Adapting scenario planning to create an expectation for surprises : going beyond probability and plausibility in risk assessment

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Derbyshire, James and Dhami, Mandeep and Belton, Ian and Onkal, Dilek and Aven, Terje (2025) Adapting scenario planning to create an expectation for surprises : going beyond probability and plausibility in risk assessment. Risk Analysis, 45 (11). pp. 3737-3757. ISSN 1539-6924 (https://doi.org/10.1111/risa.70112)

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Abstract

The need for risk assessments to take full account of uncertainty by going beyond probability and creating an expectation for surprises has recently been highlighted in this journal. This paper sets out an adaptation to the Intuitive Logics (IL) scenario-planning method that assists risk assessors to achieve this aim. We demonstrate the effectiveness of this adaptation through a controlled experiment. The controlled experiment took the form of a simulated IL scenario-planning exercise in which individuals assigned values representative of extreme outcomes to sets of simple and more complex clusters of driving forces under three experimental conditions representing alternative uncertainty expressions (‘probable’, ‘plausible’, and ‘surprising’). The values assigned in the ‘probable’ and ‘plausible’ conditions were not significantly different from each other. However, the ‘surprising’ condition resulted in the assignment of more extreme values than either of the other two conditions. The complexity of a set of clustered driving had no effect. A follow-up analysis showed that participants interpreted the words ‘probable’ and ‘plausible’ similarly. This is problematic for scenario methods like IL, which are claimed to stretch consideration of the future’s potential extremity beyond what it would be using probability by instead employing plausibility. Yet, if participants interpret ‘probable’ and ‘plausible’ similarly, then using plausibility instead of probability will not stretch their thinking as desired. By adapting IL in the simple way this paper outlines, scenario planning can assist risk assessors to go beyond both probability and plausibility, thereby taking fuller account of uncertainty and improving anticipation of surprises.

ORCID iDs

Derbyshire, James, Dhami, Mandeep, Belton, Ian ORCID logoORCID: https://orcid.org/0000-0002-2479-6563, Onkal, Dilek and Aven, Terje;
CORE (COnnecting REpositories)