Digital Performance Analytics Architecture for Executive Decision-Making in Nigerian Oil and Gas Megaprojects

Abstract Oil and gas project execution is highly complex, capital-intensive, and risk-sensitive, where timely and quality decision-making is critical. While global megaprojects frequently struggle with performance, flagship upstream capital projects in Nigeria (typically exceeding $1 billion) face an amplified set of challenges, historically experiencing average cost overruns of approximately 38% and schedule delays of approximately 37% across the sector. Consequently, the need for real-time performance visibility has become imperative. In this context, performance analytics architecture plays a vital role in transforming large volumes of construction and project data into actionable insights that support executive decision-making. This paper examines how digital performance management tools, when thoughtfully designed and strategically implemented, can support quality executive decision-making across oil and gas projects and mitigate the risks of project completion delays and budget overruns. The paper explores architectural elements such as seamless data integration across enterprise systems, robust data governance and quality controls, alignment of key performance indicators with project objectives, and executive-focused visualization frameworks. Particular attention is given to real-time monitoring of project schedule performance, cost variance analysis, and integrated project risk metrics. Through practical implementation insights and industry-informed practices derived from Nigerian project environments, the study demonstrates how well-designed performance management tools enable executives to anticipate risks, manage competing project trade-offs, and make informed strategic decisions. The study also identifies full end-to-end automation of the data pipeline as a significant near-term opportunity for further value realisation.