Value creation through big data application process management: the case of the oil and gas industry. Issue 8 (29th August 2019) - Sumbal, Muhammad Saleem; Tsui, Eric; Irfan, Irfan; Shujahat, Muhammad; Mosconi, Elaine; Ali, Murad
Abstract : Purpose: The purpose of this study is twofold: to investigate the role of big data in firms' co-knowledge and value creation and to understand the underlying drivers behind value creation through big data in the oil and gas industry by underscoring the role of firms' capabilities, trends and challenges. Design/methodology/approach: Following an inductive approach, semi-structured interviews were conducted with senior managers and analysts working in oil and gas companies across eight countries. The data collected from these key informants were then analysed using the qualitative data analysis software ATLAS.ti. Findings: Value creation through big data is an important factor for enhancing performance. It has a positive impact on both tangible (organisational performance) and intangible (societal) aspects depending on the context. Oil and gas companies understand the importance of big data to creating value in their operations. However, implementing and using big data has been problematic. In this study, a framework was developed to show that factors such as the shortage of data experts, poor data quality, the risk of cyber-attacks and unsupportive organisational cultures impede its implementation and utilisation. Research limitations/implications: The findings from this study have implications for managers and executives implementing big data and creating value across various data-intensive industries. The research findings, are contextual, however, and should be applied cautiously. Originality/value: This study contributes to the value creation literature in the big data context. The findings identify the key areas to be considered for the effective implementation and utilisation of big data in the oil and gas sector. This study addresses a broad but under-explored issue (i.e. knowledge creation from big data and its implementation) and strengthens the academic debate within this research stream.