Data Analytics for Effective Project Management in the Oil and Gas Industry
- DOI
- 10.2991/978-94-6463-080-0_20How to use a DOI?
- Keywords
- Data Analytics; Project Management; Oil and Gas; Big Data; Case Study
- Abstract
This study aims to highlight the effectiveness of data analytics in project management within the oil and gas sector. Data analytics have increasingly improved efficiency and effectiveness in most sectors by boosting decision-making accuracy through an intensive data-driven forecasting model. Despite the importance of data analytics in most industries, limited studies have evaluated its role within the oil and gas industry. The research applied the case study research method. Executives from a multinational oil and gas company with significant working experience were approached for the interview sessions. The thematic content analysis method was applied to sort the qualitative data and elucidate findings on the role of data analytics within the company. The insights gained from the case study of this major international oil and gas company led to recommendations for the sector in general. Finally, the study established that better returns were achieved when data-driven decisions were made compared to situations where big data were ignored.
- Copyright
- © 2022 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Victor Tan AU - Kamarulzaman Ab. Aziz AU - Seyed Hadi Razavi PY - 2022 DA - 2022/12/26 TI - Data Analytics for Effective Project Management in the Oil and Gas Industry BT - Proceedings of the International Conference on Technology and Innovation Management (ICTIM 2022) PB - Atlantis Press SP - 233 EP - 242 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-080-0_20 DO - 10.2991/978-94-6463-080-0_20 ID - Tan2022 ER -