The Value of Assessing Uncertainty

Abstract

Summary Despite the perception of lucrative earnings in the petroleum industry, various authors have noted that industry performance is routinely less than expectations. For example, Brashear et al. (2001) noted that the average return was approximately 7% in the 1990s, despite the use of typical project-hurdle rates of at least 15%. The underperformance is generally attributed to poor project evaluation and selection because of chronic bias. Although other authors have investigated cognitive biases in oil-and-gas (O&G) project evaluation, there have been few quantitative studies of the impact of biases on economic performance. We suggest that incomplete investigation and the possible underestimation of the impact of biases in project evaluation and selection are at least partially responsible for the persistence of these biases. The objectives of our work were to determine quantitatively the value of assessing uncertainty or, alternatively, the cost of underestimating uncertainty. In this paper, we present a new framework for assessing the monetary impact of overconfidence bias and directional bias (i.e., optimism or pessimism) on portfolio performance. For moderate amounts of overconfidence and optimism, expected disappointment (ED) was 30 to 35% of estimated net present value (NPV) for the industry portfolios and optimization cases that we analyzed. Greater degrees of overconfidence and optimism resulted in EDs approaching 100% of estimated NPV. A comparison of modeling results with industry performance in the 1990s indicates that these greater degrees of overconfidence and optimism have been experienced in the industry. The value of reliably quantifying uncertainty is reducing or eliminating both ED (realizing an NPV is substantially less than estimated NPV) and expected decision error (EDE) (selecting the wrong projects). Because biases are usually related, mitigating one bias will often mitigate others in the process. ED and EDE can be reduced by focusing on the elimination of either overconfidence or optimism, although there is an advantage to focusing on overconfidence. The elimination of ED will improve overall industry performance to the extent that superior projects are available and that better quantification of uncertainty allows the identification of these superior projects.

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