Transforming organizations through analytics: key success determinants for business analytics implementation in oil and gas surface infrastructure

The petroleum industry increasingly seeks to enhance the performance of aging surface infrastructure amid declining output and escalating operational expenditures. However, Business Analytics (BA) implementations frequently underperform, with fewer than 30% achieving anticipated outcomes despite significant capital allocation. This research examines the determinants influencing BA adoption for surface infrastructure optimization within PT XYZ, employing a mixed-methods approach comprising stakeholder interviews (n = 15) and professional surveys (n = 130) analyzed via Partial Least Squares Structural Equation Modeling (PLS-SEM). Drawing upon Socio-Technical Systems Theory, this investigation explores the interrelationships between organizational dimensions and BA implementation outcomes. The findings reveal that governance frameworks serve as the predominant enabler, followed by workforce capabilities and organizational culture, perceived business impact, and technological integration. Structural modeling indicates that governance mechanisms, human and cultural factors, and business value recognition directly affect BA implementation success, while decision-making processes function as mediating variables between implementation and operational performance. Notably, technological and data infrastructure alongside procedural methodologies demonstrated no statistically significant relationships—a finding that contradicts technology-centric digital transformation paradigms. The results underscore that effective BA deployment necessitates concurrent enhancement of both social and technical organizational components, emphasizing executive commitment, cultural preparedness, and strategic coherence rather than technological advancement alone. This study offers practical guidance for energy sector organizations pursuing analytics-enabled operational improvements.