TY - JOUR
T1 - Scenario generation and scenario quality using the cone of plausibility
AU - Dhami, M.K.
AU - Wicke, Lars
AU - Onkal, Dilek
N1 - Funding information: Dhami received funding from HM Government, UK.
PY - 2022/9/1
Y1 - 2022/9/1
N2 - 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.
AB - 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.
KW - Scenario generation
KW - cone of plausibility
KW - best and worst case
KW - wildcard
KW - intelligence analysis
KW - forecasting
KW - futures and foresight
U2 - 10.1016/j.futures.2022.102995
DO - 10.1016/j.futures.2022.102995
M3 - Article
VL - 142
JO - Futures
JF - Futures
SN - 0016-3287
M1 - 102995
ER -