Oyster Oil

This case follows Angela, Head of Exploration at Oyster Oil, as she decides whether to drill in the high-risk Bueno Field. Despite a large potential payoff, the probability of finding oil is only about 5%, making drilling unattractive without additional information. The case highlights a common mistake: confusing the reliability of a test with the actual likelihood of success. Using intuitive methods, it shows how imperfect data slightly improves decisions but has limited value unless it changes the final choice, emphasizing the importance of base rates and rational updating.
Collection: IESE (España)
Ref: AD-402-E
Format: PDF
Number of pages: 3
Publication Date: May 29, 2026
Language: English

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Description

This case follows Angela, Head of Exploration at Oyster Oil, as she decides whether to drill in the high-risk Bueno Field. Despite a large potential payoff, the probability of finding oil is only about 5%, making drilling unattractive without additional information. The case highlights a common mistake: confusing the reliability of a test with the actual likelihood of success. Using intuitive methods, it shows how imperfect data slightly improves decisions but has limited value unless it changes the final choice, emphasizing the importance of base rates and rational updating.
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Geographic Setting: Mexico
Industry Setting: Industry and mining

Learning Objective

The case aims to help participants clearly distinguish between the reliability of a signal and the true (posterior) probability of an event, correcting a common misinterpretation of “accurate” tests. It introduces an intuitive approach to Bayesian updating using natural frequencies rather than formulas, making conditional probability more accessible. Finally, it emphasizes a key managerial insight: information only has value if it changes decisions, reinforcing disciplined thinking about uncertainty, base rates, and the economic value of data.

Oyster Oil

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"Oyster Oil"