What Is The Delphi Method? The Delphi Method In A Nutshell

The Delphi method is a survey-based framework for estimating the likelihood and outcome of future events. The Delphi method is a survey-based framework for estimating the likelihood and outcome of future events. It was developed in response to military strategy formation during the Cold War. The Delphi method has been adapted considerably since the 1960s.

Concept Overview– The Delphi Method is a structured forecasting and decision-making technique used to collect and aggregate knowledge from a group of experts or participants. It aims to achieve consensus or make predictions in situations with uncertainty, often in areas where there is a lack of complete information.
Historical Context– Developed by the RAND Corporation in the 1950s, the Delphi Method was initially used for military planning. It has since evolved and found applications in various fields, including business, healthcare, technology, and policy-making.
Process Steps1. Selection of Experts: Experts or participants with relevant knowledge are selected to participate in the Delphi process.
2. Anonymity: Participants provide their opinions and forecasts anonymously to encourage open sharing and reduce the influence of dominant personalities.
3. Iterative Questionnaires: A series of structured questionnaires are used, with each round providing participants with feedback from the previous round. Participants can revise their responses based on this feedback.
4. Controlled Feedback: A facilitator or organizer aggregates and summarizes responses without revealing individual identities. The results are presented to participants in a way that encourages discussion and consensus building.
5. Iteration: The process continues through multiple rounds until consensus is reached or until a predefined stopping point is reached.
6. Reporting: The final results, including the aggregated responses and any emerging consensus, are reported, providing valuable insights and predictions.
Key PrinciplesAnonymity and Equal Participation: Anonymity allows participants to express their opinions openly without fear of criticism or conformity. Equal participation ensures that each expert’s input is given equal weight.
Iteration: The use of iterative rounds and controlled feedback allows for the refinement and convergence of opinions over time.
Expertise: The Delphi Method relies on the collective expertise of the participants, emphasizing the value of diverse perspectives.
Applications– The Delphi Method is applied in a variety of contexts, including technology forecasting, market research, policy planning, medical diagnosis, risk assessment, and strategic decision-making. It is particularly useful when dealing with complex, uncertain, or ambiguous problems.
AdvantagesReduction of Bias: Anonymity helps minimize biases and groupthink, leading to more unbiased and independent opinions.
Diverse Expertise: It leverages the diverse expertise of participants, providing a comprehensive view of the issue.
Systematic Process: The method provides a systematic framework for collecting and analyzing expert opinions.
Flexibility: It can be adapted to various situations and group sizes.
Challenges and LimitationsResource Intensive: Conducting multiple rounds and managing a Delphi study can be resource-intensive in terms of time and effort.
Expert Availability: Availability of experts may be a limitation, especially in niche or specialized fields.
Consensus Difficulty: Achieving consensus can be challenging and may not always be possible, particularly if experts have strongly divergent views.
Potential for Group Polarization: In some cases, the process may inadvertently lead to group polarization, where participants’ opinions become more extreme over time.
Subjectivity: The Delphi Method is still subject to the subjectivity and biases of the participating experts.
Ethical Considerations– Ethical considerations include maintaining anonymity and confidentiality of participants, ensuring their informed consent, and providing transparent reporting of results. Respecting the privacy and rights of participants is essential in conducting Delphi studies.
Contemporary Usage– In the digital age, the Delphi Method has evolved with the use of online platforms and collaborative tools to facilitate expert participation and data collection. These advancements enhance the method’s accessibility and efficiency.

Qualitative vs. Quantitative Research

Before we define the Delphi Method, let’s understand the difference between quantitative and qualitative research.

Whereas quantitative research, in general, leverages statistics as the basis for making generalizations about an issue at hand. On the other hand, qualitative research performs qualitative inquiry comprising small data, context, and human judgment.

In some instances, qualitative research is critical to define the scope of the quantitative analysis to inform it as much as possible.

Qualitative methods are used to understand, beyond the quantitative approach, the behaviors and attitudes of people by tapping into interviews, focus groups, and qualitative observation.

Indeed, the qualitative side helps better figure out what we’re trying to assess from a quantitative standpoint.

And on the other hand, the qualitative side also helps in better fine-tuning the quantitative insights to gather later on.

When we look at the quantitative data without understanding its qualitative implications, our quantitative research might be much more limited.

The characteristics of quantitative research contribute to methods that use statistics as the basis for making generalizations about something. These generalizations are constructed from data that is used to find patterns and averages and test causal relationships.

Thus, now that we have laid down the difference between qualitative and quantitative research, you can appreciate the importance of a qualitative method like the Delphi Method, which can inform quantitative research.

Understanding the Delphi method

The Delphi method was developed during the 1950s and 1960s to forecast the impact of technology on warfare.

At the time, experts were asked to give their personal opinion on the probability, intensity, and frequency of enemy attacks during the Cold War.

Opinions could be offered anonymously, and the process was repeated until a consensus became apparent.

Today, the Delphi method remains a structured and systematic forecasting process based on multiple rounds of questionnaires sent to a panel of experts.

The method has been used to predict trends in automation, aerospace, and the use of technology in schools.

Furthermore, the Delphi method can predict outcomes in business forecasting, policy formation, clinical work, and project management.

Delphi method characteristics

Although there is considerable variation in how the Delphi method is applied, there do exist some generally accepted characteristics in the form of best practices:

It must incorporate a group of participants, or panelists, selected for their relevant and specialized knowledge on a topic

A neutral facilitator with knowledge of research and data collection is also recommended. 

An initial idea generation stage should be held to get a broad sense of the most important issues.

It is often conducted across a series of two or more sequential questionnaires.

Ideas collected from the first questionnaire should then be used to construct the second questionnaire, and so on.

After each questionnaire round, there is an evaluation phase

Here, the panelists are provided with the overall panel response and asked to re-evaluate their standpoint by the facilitator.

If a consensus is not reached, another round of questioning occurs.

Strengths and weaknesses of the Delphi method


Diversity of opinion

The Delphi method is an effective way to assemble a diverse range of experts and then aggregate their opinions.

The anonymity afforded by the framework also encourages each expert to share their true feelings.


As noted earlier, the technique can be used to tackle a wide variety of issues, subjects, or situations.

There is also no requirement that the experts meet in person.


The response of each expert is weighted equally.

This democratic process ensures dominant personalities do not hijack the discussion or shift the prevailing opinion of the group.


Lack of clarity

Many practitioners struggle with the lack of clarity around what constitutes consensus.

Since it is highly unlikely a panel will reach 100% agreement, the integrity of the method may be compromised if a cut-off level is not established beforehand.

Limited scope

The Delphi method is effective when the only way to generate insight is via expert opinion.

In an evidence-based scenario such as healthcare intervention, the method may have limited use. 


Delphi studies can be complex and time-consuming, particularly if a consensus is not reached early.

Some experts may become disenfranchised and deliberately alter their views to conclude the process.

Others may shift their stance during the evaluation phase to comply with the majority view.

This phenomenon is called the bandwagon effect. 

Delphi method examples and case studies

Consider the following hypothetical Delphi model examples.

Business acquisition

In the first example, a company must decide whether to make a sizeable investment in acquiring another business.

A team of financial experts is assembled who then ideate and discuss whether the merger is in fact a good idea.

The panelists also discuss what steps the acquiring company should take if it proceeds or does not proceed with the deal.

Various elements of a successful merger are then discussed. It is pointed out that the merger should only proceed if both companies can create more value together than they could alone.

Another panellist may raise objections about the company’s debt, revenue, or product value.

Someone else notes that the cultures of the two companies must also be similar to ensure harmony and collaboration once the process is complete. 

The ideas are recorded and the first questionnaire concerning whether the deal makes sense from a financial point of view is completed by the group.

Most believe that the deal should go ahead, but a couple of individuals now share concerns about the synergies between both companies.

While each sells fast-moving consumer packaged goods, there is concern that most of the acquiring company’s products are sold in supermarkets while most of the target company’s products are sold in independent stores and gas stations.

A second questionnaire is then completed based on this point of difference with the panel once more asked to determine whether the acquisition should proceed.

Discussion should continue until there is a consensus that sufficient synergies exist between both companies.

One expert may sway the opinions of others by noting that the two companies have modular (resource-based) and sequential (value chain-based) synergies which make the acquisition more viable. 

Subsequent rounds of questionnaires are then performed until a final decision is made on whether to proceed.

Consensus on the logical steps management should take in either case is also defined by consensus.

Project development

In the second example, a tech company is tasked with creating a software system that removes some of the inefficiencies that are common in research laboratories.

To do this, the company assembles a team of experts consisting of scientists, research assistants, university students, and business professionals. 

Once assembled, the team is handed the first questionnaire that focuses on whether individuals believe efficiency can be increased, the extent of any subsequent revenue increase, and how the software will impact the industry.

The facilitator then reviews the answers provided and finds some significant discrepancies between different stakeholders.

Feedback common to each stakeholder group is then made available to be incorporated into the second round of questionnaires.

Business professionals, for example, may be required to review the project’s logistics based on hard data provided by the scientists.

Research assistants and university students may also influence the business stakeholders’ implementation timeline. 

The Delphi method continues until each stakeholder group arrives at a consensus on the software’s optimal release data, outcomes, and industry impact.

Healthcare treatment protocols

The Delphi method is primarily used in healthcare contexts to foster consensus around the proper development of treatment protocols.

This often occurs in situations where there is conflicting evidence or limited information on the most appropriate course of action.

In one example, a study involving expert physiotherapists collected data on the best ways to treat low back pain (LBP).

While clinical guidelines did exist prior to the completion of the study in 2008, there was no consensus on the management of low back pain among physiotherapists.

In any case, the results of the Delphi method would have notable implications for healthcare and indeed society itself, with over 90% of the adult population predicted to experience symptoms associated with low back pain in their lives.

To arrive at a consensus, a three-round Delphi study was conducted with a total of 34 physiotherapists involved.

The process started with a focus group that developed the key survey questions after conducting a literature review.

The panel of experts then provided their responses which were ranked in subsequent rounds of questioning using a five-point Likert scale.

Ultimately, the Delphi method indicated that it was possible to establish consensus between physiotherapists as to the best way to tackle LBP.

In fact, consensus was reached on 64 of the 95 responses (around 67%). In general, it was found that most LBP treatments adhered to the current, evidence-based clinical standards.

The panel of experts also identified the importance of the biopsychosocial model in treating patients.

Big data in obesity research

The Delphi method has also been used to build consensus around the definition (and use of) big data in obesity research.

While healthcare practitioners noted that obesity was a global challenge, there was a lack of clarity around the definition of big data and how it could be used in obesity-related research.

Some also believed that a lack of proper frameworks may be hindering progress toward solving the problem.

In response, a three-survey Delphi method was conducted to establish consensus on the best path forward.

In the first questionnaire, 96 participants were asked to either agree or disagree with 77 statements across seven domains related to the use of big data in obesity research.

At this point, participants were also called upon to contribute additional ideas that would be then used in subsequent survey rounds.

In the second and third rounds, participants reassessed their answers to facilitate consensus.

Consensus was achieved for 90.6% of the 77 statements and critically, there was 100% consensus around the definition of key terms such as big data, quality and inference domains, and data governance.

More specifically, it was agreed that big data was more complex and nuanced than the standard “volume, variety, and velocity” definition it is often attributed with.

Instead, the experts believed, big data should incorporate qualitative, quantitative, observational, and interventional data from a wide variety of sources.

Delphi method forecasting

The Delphi method is a qualitative forecasting method where a team of assembled experts makes a forecast based on their skills and knowledge.

This method is ideal for problems with no true solutions or where a wholly quantitative approach is not suitable.

Understanding the Delphi method forecasting process

Once the team of experts has been assembled to conduct a Delphi study, the facilitator asks each individual to submit a forecast based on detailed qualitative justification.

The integrity of the Delphi method depends on these steps since the individuals on the panel of experts must possess enough knowledge about a topic to:

  • Forecast the outcome of a future scenario.
  • Predict the likelihood of event occurrence, and
  • Reach a consensus about the topic in question.

Collectively, the forecast submitted by each individual forms a summary report which is then discussed and reviewed by the experts.

Based on this discussion, the panel makes an updated forecast and hands it back to the facilitator who reviews the material once more and issues a second report.

This process repeats until a consensus is reached.

It is important to note that each expert has access to the forecasts other experts have made in each round, but the forecasts themselves remain anonymous.

This encourages the panel to share their opinions openly and revise their earlier predictions in light of information provided by their counterparts. 

The Delphi method and demand forecasting

One popular application of the Delphi method is business demand forecasting.

In this scenario, each expert creates a demand forecast with a specific projection that is discussed and edited as necessary until consensus. 

The demand forecast is then handed to another department within the organization for review.

After multiple rounds of interpretation, the forecast is reviewed by senior management or others with decision-making authority.

The final forecast is then constructed based on the aggregation of the experts’ predictions.

Where is the Delphi method forecasting most useful?

Initially, the Delphi method was an effective way to forecast outcomes and trends in the science and tech industries.

As early as the 1960s, it was used in population control, war prevention, and weapons systems.

Other forecasts were subsequently made concerning industrial robots, broadband connections, vehicle-highway systems, and intelligent internet.

The method has also become useful as a way to forecast economic, educational, healthcare, and public policy outcomes.

In certain Caribbean and Latin American countries, for example, the Delphi method has been used in a partnership between the public and private sectors to identify the region’s most pressing economic and social issues.

When used in business demand forecasting, the Delphi method can be used by organizations to: 

  • Prepare their budget, make prudent financial decisions, and reduce risk.
  • Ensure that order fulfillment is synchronized with marketing campaigns before launch.
  • Forecast future sales numbers with 96-97% accuracy.
  • Reduce costs associated with inventory purchase orders and warehousing, and
  • Develop a pricing strategy based on demand, market competition, and other opportunities. 

Delphi Method vs. Starbursting

Starbursting is a structured brainstorming technique with a focus on question generation. Starbursting is a structured form of brainstorming, allowing product teams to cover all bases during the ideation process. It utilizes a series of questions to systematically work through various aspects of product development, forcing teams to evaluate ideas based on viability.

Whereas the Delphi method is a structured and systematic forecasting process based on multiple rounds of questionnaires sent to a panel of experts.

Starbursting is still a structured brainstorming technique but is skewed toward generating the right questions to tackle in the ideation process to develop relevant products.

Thus, the Delphi method is skewed toward getting answers from specific questions.

Starbursting is about asking the right questions in the first place.

Delphi Method vs. Affinity Grouping

Affinity grouping is a collaborative prioritization process where group participants brainstorm ideas and opportunities according to their similarities. Affinity grouping is a broad and versatile process based on simple but highly effective ideas. It helps teams generate and then organize teams according to their similarity or likeness.

Whereas the Delphi method looks into getting the opinion of experts on a topic with a structured set of questions.

Affinity grouping is a less structured, more versatile approach to idea generation, which later needs to be prioritized to be introduced into an innovation pipeline, for experimentation.

Delphi Method vs. Nominal Group Technique

The nominal group technique was initially conceived by Andrew H. Van de Ven and Andrew L. Delbecq in their 1975 book Group techniques for program planning: A guide to nominal group and Delphi processes. The nominal group technique (NGT) is a brainstorming framework that encourages equal contribution from stakeholders and facilitates group consensus on key issues, problems, and their solutions.

Both the nominal group technique (NGT) and the Delphi method are ways to determine consensus among groups.

Yet, the NGT is more focused on facilitating group consensus for small and controlled groups, while the Delphi method encourages diversity and equality of opinion and has no locational constraints.

Delphi Method vs. Panel Consensus

Both the Delphi method and panel consensus are decision-making techniques that synthesize the opinions of a group of experts. The main difference is in how they gather and process the group’s opinions.

Whereas the Delphi method is a structured group communication to elicit and synthesize the opinions of experts on a specific topic.

That borrows itself to be effective in complex decisions, which involve several rounds of questionnaires, with the results of each round being used to refine the questions for the next round with the goal to achieve a consensus or convergence of opinion among the experts.

Panel consensus, on the other hand, involves gathering a group of experts in one place, either physically or virtually, to discuss and reach a consensus on a particular topic.

The panel may be asked to review and evaluate evidence, discuss and debate the issue, and then reach a consensus or majority opinion on the matter.

Panel consensus can be a more time-consuming and resource-intensive process than the Delphi method, but it allows for more direct interaction and discussion among the experts.

Key takeaways:

  • The Delphi method is a survey-based framework for estimating the likelihood and outcome of future events. It was developed in response to military strategy formation during the Cold War.
  • The Delphi method has been adapted considerably since the 1960s. For best results, a facilitator must lead the panel through a series of iterative, reflective, and evaluative questionnaires until a consensus is reached.
  • The Delphi method encourages diversity and equality of opinion and has no locational constraints. However, it does not provide detailed guidance on group consensus and may be complex and time-consuming to complete.

Key Highlights:

  • Delphi Method Overview:
    • The Delphi method is a survey-based framework for forecasting future events and outcomes.
    • Developed during the Cold War to forecast the impact of technology on warfare.
    • Involves multiple rounds of questionnaires sent to a panel of experts to elicit and synthesize their opinions.
  • Qualitative vs. Quantitative Research:
    • Qualitative research focuses on understanding attitudes and behaviors through small data, context, and human judgment.
    • Quantitative research uses statistics to make generalizations based on data patterns and averages.
    • Qualitative insights can inform and refine quantitative analysis.
  • Characteristics of the Delphi Method:
    • Involves a panel of experts with specialized knowledge.
    • Utilizes multiple rounds of questionnaires and anonymous responses.
    • Facilitated by a neutral facilitator with research expertise.
    • Incorporates an initial idea generation stage and evaluation phases after each round.
  • Strengths of the Delphi Method:
    • Gathers diverse expert opinions.
    • Encourages open sharing due to anonymity.
    • Versatile and applicable to various fields.
    • Ensures equal weight for each expert’s response.
  • Weaknesses of the Delphi Method:
    • Lack of clarity in defining consensus.
    • Limited scope for evidence-based scenarios.
    • Can be time-consuming and intensive.
    • Potential for bandwagon effect and opinion shifts.
  • Delphi Method Applications:
    • Used in various fields such as business forecasting, policy formation, clinical work, and project management.
    • Examples include business acquisitions, project development, healthcare treatment protocols, and big data in obesity research.
  • Delphi Method Forecasting Process:
    • Experts submit forecasts with qualitative justifications.
    • Facilitator compiles and reviews forecasts, updates them, and repeats the process until consensus is reached.
    • Anonymity encourages open sharing and revisions based on others’ opinions.
  • Delphi Method in Demand Forecasting:
    • Applied in business demand forecasting to prepare budgets, make financial decisions, and reduce risks.
    • Helps synchronize order fulfillment with marketing campaigns.
    • Can predict future sales numbers with high accuracy.
  • Comparison with Other Techniques:
    • Compared to techniques like Starbursting, Affinity Grouping, Nominal Group Technique, and Panel Consensus.
    • Each technique has its strengths and focuses on different aspects of decision-making, consensus, and idea generation.
  • Evolution and Utility:
    • Originally used for science and tech forecasting, the Delphi method now finds applications in various fields.
    • Useful for predicting outcomes, trends, and consensus in complex and uncertain scenarios.

What is the Delphi method used for?

The Delphi method is a survey-based framework for estimating the likelihood and outcome of future events developed in response to military strategy formation during the Cold War. This method encourages diversity and equality of opinion and has no locational constraints.

Is Delphi qualitative or quantitative?

The interesting aspect of the Delphi method is that it combines quantitative and qualitative research. Thus making it an approach that leverages both methodologies. In fact, the Delphi method asks a round of questions anonymously to a group of experts concerning future events.

What are the steps of Delphi method?

  • It must incorporate a group of participants.
  • An initial idea-generation stage should be held.
  • It is often conducted across a series of two or more sequential questionnaires.
  • After each questionnaire round, there is an evaluation phase.
  • After the evaluation phase, the Delphi Method will inform the likelihood and outcome of future events.

Other connected business strategy frameworks

PESTEL Analysis

The PESTEL analysis is a framework that can help marketers assess whether macro-economic factors are affecting an organization. This is a critical step that helps organizations identify potential threats and weaknesses that can be used in other frameworks such as SWOT or to gain a broader and better understanding of the overall marketing environment.

STEEP Analysis

The STEEP analysis is a tool used to map the external factors that impact an organization. STEEP stands for the five key areas on which the analysis focuses: socio-cultural, technological, economic, environmental/ecological, and political. Usually, the STEEP analysis is complementary or alternative to other methods such as SWOT or PESTEL analyses.

STEEPLE Analysis

The STEEPLE analysis is a variation of the STEEP analysis. Where the step analysis comprises socio-cultural, technological, economic, environmental/ecological, and political factors as the base of the analysis. The STEEPLE analysis adds other two factors such as Legal and Ethical.

Porter’s Five Forces

Porter’s Five Forces is a model that helps organizations to gain a better understanding of their industries and competition. Published for the first time by Professor Michael Porter in his book “Competitive Strategy” in the 1980s. The model breaks down industries and markets by analyzing them through five forces.

SWOT Analysis

SWOT Analysis is a framework used for evaluating the business’s Strengths, Weaknesses, Opportunities, and Threats. It can aid in identifying the problematic areas of your business so that you can maximize your opportunities. It will also alert you to the challenges your organization might face in the future.

BCG Matrix

In the 1970s, Bruce D. Henderson, founder of the Boston Consulting Group, came up with The Product Portfolio (aka BCG Matrix, or Growth-share Matrix), which would look at a successful business product portfolio based on potential growth and market shares. It divided products into four main categories: cash cows, pets (dogs), question marks, and stars.

Balanced Scorecard

First proposed by accounting academic Robert Kaplan, the balanced scorecard is a management system that allows an organization to focus on big-picture strategic goals. The four perspectives of the balanced scorecard include financial, customer, business process, and organizational capacity. From there, according to the balanced scorecard, it’s possible to have a holistic view of the business.

Blue Ocean Strategy

A blue ocean is a strategy where the boundaries of existing markets are redefined, and new uncontested markets are created. At its core, there is value innovation, for which uncontested markets are created, where competition is made irrelevant. And the cost-value trade-off is broken. Thus, companies following a blue ocean strategy offer much more value at a lower cost for the end customers.

Scenario Planning

Businesses use scenario planning to make assumptions on future events and how their respective business environments may change in response to those future events. Therefore, scenario planning identifies specific uncertainties – or different realities and how they might affect future business operations. Scenario planning attempts at better strategic decision making by avoiding two pitfalls: underprediction, and overprediction.

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