Abstract

Effective supplier evaluation and performance monitoring are critical for ensuring operational excellence and competitive advantage in industrial supply chains. With increasing complexity, globalization, and risk exposure, traditional supplier assessment methods often fall short in providing timely, comprehensive, and actionable insights. This proposes a novel conceptual framework designed to enhance supplier evaluation and ongoing performance monitoring by integrating multiple dimensions of supplier capabilities, risk factors, and real-time performance metrics. The framework combines both qualitative and quantitative evaluation criteria, including quality, cost, delivery reliability, flexibility, and sustainability indicators. It incorporates continuous monitoring mechanisms supported by advanced technological tools such as Internet of Things (IoT) sensors, enterprise resource planning (ERP) systems, and data analytics platforms to facilitate real-time tracking and early detection of performance deviations. A dynamic feedback loop enables corrective actions and supplier development initiatives to be implemented swiftly, fostering stronger supplier relationships and collaboration.
Key components of the framework include a multi-criteria decision-making approach for initial supplier assessment, risk-based prioritization of suppliers, and performance scorecards tailored to industrial contexts. The framework is designed to be adaptable across different industrial sectors and scalable for varying supply chain complexities. Organizational factors such as data management, change readiness, and stakeholder engagement are also considered to ensure effective adoption.
By integrating supplier evaluation and performance monitoring into a unified system, this framework aims to improve supply chain resilience, reduce operational disruptions, and drive cost efficiencies. The conceptual model offers a foundation for further empirical validation and practical implementation, as well as opportunities to incorporate emerging trends such as sustainability metrics and artificial intelligence-driven predictive analytics. Ultimately, this framework addresses the critical need for enhanced visibility and control over supplier performance in industrial supply chains, supporting firms in achieving sustainable competitive advantages in increasingly volatile and complex markets.