Implementing Data-Driven Contract Optimization Strategies to Strengthen Local Content Development and Import Substitution in the Nigerian Energy Sector

Abstract

The Nigerian energy sector faces structural challenges due to its heavy dependence on imported goods and services, as well as insufficient local involvement, despite the enactment of local content policies. Conventional contracting structures, characterized by day-rate, cost-plus, and turnkey models, have historically been efficient in serving foreign operators, often with little regard for creating sustainable local capacity or reducing reliance on imports. This paper provides a conceptual overview of how data-driven contract optimization can address these gaps and enhance local content, as well as import substitution. Based on the Digital and analytics-enabled contracting, the Resource-Based View, Import substitution Industrialisation theory, and Institutional Theory, the review demonstrates how the reduction of inefficiencies, more transparency, and better alignment of performance with measurable development outcomes can be realised through digital and analytics-enabled contracting, including predictive analytics, blockchain, artificial intelligence, and supply chain platforms. The analysis shows that optimised contracts can promote the involvement of indigenous companies, transfer
knowledge, and boost domestic production, while also providing adequate exposure to international supply disruptions and foreign exchange volatility. The paper presents an idea that connects contract optimisation and enhanced local content and self-reliance in industry, which is relevant to government policy alignment, operator performance-based contracting adoption, and supplier improvement of capabilities. Data-driven optimisation offers an avenue for increased competitiveness, resilience, and sustainable growth by redefining contracts as strategic tools rather than transactional ones in the Nigerian energy sector.