The traditional Enterprise Resource Planning (ERP) systems have been used as back office transactional systems and reporting infrastructures to supply chain planning.Nevertheless, environmental volatility, the pressure of digital transformation, and the spread of artificial intelligence (AI) technologies have increased the pace of the move to descriptive reporting to predictive and prescriptive decision support.Present-day studies show that analytics-empowered supply chain functions provide a great contribution to responsiveness, resilience, and operational performance in case of effective information systems and data governance systems.Simultaneously, a new set of paradigms including digital twins, real-time integration of IoT, and explainable AI are redefining the architectural and managerial underpinnings of the intelligent enterprise systems.This review focuses on how ERP systems have evolved into forecasting and decision-support engines in the supply chain planning function of the ERP systems.Critical architectural enablers, governance frameworks, analytical models, and empirically obtained performance results were examined.The review found that there were still research gaps associated with integration complexit y, model transparency, cross-enterprise data interoperability, and sustainability-oriented planning optimization.The future of research is focused on the autonomous planning systems, AI-human collaboration frameworks, resilience-by-design architecture, and sustainability-based ERP ecosystems.The results locate predictive ERP systems as strategic supporting platforms of intelligent, adaptive, and accountable supply chain management.
Pushpanjali Chauhan (Thu,) studied this question.