Scenario generation and scenario quality using the cone of plausibility

Dhami, Mandeep K., Wicke, Lars and Önkal, Dilek (2022) Scenario generation and scenario quality using the cone of plausibility. Futures, 142. p. 102995. ISSN 0016-3287

1-s2.0-S0016328722000957-main.pdf - Published Version
Available under License Creative Commons Attribution 4.0.

Download (938kB) | Preview
[img] Text
Dhami_Wicke_Onkal_ACCEPTED_MANUSCRIPT.pdf - Accepted Version
Restricted to Repository staff only until 15 July 2024.
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0.

Download (467kB) | Request a copy
Official URL:


The intelligence analysis domain is a critical area for futures work. Indeed, intelligence analysts’ judgments of security threats are based on considerations of how futures may unfold, and as such play a vital role in informing policy- and decision-making. In this domain, futures are typically considered using qualitative scenario generation techniques such as the cone of plausibility (CoP). We empirically examined the quality of scenarios generated using this technique on five criteria: completeness, context (otherwise known as ‘relevance/pertinence’), plausibility, coherence, and order effects (i.e., ‘transparency’). Participants were trained to use the CoP and then asked to generate scenarios that might follow within six months of the Turkish government banning Syrian refugees from entering the country. On average, participants generated three scenarios, and these could be characterized as baseline, best case, and worst case. All scenarios were significantly more likely to be of high quality on the ‘coherence’ criterion compared to the other criteria. Scenario quality was independent of scenario type. However, scenarios generated first were significantly more likely to be of high quality on the context and order effects criteria compared to those generated afterwards. We discuss the implications of these findings for the use of the CoP as well as other qualitative scenario generation techniques in futures studies.

Item Type: Article
Additional Information: Funding information: Dhami received funding from HM Government, UK.
Uncontrolled Keywords: Scenario generation, cone of plausibility, best and worst case, wildcard, intelligence analysis, forecasting, futures and foresight
Subjects: N100 Business studies
N200 Management studies
N900 Others in Business and Administrative studies
Department: Faculties > Business and Law > Newcastle Business School
Depositing User: Rachel Branson
Date Deposited: 18 Jul 2022 13:00
Last Modified: 25 Jul 2022 15:13

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics