3.3 Delphi – Foresight

3.3 Delphi – Foresight
3.3 Delphi - Foresight logo

The Delphi method was developed by Project RAND during the 1950-1960s. It has been used ever since, together with various modifications and reformulations. Today, the online Delphi method has gained popularity as it makes the data collection and analyses faster and easier.

The Delphi method is typically used when long-term issues (up to 30 years) have to be assessed. It is a useful means of predicting and assessing emerging developments where there is no empirical database, where external factors are likely to have a determining effect and where social arguments may dominate economic or technical considerations.

The goal of a Delphi study is to collect and synthesise opinions from experts in the field and to achieve a degree of convergence. The Delphi method is based on structural surveys. The key features of Delphi survey are giving feedback, and the anonymity of the participants. Therefore, the experts from the second round are under the influence of their colleagues’ opinions, which is what differentiates Delphi from ordinary opinion surveys.

The RIS3 mapping exercise showed that around 24% of studied 30 regions have used foresight related analytical approaches in RIS3 development. Only a couple of countries e.g. Lithuania, Poland and Romania have used Delphi surveys in the development of RIS3 (see case examples at the end of this document).

Description of the method

The Delphi exercise begins with the selection of the subject for the data inquiry. In the context of RIS3, the method can be used to in the first round to identify key trends and uncertainties affecting the national/regional development in the next 20-30 years. These trends and uncertainties can be grouped according to PEST categories to be political, economic, social and technological related. Moreover, the experts can be asked to also provide brief qualitative remarks related to the major national/regional implications of the trends and uncertainties they have chosen.

In the second round the Delphi method may be used to rank the trends according to their importance, and the uncertainties according to their importance and the level of uncertainty. It can thus be utilized for defining the bases for scenarios. The aim is to identify the two or three factors that are the most important and the most uncertain. These will be then selected as the scenario axes. The main goal (and challenge) is to conclude with just a few scenarios whose differences can inform the decision-maker.

Typically, the number of participants in Delphi survey is not high, as it is not necessarily meant to produce statistically relevant results. With regard to RIS3, it is important to ensure the participation of different kinds of parties representing all quadruple helix partners. Moreover, before an expert agrees to take part in a Delphi inquiry, he/she should understand the purpose of the inquiry, and should be aware that his/ her expertise should be made available in different rounds of the inquiry. It is preferable that the same person should administer and manage the questionnaire and communicate results to the experts.

With the online Delphi method, the responses of the first round can be either given after or during the first round to the panel members to review. In both cases, it is good to structure the responses and to remove the duplicate responses before providing them in the second round for the experts to evaluate. In the second round, it is also possible to ask for a brief justification from panel members for their opinion. The questionnaire can circulate until a consensus is reached, but a Delphi inquiry should not have more than four rounds.

Usability and impact

The Delphi method forces people to think about the future. In relation to workshops or focus groups, Delphi gives participants the opportunity to think in more depth and gather further information between the rounds. It is an efficient method to develop in-depth analyses, ranking and priority-settings among the experts based on together developed consensus.

Correctly focused, and with the full cooperation of participants, the Delphi method may potentially have a high impact on the quality of RIS3. Special attention is required for the selection criteria of expert participants and to ensure that the participants understand both the purpose of Delphi inquiry and that they are required to participate in all data collection rounds.

Required data

Key data are collected through expert surveys. Also desk research may be used to provide the initial set of trends and uncertainties for the survey, those for which there are obvious evidence such as aging population in Europe. Then, the experts may be used to provide additional trends and uncertainties those would not be able easily identified with pure desk research.

Relevant data sources

There are numerous applications for creating surveys (e.g webropol, Google Forms), which can be used as the basis to develop a RIS3 specific Delphi application.

Further information: Webropol, http://w3.webropol.com/news-4/

Implementation roadmap
  • Modify the Delphi survey questionnaire for regional use, e.g. adapt language if needed
  • Select and invite experts to participate in a Delphi survey.
  • Run the first round of survey, provide feedback and then repeat this for second and potentially third round of a survey
  • Write down survey results
  • Incorporate the results to RIS3 work, use them as basis for step 3.2. scenario development

References
  1. For-Learn, http://forlearn.jrc.ec.europa.eu/guide/4_methodology/meth_delphi.htm, [viewed 2016-11-08].

Case Examples

  1. Gheorghiu, R., Andreescu, L., Curaj, A. 2014. Dynamic argumentative Delphi: lessons learned from two large-scale foresight exercises. 5th international conference on future-oriented technology analysis, Brussels (2014), pp. 27–28 https://ec.europa.eu/jrc/sites/default/files/fta2014-t3practice_81.pdf
  • Gheorghiu, R., Adreescu, L., Curaj, A. 2016. A foresight toolkit for smart specialization and entrepreneurial discovery.Futures, 80, pp. 33–44. http://dx.doi.org/10.1016/j.futures.2016.04.001
  • Hilbert, M., Miles, I., Othmer, J. 2009. Foresight tools for participative policy-making in inter-governmental processes in developing countries: Lessons learned from the eLAC Policy Priorities Delphi. Technological Forecasting and Social Change, 15(2): 880–896.
  • Paliokaitė, A., Martinaitis, Ž., Reimeris, R. 2015. Foresight methods for smart specialisation strategy development in Lithuania. Technological Forecasting & Social Change, 101, pp. 185–199.
  • Smoliński, A., Bondaruk, J., Pichlak, M., Trząski, L., Uszok, E. 2015. Science-Economy-Technology Concordance Matrix for Development and Implementation of Regional Smart Specializations in the Silesian Voivodeship, Poland, Scientific World Journal, 2015
  • Vision 2023: Turkish National Technology Foresight Exercise, http://forlearn.jrc.ec.europa.eu/guide/6_examples/turkey2023.htm#Delphi, [viewed 2016-11-08]