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Scenario planning is a tool used to formulate contingent but potentially impactful futures to aid strategic decision‐making. A crucial element of many versions of scenario planning is an assessment of levels of uncertainty about the broad drivers of change within the system under consideration. Despite the importance of this element, the scenario planning literature is largely silent on the appropriate conception of uncertainty to use, exactly what it attaches to and how it might be measured. This paper seeks to fill this gap by advancing a non‐probabilistic measure of uncertainty based on the concept of evidential weight drawn from the economist John Maynard Keynes' 1921 A Treatise on Probability .
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Derbyshire et al. (2022) studied this question.
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