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Introducing a classification framework for prospective methods

Joseph Voros (Joseph Voros is a lecturer in the Strategic Foresight Program at the Australian Graduate School of Entrepreneurship, Faculty of Business and Enterprise, Swinburne University of Technology, Hawthorn, Australia.)

Foresight

ISSN: 1463-6689

Article publication date: 1 March 2006

1798

Abstract

Purpose

The purpose of this article is to examine the nature and type of methods used in futures studies and foresight work which are explicitly concerned with creating “forward views” and/or “images of the future” (“prospective” methods).

Design/methodology/approach

A new analytical technique, “mode‐level analysis”, is introduced and described, based on a classification of “modes” of futures thinking and levels of “depth” of interpretive frameworks. By choosing both a set of thinking modes and a series of interpretive levels as a basis, prospective methods may be analyzed in terms of which mode(s) and what level(s) they operate with or at.

Findings

Two modes of thinking and five levels of depth are chosen for this analysis. The resulting schema is used to classify such methods as: wildcards, forecasting, “trend breaks”, visioning, backcasting, and alternative histories and counterfactuals. An analysis is also carried out on the method of “scenarios”, revealing a variety of different approaches operating at multiple levels of depth. The historical development of prospective methods is also discussed.

Practical implications

Mode‐level analysis can be generalized to any number of modes or levels, depending on the application, context or objectives of the analyst. It may be used by academics for interest's sake and for teaching students, and by practitioners as both a design tool and a diagnostic one.

Originality/value

This paper introduces a new technique for classifying prospective methods, and may help lead to ideas for the creation of new methods.

Keywords

Citation

Voros, J. (2006), "Introducing a classification framework for prospective methods", Foresight, Vol. 8 No. 2, pp. 43-56. https://doi.org/10.1108/14636680610656174

Publisher

:

Emerald Group Publishing Limited

Copyright © 2006, Emerald Group Publishing Limited

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