Memes in Foresight: Response to the Black Swan

Mack, Timothy C.

doi:10.1177/194675671000200203

Cited by 2 publications

(2 citation statements)

References 4 publications

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“…For now, it is enough to be aware of the breadth of approaches to data and analysis, when building an evidence base. These include, for example, critical interpretation (Ramírez et al 2015); historical events with ongoing influence 8 ; judgement and statistical inferences from past events (Nicosia 2011;Mack 2010;Suharto 2013); current baseline events and critical variables (O'Mahony 2014; Konno et al 2014a); weak signals of a potentially substantial future change (Gambelli et al 2010); consensus of expert opinion (Suharto 2013;Kaufmann 2016;Agustan et al 2019;Hernandez et al 2019;United Nations Industrial Development Organization 2005;Ritchey 2011); ruling out mutually exclusive/implausible combinations of factors (Nygrén 2019;Lord et al 2016) and integration of multiple scenarios (Barker 2014). The strength of scenario plausibility depends, in part, on the rigour of the evidence base.…”

Section: Plausibility and The 'Aha' Momentmentioning

confidence: 99%

Scenario Analysis and the Limits of Prediction

McGee

Edmiston

Haward

2021

The Future of Antarctica

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The limits of prediction pose a critical risk for any organisation making long-range decisions about its strategy and investments. The accuracy of our forecasts degrades progressively due to the combined effects of complexity and uncertainty, compounded by the passage of time. Scenarios become useful in the zone beyond the limits of standard prediction. However, we question whether it is really the case that scenarios must only start where prediction ends. Do most organisations that invest in scenario planning have no expectation that the scenarios created will provide a credible picture of what the future might be like? Instead, we view scenarios as anticipatory systems with a distinctive type of predictive model, where prediction is not based on probability, but plausibility. The zone of plausibility is a space in which scenarios provide evidence-based, broad-brush, but targeted, prediction. We contend that other objectives for scenarios, (such as futures consciousness, or re-perception) are necessary but secondary to scenarios' predictive work in the zone of plausibility. Importantly, we argue that if we abandon hope that our scenarios will provide a constrained form of prediction, then we fail to harness the potential that scenarios can offer-when they are plausible, rigorous, and robust. KeywordsLimits of prediction • Complexity, uncertainty and prediction • Scenarios and prediction • Properties of scenarios • Plausible scenarios • Turbulence, Uncertainty, Novelty and Ambiguity (TUNA conditions) OverviewAll who claim to foretell or forecast the future are inevitably liars, for the future is not written anywhere-it has still to be built (Godet and Roubelat, 1996, p. 164).

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Section: Plausibility and The 'Aha' Momentmentioning

confidence: 99%

Scenario Analysis and the Limits of Prediction

McGee

Edmiston

Haward

2021

The Future of Antarctica

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“…As Lindgren and Bandhold put it, quantitative approaches provide 'output data in numbers' (Lindgren and Bandhold 2009, p. 186). Quantitative approaches encompass a large suite of methods that use numerically represented data and mathematically expressed logics to: model scale, intensity, probability and sensitivity; identify structures and relationships; integrate data and variables; extrapolate trends; simulate impacts of interventions; exclude mutually incompatible combinations of factors; and process larger volumes of data, variables and relationships than can be handled by qualitative approaches alone (Wright et al 2013;Huss 1988;Amer et al 2013;Wodak and Neale 2015;Nygrén 2019;Lord et al 2016;Bradfield et al 2016;Mack 2010;Halim et al 2016).…”

Section: Quantitative Approachesmentioning

confidence: 99%

Objectives, Approaches and Techniques

McGee

Edmiston

Haward

2021

The Future of Antarctica

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From our review of scenario objectives, approaches, and techniques, we suggest that scenario methods can be grouped under one or more of seven broad approaches: deductive, inductive, quantitative, hybrid, integrated, scoping, and engagement. Each has its strengths and weaknesses. We conclude that no single scenario approach can match the scale and complexity of Antarctic geopolitics. For that reason, we recommend that a scenario process employ a judicious blend of several approaches. For this book, we focus on one technique, the standard intuitive logics '2 × 2' matrix, commonly deployed in geopolitical scenarios. We unpack it with a worked example and encounter some difficulties applying it to the field of Antarctic geopolitics. This leads us to propose some modifications, which may be useful for scenarios in other fields. Importantly, 'practical' decisions about scoping and framing of scenarios are shaped, in important ways, by the assumptions and values we hold. Which issues are in? Which are out? How are issues framed? Whose voices are heard, and whose are excluded? What types of data do we admit? How do we handle complexity? What expertise do we need? Decisions about scenario process are not the objective, technical considerations they are often perceived to be.In the preceding chapter, we described a space where standard, probabilistic predictions are doomed to fail due to the convergence of complexity, uncertainty, and time. Nonetheless, we proposed that, within that space, there is opportunity for scenarios to provide evidence-based, broad-brush, but targeted prediction. We

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Memes in Foresight: Response to the Black Swan

Cited by 2 publications

References 4 publications

Scenario Analysis and the Limits of Prediction

Scenario Analysis and the Limits of Prediction

Objectives, Approaches and Techniques

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