for data accuracy. The general purpose of the study is to investigate how changes in advanced forecasting techniques influence inventory management performance. Despite technological advancements, businesses grapple with suboptimal inventory management, leading to excess costs and stockouts. The literature primarily focuses on traditional forecasting methods, lacking a comprehensive exploration of advanced techniques' impact. This study aims to fill this gap by investigating how advanced forecasting optimizes inventory management, providing empirical evidence and practical insights. Studies across regions emphasize the positive impact of advanced forecasting. In the USA, advanced techniques enhance supply chain responsiveness. Canada benefits from RFID technology, Europe from JIT systems, and Africa from cloud-based inventory systems. Collaborative forecasting improves outcomes, and resilience strategies during the COVID-19 pandemic are crucial. Sustainable practices contribute to both environmental and economic goals. Research gaps include a need for a more extensive geographic scope, conceptual integration with emerging technologies, and longitudinal studies to assess sustained impacts of advanced forecasting techniques. The study involves a comprehensive examination of existing scholarly works, encompassing books, journal articles, and publications, to understand the current state of knowledge within the field. Companies embracing advanced forecasting techniques experience substantial improvements in inventory management performance. Real-time data, machine learning, and collaborative approaches are critical components. The study highlights the positive impact of advanced forecasting on different industries, emphasizing its versatility. The study contributes to the Theory of Constraints, offering a framework for understanding advanced forecasting's impact. Practical implications guide practitioners, and policy recommendations advocate for widespread adoption. The study contributes to sustainability discourse and addresses industry-specific policy considerations. Overall, it advances our understanding of how advanced forecasting enhances inventory management within supply chains.