Borrowing from Keynes' A Treatise on Probability: A non‐probabilistic measure of uncertainty for scenario planning

• Published date: 01 December 2023
• Author: James Derbyshire,Alberto Feduzi,Jochen Runde
• Date: 01 December 2023
• DOI: http://doi.org/10.1111/emre.12549

SPECIAL ISSUE ARTICLE

Borrowing from Keynes’A Treatise on Probability: A non-

probabilistic measure of uncertainty for scenario planning

James Derbyshire

1

| Alberto Feduzi

2

| Jochen Runde

2

1

Middlesex University, London, UK

2

Judge Business School, Cambridge University,

Cambridge, UK

Correspondence

James Derbyshire, Middlesex University,

Hendon, London, NW4 4BT, UK.

Email: jrderby@hotmail.com

Funding information

SAMS/BAM Research and Capacity Building

Grant Scheme; Society for the Advancement of

Management Studies (SAMS); British Academy

of Management (BAM)

Abstract

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 con-

ception of uncertainty to use, exactly what it attaches to and how it might be mea-

sured. 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 econo-

mist John Maynard Keynes’1921 A Treatise on Probability.

KEYWORDS

Keynes, openness, organisational myopia, scenario planning, uncertainty

INTRODUCTION: A PRACTICAL TOOL

IN SEARCH OF THEORETICAL

FOUNDATIONS

Scenario planning is a tool for exploring contingent but

potentially impactful futures to guide strategic decision-

making. Originating as an aid to military planning shortly

after WWII, it was subsequently applied in the public

policy domain by Herman Kahn and his colleagues at

RAND Corporation (Bradfield et al., 2005). Its popularity

in the business domain goes all the way back to its use by

Royal Dutch Shell to anticipate the oil crises of the 1970s,

captured in two case studies still widely cited as evidence

of its efficacy (Wack, 1985a,1985b). But it continues to be

widely used in business (Augier et al., 2018), including

by well-known organisations such as British Airways

(Moyer, 1996). Scenario planning is also used in other

domains, not least—with rising concern about potential

threats resistant to traditional forecasting methods such as

climate change and the COVID-19 pandemic (Scoblic &

Tetlock, 2020)—in public policy.

There is now an established academic literature on

scenario planning in which at least 23 distinct approaches

have been identified (Bishop, Hines, & Collins, 2007;

Phadnis et al., 2014). This proliferation can be seen in

positive terms as a reflection of the versatility and rate of

development of scenario planning. But it is also a sign of

an absence of common theoretical foundations (Phadnis

et al., 2014; Bowman, 2015). Although perhaps an under-

standable consequence of its practice-based origins and

associated prioritisation of applicability over theoretical

development (Bradfield, 2008), this absence is more than

a‘mere academic inconvenience’(Phadnis et al., 2014,

p. 122). For practitioners, the absence of sound theoreti-

cal foundations makes it difficult to assess the relative

merits of competing approaches and to assess which

approach is best suited to any particular situation. For

those seeking its academic development, there is the

catch-22 of weak theoretical foundations being seen as

confirming the lack of academic credibility of the subject,

at the same time as hindering its prospects of being for-

mulated in ways more suited to rigorous academic discus-

sion and dissemination (Derbyshire, 2017).

The lack of common theoretical foundations also

reflects important divisions in the subject, notably between

opponents and proponents of the use of probability

[Correction added on 28 April 2023, after first online publication: Article category was corrected in this version]

DOI: 10.1111/emre.12549

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any

medium, provided the original work is properly cited and is not used for commercial purposes.

© 2022 The Authors. European Management Review published by John Wiley & Sons Ltd on behalf of European Academy of Management (EURAM).

638 European Management Review. 2023;20:638–650.

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