Editing Delphi method (section)

==Accuracy==

Today the Delphi method is a widely accepted forecasting tool and has been used successfully for thousands of studies in areas varying from technology forecasting to [[drug abuse]].<ref>{{cite book | vauthors = Jillson IA | chapter = II.B.3. The National Drug-Abuse Policy Delphi: Progress Report and Findings to Date | veditors = Turoff M, Linstone HA | title = The Delphi Method: Techniques and Applications | date = 2002 | chapter-url = http://is.njit.edu/pubs/delphibook/ch3b3.html | archive-url = https://web.archive.org/web/20120206170836/http://is.njit.edu/pubs/delphibook/ch3b3.html | archive-date = 6 February 2012 }}</ref>
Overall the track record of the Delphi method is mixed.<ref name=":1">Khodyakov, D., Grant, S.,  Kroger, J.,  Bauman, M. (2023). ''RAND methodological guidance for conducting and critically appraising Delphi panels.'' RAND Corporation. www.rand.org/t/TLA3082-1 https://doi.org/10.7249/tla3082-1</ref> There have been many cases when the method produced poor results. Still, some authors attribute this to poor application of the method and not to the weaknesses of the method itself. The ''RAND Methodological Guidance for Conducting and Critically Appraising Delphi Panels'' is a manual for doing Delphi research which provides guidance for doing research and offers a appraisal tool.<ref name=":1" /> This manual gives guidance on best practices that will help to avoid, or mitigate, potential drawbacks of Delphi Method Research; it also helps to understand the confidence that can be given to study results. 

It must also be realized that in areas such as science and technology forecasting, the degree of uncertainty is so great that exact and always correct predictions are impossible, so a high degree of error is to be expected. An important challenge for the method is ensuring sufficiently knowledgeable panelists. If panelists are misinformed about a topic, the use of Delphi may only add confidence to their ignorance.<ref name = "Green_2008">{{cite journal | vauthors = Green KC, Armstrong JS, Graefe A | title = Methods to elicit forecasts from groups: Delphi and prediction markets compared. | journal = Foresight: The International Journal of Applied Forecasting | date = June 2008 | volume = 8 | pages = 17–20 | doi = 10.2139/ssrn.1153124 | url = https://repository.upenn.edu/cgi/viewcontent.cgi?article=1168&context=marketing_papers }}</ref>

One of the initial problems of the method was its inability to make complex forecasts with multiple factors. Potential future outcomes were usually considered as if they had no effect on each other. Later on, several extensions to the Delphi method were developed to address this problem, such as [[cross impact analysis]], that takes into consideration the possibility that the occurrence of one event may change probabilities of other events covered in the survey. Still the Delphi method can be used most successfully in forecasting single scalar indicators.

===Delphi vs. prediction markets===
Delphi has characteristics similar to [[prediction markets]] as both are structured approaches that aggregate diverse opinions from groups. Yet, there are differences that may be decisive for their relative applicability for different problems.<ref name = "Green_2008" />

Some advantages of [[prediction markets]] derive from the possibility to provide incentives for participation.
# They can motivate people to participate over a long period of time and to reveal their true beliefs.
# They aggregate information automatically and instantly incorporate new information in the forecast.
# Participants do not have to be selected and recruited manually by a facilitator. They themselves decide whether to participate if they think their private information is not yet incorporated in the forecast.

Delphi seems to have these advantages over prediction markets:
# Participants reveal their reasoning
# It is easier to maintain confidentiality
# Potentially quicker forecasts if experts are readily available.
# Delphi is applicable in situations where the bets involved might affect the value of the currency used in bets (e.g. a bet on the collapse of the dollar made in dollars might have distorted odds).

More recent research has also focused on combining both, the Delphi technique and prediction markets. More specifically, in a research study at [[Deutsche Börse]] elements of the Delphi method had been integrated into a prediction market.<ref>{{cite journal | vauthors = Prokesch T, von der Gracht H, Wohlenberg H |year = 2015 | title = Integrating prediction market and Delphi methodology into a foresight support system — Insights from an online game | journal = Technological Forecasting and Social Change | volume = 97 | pages = 47–64 | doi = 10.1016/j.techfore.2014.02.021}}</ref>