Natarajan, Ananth
Reference class forecasting and machine learning for improved offshore oil and gas megaproject planning: Methods and application - Project Management Journal - 53(5), Oct, 2022: p.456-484
This article develops and describes rigorous oil and gas project forecasting methods. First, it builds a theoretical foundation by mapping megaproject performance literature to these projects. Second, it draws on heuristics and biases literature, using a questionnaire to demonstrate forecasting-related biases and principal-agent issues among industry project professionals. Third, it uses methodically collected project performance data to demonstrate that overrun distributions are non-normal and fat-tailed. Fourth, reference-class forecasting is demonstrated for cost and schedule uplifts. Finally, a predictive approach using machine learning (ML) considers project-specific factors to forecast the most likely cost and schedule overruns in a project.- Reproduced
Megaproject performance, Reference class forecasting, Oil and gas projects, Machine learning, Schedule and cost overruns, Megaproject performance forecasting, Planning, heuristics, biases.
Reference class forecasting and machine learning for improved offshore oil and gas megaproject planning: Methods and application - Project Management Journal - 53(5), Oct, 2022: p.456-484
This article develops and describes rigorous oil and gas project forecasting methods. First, it builds a theoretical foundation by mapping megaproject performance literature to these projects. Second, it draws on heuristics and biases literature, using a questionnaire to demonstrate forecasting-related biases and principal-agent issues among industry project professionals. Third, it uses methodically collected project performance data to demonstrate that overrun distributions are non-normal and fat-tailed. Fourth, reference-class forecasting is demonstrated for cost and schedule uplifts. Finally, a predictive approach using machine learning (ML) considers project-specific factors to forecast the most likely cost and schedule overruns in a project.- Reproduced
Megaproject performance, Reference class forecasting, Oil and gas projects, Machine learning, Schedule and cost overruns, Megaproject performance forecasting, Planning, heuristics, biases.