Business analytics adoption framework for oil and gas surface facilities management
Year: 2026
Type: article
Abstract: The oil and gas industry faces significant challenges managing aging surface facilities, with over 80% exceeding 20 years of operation, necessitating effective Business Analytics (BA) adoption for optimization and decision-making. Existing BA frameworks remain generic and lack industry-specific considerations, particularly regarding safety-critical environments and real-time operational requirements. Unlike generic business domains, surface facilities require simultaneous monitoring of parameters such as H2S concentration and pressure differentials, where analytical delays can result in catastrophic incidents — complexities demanding specialized frameworks integrating process engineering data with business intelligence under stringent hydrocarbon safety protocols. This study develops a comprehensive BA adoption framework tailored for oil and gas surface facilities through strategic integration of people, process, and technology dimensions. A qualitative approach using semi-structured interviews was employed with 16 participants across four stakeholder groups: Senior Management, Project Implementation teams, Subject Matter Experts, and End Users. Thematic analysis revealed 12 primary themes clustered into three major dimensions, synthesized into a structured framework. Results demonstrate that successful BA adoption requires transformations spanning descriptive, predictive, and prescriptive analytics capabilities. The proposed framework addresses aging infrastructure challenges while delivering substantial value creation and enhanced operational resilience. This research provides one of the first empirically grounded BA adoption frameworks specifically designed for safety-critical oil and gas surface facilities management.
Source: Cogent Business & Management
Authors: Agung Prasetya, Meditya Wasesa, Yos Sunitiyoso
Institution: Bandung Institute of Technology
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,165
OpenAlex ID: W7155208095