Abstract
Business under-performance in the upstream oil and gas industry, and the failure of many decisions to return expected 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. A primary observation is that different decision types require different decision-making approaches to achieve optimal outcomes.
Optimal decision-making relies on understanding the types of decisions being made and matching the type of decision with the appropriate tools and processes. Yet the industry lacks both a definition of decision types and any guidelines as to what tools and processes should be used for what decisions types. It is argued that maximizing the chances of a good outcome in real world decisions requires the implementation of such matching. Comparing a "real world" decision-making model used by the upstream oil and gas industry with a theoretical model yields various prescriptions for optimal decision-making.
Further implications are examined in relation to a variety of oil and gas decisions by documenting both a definition of decision types as well as guidelines to what decision-making processes should be used with what decision types. The paper looks at a comparison between what tools and processes companies are now using for some of the decision types and compare these with what they should be using in order to lead to optimal decision-making.
