Title: Real-Time Predictive Analytics and Business Intelligence for Accurate Demand Forecasting and Inventory Management in Modern Supply Chains
Authors: Julius Olatunde Omisola, Emmanuel Augustine Etukudoh , Ekene Cynthia Onukwulu and Grace Omotunde Osho
Volume: 9
Issue: 4
Pages: 274-287
Publication Date: 2025/04/28
Abstract:
The increasing complexity of global supply chains and heightened consumer expectations demand innovative approaches to demand forecasting and inventory management. Real-time predictive analytics and business intelligence (BI) are transforming traditional supply chain practices by leveraging data-driven insights to optimize operations, reduce costs, and enhance customer satisfaction. This review explores the integration of real-time predictive analytics and BI tools in modern supply chains, focusing on their applications for accurate demand forecasting and efficient inventory management. Predictive analytics, driven by machine learning and artificial intelligence, enables businesses to anticipate demand patterns by analyzing historical and real-time data. These models account for seasonal variations, market trends, and external disruptions, allowing organizations to adapt quickly to changing conditions. Simultaneously, real-time inventory management systems utilize predictive insights to monitor stock levels, optimize reorder points, and minimize holding costs. The implementation of IoT devices and cloud-based solutions ensures seamless data collection and analysis, providing organizations with a unified view of their supply chain. Business intelligence complements predictive analytics by offering visualization tools and interactive dashboards that aid decision-making. With BI, organizations can identify underperforming products, track KPIs, and simulate scenarios to mitigate risks. The integration of predictive analytics and BI enhances supply chain agility, enabling proactive responses to disruptions and improved resource allocation. However, challenges such as data integration, technological complexity, and security concerns persist, requiring strategic planning and investment. This review highlights the transformative potential of real-time analytics and BI in reshaping supply chains, emphasizing their role in achieving operational resilience and maintaining a competitive edge in dynamic markets. By adopting these advanced tools, organizations can ensure accurate demand forecasting, efficient inventory management, and sustainable supply chain performance.