A Conceptual Framework for Data-Driven Procurement Risk Management in Multinational Enterprises

Procurement risk in multinational enterprises (MNEs) presents a significant challenge due to complex global supply chains, regulatory diversity, and market volatility. Leveraging data-driven approaches for procurement risk management enhances visibility, predictive capability, and decision-making efficiency. This study proposes a conceptual framework integrating data analytics, risk assessment models, and strategic procurement processes to strengthen risk mitigation in MNEs. Through a comprehensive review of literature, case studies, and industry reports, key dimensions of procurement risk including supplier, operational, financial, and geopolitical factors are analyzed in conjunction with data-driven methodologies. The framework emphasizes real-time data integration, predictive analytics, and decision support systems, offering practical insights for procurement managers and organizational leaders. The findings contribute to the development of resilient, proactive, and adaptive procurement strategies in multinational contexts.