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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 | doi-access = free }}</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.
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