Abstract

In regulated industries such as biopharmaceuticals and advanced therapies, uncertainty in demand, variability in manufacturing yields, and complex compliance standards introduce critical challenges to strategic supply chain planning. This paper presents a robust decision intelligence framework that delivers real-time end-to-end visibility, predictive forecasting, and dynamic capacity planning capabilities across the supply chain ecosystem. Through the integration of machine learning, stakeholder-centric dashboards, and prescriptive optimization models, the framework facilitates proactive responses to supply chain risks and disruptions. Use cases across healthcare and e-commerce logistics highlight the system’s flexibility and tangible impact on operational efficiency, resilience, and regulatory compliance. The proposed model serves as a comprehensive guide for supply chain practitioners and researchers seeking to modernize planning methodologies in high-variability, high-compliance environments.