Abstract

The increasing complexity of globalized and distributed supply chain operations necessitates a redefinition of talent management strategies to ensure capability development and sustainable performance. This study presents a conceptual supply chain talent development model designed to strengthen organizational capability across geographically dispersed networks through data-driven insights and adaptive learning mechanisms. The model emphasizes alignment between strategic objectives, competency frameworks, and technological enablement to enhance workforce agility and operational excellence. By integrating workforce analytics, digital collaboration platforms, and continuous capability mapping, the model addresses critical gaps in skill alignment, leadership readiness, and process standardization within distributed supply chains.The proposed model operates through four interconnected layers: strategic capability identification, digital talent mapping, continuous learning integration, and performance optimization. It leverages advanced analytics to forecast future skill needs, monitor competency gaps, and personalize development pathways that align with operational objectives. The model also incorporates cross-functional learning ecosystems, enabling knowledge transfer and collaborative innovation across regions and business units. Furthermore, it embeds digital transformation enablerssuch as artificial intelligence, cloud learning management systems, and real-time performance dashboardsto ensure that workforce development remains adaptive to changing market dynamics and technological disruptions.The conceptual framework contributes to theory and practice by offering a holistic approach to talent capability management in supply chains, where talent flow and knowledge diffusion are as critical as material flow. It proposes a systemic alignment between human capital strategy and operational performance, reinforcing resilience and scalability. The model also provides a foundation for empirical validation through longitudinal studies assessing the correlation between talent maturity indices and key performance indicators (KPIs) such as lead time efficiency, innovation rate, and supply chain resilience.This research concludes that organizations adopting integrated, analytics-driven talent development frameworks are better positioned to enhance workforce productivity, mitigate skill shortages, and sustain competitive advantage across distributed operations. The model serves as a roadmap for organizations seeking to institutionalize strategic talent development within dynamic and technology-intensive supply chain ecosystems.