Human decision-making under uncertainty in the upstream oil and gas industry.

Abstract

Business under-performance in the upstream oil and gas industry, and the failure of many decisions to return anticipated results, has led to a growing interest over the past few years in understanding the impacts of current decision-making tools and processes and their relationship with decision outcomes. Improving oil and gas decision-making is thus, increasingly, seen as reliant on an understanding of what types of decisions are involved and how they actually are made in the “real world”. There has been significant work carried out within the discipline of cognitive psychology, observing how people actually make decisions. However, little is known as to whether these general observations apply to decision-making in the upstream oil and gas industry. Nor has there been work on how the results might be used to improve decision-making in the industry. This research is a step towards filling this gap by developing two themes – decision-making process and decision type. It distils a “real world” oil and gas decision-making model together with a theoretical decision-making model. Comparing and contrasting the two models yields several prescriptions for improved decision-making in the upstream oil and gas industry. This research also documents the development of an oil and gas decision making taxonomy that lays a decision space within which to judge the processes of decision-making. The taxonomy builds on established ideas in the human decision-making literature, but is itself novel, and involves four different dimensions: 1) complexity; 2) task constraint; 3) value functions; and 4) structure of the information environment. A primary observation is that decision-making processes are tailored to the various types of decisions. It is argued that maximising the chances of a good outcome in “real world” decisions requires the implementation of such tailoring.