Designing and Applying Integrated Supply Chain–Contracting Frameworks for Reducing Non-Productive Time in Offshore Drilling Projects

The nature of offshore drilling projects is marked by the high complexity of operations and high financial risks, and Non-Productive Time (NPT) becomes a significant issue that compromises efficiency, safety, and cost-effectiveness. Current methods of mitigating NPT have primarily focused on technical solutions, such as automating drilling, predictive maintenance, and enhanced planning. Although useful, such strategies fail to provide a picture of the systemic role of fragmented supply chains and inappropriate contracting practices in increasing downtime. This conceptual review fills this gap by creating an integrated supply chain-contracting framework that helps reduce NPT in offshore drilling projects. This paper begins with an explanation of key concepts, including NPT, integrated supply chain management, and contracting structures, and discusses the concept of integration between these aspects. It employs various theoretical viewpoints, including Transaction Cost Economics, Resource-Based View, Systems Theory, and lean/agile supply chain principles, to support its argument for the necessity of integration. The review of the current literature reveals ongoing supply chain issues, existing methods of supply chain management, and shortcomings in current contracting models, which lack an overall framework that can interconnect governance with operations. In reply, the suggested framework implements collaboration, information sharing, digitalisation, performance-based contracting, and fair distribution of risks within a dynamic framework that minimizes downtime. The research also makes a theoretical contribution by filling gaps in supply chain and contracting scholarship, and provides practical value by offering a set of guidelines for operators, contractors, and suppliers to follow in a structured manner. Although conceptual, the framework provides a basis for future empirical validation through case studies, simulations, or field applications, and has implications for policy, practice, and sustainable operational excellence.