BIG DATA ANALYTICS CAPABILITY AND STRATEGIC COST MANAGEMENT: EVIDENCE FROM UPSTREAM OIL AND GAS EXPLORATION AND PRODUCTION COMPANIES

Abstract

The central objectives of this study is to explore the importance of big data analytics capability (BDAC) to strategic cost management (SCM) in the upstream oil and gas exploration and production firms. The oil and gas sector are highly complex in terms of the operations and highly in terms of capital requirement and the exposure to price volatility and therefore, effective cost management is important to allow the company to maintain its competitiveness over the long-term. Although the previous studies have focused on the operational efficiency, few empirical studies have been conducted on the ability of analytics translating into strategic cost advantages. The main purpose of this paper is to investigate how the capabilities of the big data analytics impact the strategic cost management and cost efficiency and test the moderating impact of the organizational readiness and technological infrastructure. The type of research design used was quantitative where primary data were gathered on 150 managerial, technical, and analytics staff of upstream oil and gas companies. The descriptive statistics and correlation analysis, as well as multiple regression were used to analyze data, and tests containing t-values, p-values, F-values, R2, adjusted R2, and Durbin-Watson statistics were used to evaluate the strength, significance, and direction of the relationships. The strategic cost management was measured in the aspects of cost planning, cost control, and cost optimization, whereas BDAC was operationalized in terms of analytical tool, technical skill and data quality as well as managerial support. The findings indicate that the big data analytics capability produces a positive impact on strategic cost management of high magnitude (b = 0.571, t = 8.27, p < 0.001), which accounts to about 45 percent of the difference in the SCM practices. BDAC also yields a significant improvement in cost efficiency (b = 0.613, t = 8.40, p < 0.001), which explains 47.5% variation in the cost effectiveness results. Companies that have superior analytics capacity see better gains in cost planning, monitoring, and resource allocation and those companies that have high organizational preparedness and technology are getting increased returns. The research also determines that the cost control practices are more developed than those of cost optimization, which is a possible strategic area of improvement. The results highlight the need to perceive big data analytics as a strategic organizational asset and not an exclusively functional instrument. Companies that are able to incorporate analytics in their decision making process with qualified staff and with strong IT infrastructure can realize sustainable cost of advantage and competitiveness in upstream oil and gas operations.