Delphi method

Qualitative forecasting method that seeks to use the judgment of experts systematically to forecast what future events will be or when they may occur. It brings together a group of experts who have access to each other's opinions in an environment where no majority opinion is disclosed.

The Disaggregative Policy Delphi (DPD)

A critical phase of scenario formation is the choosing of the main features of alternative scenarios. Too often it is made unsystematically, using only the futurist’s subjective perception of the study material. The Disaggregative Policy Delphi (DPD) method makes this important decision a data sensitive action.

The traditional Delphi method is used to gather expert opinions and to ask for well argued statements of the most probable future. When asked in several rounds a consensus is hoped to be achieved as the respondents would learn from each other. Then the median and the interquartiles of the answers are reported and convergence of the answers is considered a success. The Policy Delphi also asks for statements concerning the most preferred future.

Contrary to consensus seeking in traditional Delphi, the Disaggregative Policy Delphi (DPD) classifies quantitative expert or interest group responses into similar groups. This is made by using cluster analysis which forms the core of different scenarios directly from the responses. Qualitative arguments gathered by argumentative interviews are then attached to the clusters. After critical examination of the content of the arguments, the remaining inconsistencies are solved. The DPD procedure produces relevant scenarios directly from data produced by experts or interest groups. It ties up lessons learnt in technological foresight, visionary leadership and participatory planning.

Here are some slides (pdf) for further information of the Disaggregative Policy Delphi procedure. For full details and a review on the literature of Delphi pitfalls, please read the article:

  • Tapio, Petri, 2002, Disaggregative Policy Delphi: Using cluster analysis as a tool for systematic scenario formation, Technological Forecasting and Social Change 70 (1): 83-101.

A thorough analysis of an empirical application concerning the future of transport CO2 policy can be found in chapter 5 in the reference:

  • Tapio, Petri, 2002, The Limits to Traffic Volume Growth, Acta Futura Fennica No 8, Finland Futures Research Centre & Finnish Society for Futures Studies, Summary of doctorate dissertation (148 p.) published in www.ethesis.fi. The hard copy of the whole thesis (234 p.) can be purchased from the toimisto@futurasociety.fi by 25 euro.

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