The Delphi method is a communication technique leveraged for long-term predictions or forecasts. The approach resides on the theory that projections are more accurate when developed by a structured group of experts instead of an unstructured assembly (Tidd & Bessant, 2005). The Delphi method's process begins with a survey, gathering feedback from experts on future trends, technology, and growth likelihood. The qualitative approach uses iteration with the group, often polling the audience multiple times with a more narrow-focused question set. The selection of experts and the choice of questions are important, contributing to the reasoning behind numerous iterations of questioning (Okoli & Pawlowski, 2004). The process is intentionally individualized, as opposed to a group meeting format, so that the group is not influenced or persuaded by a single person (Tidd & Bessant, 2005).
In Okoli and Pawlowski (2004), the research indicates that the Delphi method is a compelling theory development method. First, the initial stages enable variable development and generation of propositions. Next, the diversity of the experts leads to the strengthening of the grounded theory and likelihood of theory applicability. Third, justification of an expert's answer leads to a better understanding of causal relationships between factors underpinning the approach. Lastly, the method contributes to "construct validity," or the precise definition of the paradigm. While theory construction is not a traditional use of the Delphi method, it illustrates an interesting use case.
Another forecasting method is scenario development, which are consistent accounts of possible future outcomes. The scenario method applies best under two different situations; first, when a desired vision of the future exists, and scenarios enable different achievement pathways; secondly, for exploration and discovery where no explicit objective exists. Various scenarios are typical, accounting for different assumptions and understandings of forces driving change. The execution of scenario development includes mixing two methods, quantitative (leveraging data as input) and qualitative (to capture expectations and assessments). The result of scenarios is advantageous in evaluating potential events and the impacts those events might have when combined on an outcome. The scenario design leverages critical indicators to measure the effort's progress and compare different results (Tidd & Bessant, 2005).
In Ramirez et al. (2015), scenarios produce what the authors call "interesting research," referring to research efforts that are both innovative and develop theory. Scenarios in research enable narratives for a specific purpose, often providing new insights for additional work. The scenario development method is a viable solution for research methodology by establishing epistemological issues once seen as barriers. Like the Delphi method, scenario development is not limited to traditional research objects but as a proven option for theory development.
The Delphi method and scenario development are best for long-term forecasting and predictive outcomes. The Delphi method, based on segregated input from participants, builds a consensus through iteration. The scenario development method works well in high ambiguity situations by using indicators as intervals towards an outcome. Each method has its own set of risks. The Delphi method is challenging when experts disagree to the point where a consensus is unreachable. Also, selecting the wrong group of experts or choosing incorrect questions may lead to an erroneous conclusion. The scenario development method is often time-consuming and, without useful indicators, might lead to unacceptable outcomes (Tidd & Bessant, 2005). However, in Okoli and Pawlowski (2004) and Ramirez et al. (2015), it becomes clear that both methods can extend into the theory development space, a unique perspective on the two traditional methods.
References
Okoli, C., & Pawlowski, S. D. (2004). The Delphi method as a research tool: an example, design considerations and applications. Information & Management, 42(1), 15-29. https://doi.org/10.1016/j.im.2003.11.002
Ramirez, R., Mukherjee, M., Vezzoli, S., & Kramer, A. M. (2015). Scenarios as a scholarly methodology to produce "interesting research". Futures, 71, 70-87. https://doi.org/10.1016/j.futures.2015.06.006
Tidd,
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