Editing Delphi method (section)

===Use in forecasting===
First applications of the Delphi method were in the field of science and technology forecasting. The objective of the method was to combine expert opinions on likelihood and expected development time, of the particular technology, in a single indicator. One of the first such reports, prepared in 1964 by Gordon and Helmer, assessed the direction of long-term trends in science and technology development, covering such topics as scientific breakthroughs, [[population control]], [[automation]], space progress, war prevention and weapon systems. Other forecasts of technology were dealing with vehicle-highway systems, industrial robots, intelligent internet, broadband connections, and technology in education.

Later the Delphi method was applied in other places, especially those related to public policy issues, such as [[Economic indicator|economic trend]]s, health and education. It was also applied successfully and with high accuracy in business forecasting. For example, in one case reported by Basu and Schroeder (1977),<ref>{{cite journal| vauthors = Basu S, Schroeder RG |title=Incorporating Judgments in Sales Forecasts: Application of the Delphi Method at American Hoist & Derrick|journal=Interfaces|date=May 1977|volume=7|issue=3|pages=18–27|doi=10.1287/inte.7.3.18}}</ref> the Delphi method predicted the sales of a new product during the first two years with inaccuracy of 3–4% compared with actual sales. Quantitative methods produced errors of 10–15%, and traditional unstructured forecast methods had errors of about 20%. (This is only one example; the overall accuracy of the technique is mixed.)

The Delphi method has also been used as a tool to implement multi-stakeholder approaches for participative policy-making in developing countries. The governments of Latin America and the Caribbean have successfully used the Delphi method as an open-ended public-private sector approach to identify the most urgent challenges for their regional ICT-for-development [[eLAC Action Plans]].<ref name="HilbertMilesOthmer2009">{{cite journal | vauthors = Hilbert M, Miles I, Othmer J | year = 2009 | title = Foresight tools for participative policy-making in inter-governmental processes in developing countries: Lessons learned from the eLAC Policy Priorities Delphi | url = http://martinhilbert.net/Hilbert_etal.eLACdelphi.pdf | journal = [[Technological Forecasting and Social Change]] | volume = 15 | issue = 2| pages = 880–896 | doi = 10.1016/j.techfore.2009.01.001 | s2cid = 154784808 }}</ref> As a result, governments have widely acknowledged the value of collective intelligence from civil society, academic and private sector participants of the Delphi, especially in a field of rapid change, such as technology policies.