Futures Wheel

The Futures Wheel is a structured futures research method used to identify and explore the direct and indirect consequences of a change, trend, event, decision or emerging issue. The focal development is placed at the centre of the wheel, its immediate consequences are mapped around it, and the consequences of those consequences are then explored through additional outward layers.

The method was developed by futurist Jerome C. Glenn in the early 1970s as a way of systematically considering potential future impacts. It is now used in futures research, strategic foresight, policy analysis, education and organizational decision-making. Rather than predicting exactly what will happen, a Futures Wheel helps researchers investigate what could happen if a particular development occurs or continues.

Its apparent simplicity can be misleading. Drawing possible consequences is relatively easy; deciding which consequences are plausible, important and worthy of further investigation is considerably harder. For research purposes, the Futures Wheel therefore benefits from separating two activities: generating possible consequences broadly and evaluating important consequences critically.

On this page:

• Futures Wheel Explained Simply
• What Is a Futures Wheel?
• How a Futures Wheel Works
• First-, Second- and Third-Order Consequences
• How to Create a Futures Wheel
• Generating Consequences Without Prematurely Filtering Them
• Evaluating the Consequences
• Dudovskiy Futures Wheel Consequence Evaluation Framework
• Futures Wheel vs Mind Map
• Combining Futures Wheel with Other Futures Research Methods
• Application of Futures Wheel: an Example
• Advantages and Limitations of Futures Wheel
• Common Mistakes When Using Futures Wheel
• Futures Wheel in Business Research
• Futures Wheel in the Age of AI and Digital Research
• When to Use Futures Wheel
• Dissertation Example
• Exam Tip

Futures Wheel Explained Simply

Suppose a government announces that all new passenger cars sold after a future date must be electric.

The obvious first-order consequences might include increased demand for electric vehicles, declining demand for new petrol cars and greater need for charging infrastructure. Each of these developments can then produce additional consequences. Increased electric-vehicle adoption, for example, could increase electricity demand, which could influence investment in electricity generation and distribution. Expansion of charging infrastructure might affect petrol-station business models, commercial property and urban planning.

These consequences can continue outward through additional layers.

The purpose is not to claim that every consequence will occur. Instead, the Futures Wheel forces researchers to move beyond the most immediate effect and ask:

“And what might happen because of that?”

Dudovskiy Research Assistant

Not sure if futures wheel is the correct methodology for your dissertation?

Enter your topic to receive a free, tailored methodology preview.

Dissertation topic

Generate Free Methodology Preview → Free · No account required

Learn more about Dudovskiy Research Assistant

What Is a Futures Wheel?

The Futures Wheel was developed by Jerome C. Glenn as a method for systematically identifying and organizing potential consequences of change. Glenn’s work subsequently incorporated the method into the broader body of futures research methodology developed through the Millennium Project.

The method is visually organized around a central development. This might be a technological breakthrough, regulatory change, demographic trend, strategic decision, emerging issue or hypothetical future event. Researchers identify its direct consequences and position them around the centre. They then examine each direct consequence and identify additional consequences that could result from it.

The result resembles a wheel because chains of consequences radiate outward from the central development. However, the diagram is not merely a visualization technique. Its methodological purpose is to encourage researchers to consider indirect and higher-order implications that may be missed when attention remains focused only on immediate effects.

A Futures Wheel should therefore be interpreted as an exploration of possible causal pathways, not as a deterministic model of the future.

How a Futures Wheel Works

A Futures Wheel begins with a clearly formulated focal development. The quality of this starting statement matters because a vague or excessively broad central issue can produce consequences that are equally vague. “Artificial intelligence,” for example, may be too broad for a useful analysis, whereas “widespread adoption of generative AI for customer-service interactions in retail banking” establishes a more specific analytical starting point.

Participants first ask what could occur directly because of the focal development. These first-order consequences are positioned around the centre and connected to it. Attention then moves outward. For each first-order consequence, researchers ask what might happen because that consequence occurs. These become second-order consequences.

The process can continue to third-order and, where useful, further consequences. As the wheel expands, the relationships become increasingly indirect and usually more uncertain. At the same time, the process can reveal implications that were not apparent from the original focal development.

A simplified structure is:

Focal development → First-order consequences → Second-order consequences → Third-order consequences

This sequence represents increasing causal distance, not necessarily decreasing importance.

First-, Second- and Third-Order Consequences

Understanding consequence order is fundamental to using the Futures Wheel correctly.

A first-order consequence follows directly from the focal development. If remote working becomes the dominant working arrangement for office employees, reduced daily commuting could be a first-order consequence.

A second-order consequence follows from one of those first-order consequences. Reduced commuting might lower weekday demand for city-centre parking. A third-order consequence could then arise if falling parking demand encourages redevelopment of parking facilities into residential, retail or recreational space.

The distinction is based on the position of a consequence within the pathway:

Remote working becomes dominant

↓

Less commuting — first order

↓

Lower city-centre parking demand — second order

↓

Redevelopment of parking facilities — third order

Researchers should not assume that first-order consequences are more important merely because they are closer to the focal development. Higher-order consequences may be less obvious but strategically significant. Bengston’s work on Futures Wheels similarly emphasizes the value of exploring indirect consequences and cautions against interpreting the resulting possibilities as predictions.

Order tells us how far a consequence is from the initiating development. It does not tell us how important that consequence is.

How to Create a Futures Wheel

The first step is to define the focal development precisely enough to generate meaningful consequences. Researchers should clarify whether they are analysing a trend, event, proposed decision, emerging issue or hypothetical future condition and, where necessary, specify the relevant geography, sector and time horizon.

The next task is to generate first-order consequences. Participants should consider both desirable and undesirable effects and avoid concentrating exclusively on consequences that support their existing expectations. Diverse participation can improve this stage because people with different expertise and stakeholder positions may notice different implications.

Once the first-order layer is reasonably developed, attention moves to the second-order consequences. Rather than immediately following one interesting branch all the way outward, it is generally better to develop the first-order layer broadly before systematically moving to subsequent layers. This reduces the risk that the wheel becomes dominated by one early line of thought.

Researchers can then repeat the process for third-order consequences where further exploration remains useful. Connections should be recorded clearly so that the pathway from the central development to each consequence remains visible.

The wheel should initially be treated as a structured possibility map. Evaluation comes next.

Generating Consequences Without Prematurely Filtering Them

Futures research frequently deals with developments whose evidence is incomplete precisely because they have not yet fully emerged. Applying strict probability tests during the initial generation stage can therefore eliminate unusual but potentially important possibilities before they have been considered.

A productive Futures Wheel initially permits participants to think expansively. Positive, negative, intended, unintended and relatively low-probability consequences may all deserve consideration. The objective at this stage is not to prove that a consequence will occur, but to expose possible pathways that conventional linear analysis might overlook.

This does not mean that every idea should later receive equal analytical weight. A speculative third-order consequence supported only by a tenuous chain of assumptions should not be treated in the same way as a direct consequence supported by substantial evidence.

The methodological solution is to separate the stages:

Generate broadly → Evaluate critically

This separation preserves the exploratory strength of the Futures Wheel without turning brainstorming into unsupported forecasting.

Evaluating the Consequences

Once the wheel has generated a sufficiently broad set of consequences, researchers can begin evaluating which ones warrant greater attention. The criteria used should correspond to the purpose of the study rather than being applied mechanically.

Plausibility concerns whether there is a credible pathway connecting one consequence to the next. Researchers should be able to explain why consequence B might reasonably result from consequence A rather than relying on visual proximity in the diagram.

Evidence concerns what supports that relationship. Historical analogies, existing research, current trends, expert judgement and empirical observations may provide different forms of support. Futures research inevitably involves uncertainty, so lack of definitive evidence does not automatically invalidate a consequence; it should, however, influence how confidently the consequence is presented.

Magnitude considers how significant the effect could become, while uncertainty captures how little is known about whether, when or in what form it might occur. Researchers can also consider time horizon, because some consequences could emerge quickly while others require many years of preceding change.

Finally, consequences may affect stakeholders differently. What constitutes an opportunity for one organization or social group may create costs for another. Evaluating stakeholder effects can therefore reveal distributional consequences hidden by a simple positive-versus-negative classification.

Dudovskiy Futures Wheel Consequence Evaluation Framework

The Dudovskiy Futures Wheel Consequence Evaluation Framework is a practical decision aid for moving from consequence generation to systematic evaluation. It does not modify Glenn’s established Futures Wheel method or claim to introduce the concepts of first-, second- or third-order consequences. Instead, it addresses a practical problem that arises after a wheel has generated many plausible possibilities: which consequences deserve serious analytical attention?

The framework begins only after the exploratory consequence-generation stage. Each potentially important consequence can be examined across six dimensions.

Plausibility asks whether a credible pathway connects the consequence to the preceding development. Evidence examines what information, theory, analogy or expert reasoning supports that pathway. Magnitude considers the possible significance of the effect, while uncertainty makes explicit how tentative the judgement remains.

Time horizon asks when the consequence could become relevant and whether preceding conditions need to occur first. Stakeholder impact examines who could experience the consequence and whether effects differ between groups. Taken together, these dimensions inform analytical priority: whether the consequence deserves further research, expert assessment, monitoring or consideration in subsequent futures methods.

The sequence is:

Generated Consequence → Plausibility → Evidence → Magnitude → Uncertainty → Time Horizon → Stakeholder Impact → Analytical Priority

The central principle is:

A Futures Wheel is strongest when researchers separate two tasks: generating possible consequences broadly and evaluating important consequences critically.

This distinction also prevents a common error: confusing the order of a consequence with its importance. A third-order consequence can receive high analytical priority if its potential impact is substantial, even though the pathway leading to it is longer and more uncertain.

Futures Wheel vs Mind Map

A Futures Wheel can visually resemble a mind map because both place a central idea within a network of connected concepts. Their analytical purposes, however, are different.

A mind map primarily organizes ideas and associations around a topic. Connections do not necessarily imply that one concept produces another. In a Futures Wheel, the connections are intended to represent consequence relationships. A second-order consequence appears where it does because it may result from a particular first-order consequence.

A visually attractive diagram is therefore not necessarily a Futures Wheel. The logic connecting the nodes is more important than the circular appearance.

Combining Futures Wheel with Other Futures Research Methods

The Futures Wheel becomes particularly useful when positioned within a broader futures research process.

Environmental Scanning can precede the Futures Wheel. Scanning identifies emerging issues, weak signals, trends and potential drivers of change. A development judged sufficiently important can then become the focal issue at the centre of a Futures Wheel.

The wheel generates possible direct and indirect implications. Those consequences can subsequently provide inputs to a Delphi Method study, where appropriately selected experts evaluate issues requiring structured expert judgement.

Cross-Impact Analysis can perform another function by examining how multiple developments may influence one another rather than following only consequence chains from a single focal development.

A simplified methodological sequence could therefore be:

Environmental Scanning → Identify important development → Futures Wheel → Explore consequences → Delphi / Cross-Impact Analysis → Further evaluation

This sequence is illustrative rather than mandatory. Futures methods should be combined because their analytical functions complement one another, not because every futures research project requires the same methodological pipeline.

Application of Futures Wheel: an Example

Consider a research project investigating the possible implications of widespread commercial adoption of autonomous delivery vehicles in major European cities by 2035.

The central development would be placed at the centre of the Futures Wheel. Potential first-order consequences might include reduced demand for human delivery drivers, lower last-mile delivery costs, increased demand for autonomous-vehicle infrastructure and new regulatory requirements.

Reduced last-mile delivery costs could produce second-order consequences such as increased consumer expectations for rapid delivery and greater commercial viability of frequent small orders. This might then generate third-order effects including changes in urban warehouse locations, packaging volumes and competitive pressure on traditional retailers.

Meanwhile, reduced demand for delivery drivers could produce a separate chain involving employment displacement, retraining requirements and political pressure for labour-market intervention. Infrastructure requirements could generate another branch involving curb-space allocation, charging facilities and changes to urban planning.

The completed wheel would not demonstrate that any of these consequences will occur. The researcher could use the Dudovskiy Futures Wheel Consequence Evaluation Framework to assess selected consequences according to plausibility, supporting evidence, potential magnitude, uncertainty, time horizon and stakeholder impact. Consequences with high potential significance but substantial uncertainty might then be selected for expert evaluation through a Delphi study.

Advantages and Limitations of Futures Wheel

One of the strongest advantages of the Futures Wheel is its ability to push analysis beyond immediate effects. Decision-makers naturally tend to focus on obvious first-order consequences, yet indirect effects can become strategically important. The wheel makes these pathways visible and encourages participants to consider intended and unintended consequences simultaneously.

Its visual structure also supports collaborative research. Participants from different backgrounds can contribute consequences based on their own expertise, challenge assumed pathways and identify effects on stakeholders that others may overlook. The resulting diagram provides a transparent record of how participants moved from the initiating development toward more distant possibilities.

The same openness creates limitations. Futures Wheels can become very large and difficult to interpret. As causal distance increases, consequence chains often depend on more assumptions, making later-order effects increasingly uncertain. Participants can also generate consequences reflecting their own biases, knowledge gaps and expectations.

Most importantly, the method does not automatically establish probabilities or causal validity. A line connecting two nodes indicates a proposed consequence relationship, not proof that one will cause the other. The analytical credibility of a Futures Wheel therefore depends on how carefully its consequences are generated, documented, evaluated and communicated.

Common Mistakes When Using Futures Wheel

A frequent mistake is treating the Futures Wheel as a prediction. Researchers may present the completed diagram as though it shows what the future will look like. In reality, it maps possible consequences conditional on an initiating development and a series of subsequent relationships.

Another mistake is following one interesting branch outward before adequately exploring the rest of the first-order consequences. This can create an unnecessarily linear wheel and cause early ideas to dominate the analysis. Developing each consequence layer more systematically encourages broader thinking.

Researchers can also confuse consequence order with probability or importance. A third-order consequence is not automatically improbable, trivial or remote in time; its order simply indicates that it occurs further along a consequence pathway.

Premature filtering is another problem. Rejecting unconventional possibilities during brainstorming can undermine the exploratory purpose of the method. Conversely, retaining every generated idea as equally credible creates the opposite problem. The stronger approach is to distinguish generation from evaluation.

Finally, a Futures Wheel should not become an elaborate mind map. Every outward connection should represent a reasoned potential consequence relationship rather than a general association with the central topic.

Futures Wheel in Business Research

The Futures Wheel is useful in business research when organizations need to understand how a significant external development or strategic decision could create consequences beyond its immediate effects. Potential focal developments include new technologies, regulatory changes, demographic shifts, changing consumer behaviour, sustainability requirements and new business models.

For example, a researcher examining widespread adoption of generative AI in professional services could explore first-order consequences such as automation of routine analytical tasks and lower production costs. Those developments might influence staffing models, graduate recruitment, pricing structures, client expectations and eventually the competitive architecture of professional-service industries.

The method is especially useful before strategic decisions are finalized because indirect consequences can reveal risks or opportunities overlooked by conventional short-term analysis. It should nevertheless be presented as exploratory foresight rather than as evidence that a particular commercial outcome will occur.

Futures Wheel in the Age of AI and Digital Research

Generative AI can greatly accelerate consequence generation. A researcher can ask an AI system to suggest dozens of possible first-, second- and third-order effects across technological, economic, social, environmental and regulatory domains. Used carefully, this can help expose blind spots and stimulate branches that human participants might initially overlook.

The same capability creates a serious methodological risk. AI systems can generate plausible-sounding causal chains without reliable evidence that those relationships exist. A wheel populated automatically by AI may therefore become visually sophisticated while containing hidden assumptions, fabricated relationships or repetitive ideas expressed in different language.

This makes the distinction between generation and evaluation even more important in AI-assisted Futures Wheels. AI can serve as a brainstorming participant, clustering assistant or challenge mechanism, but consequential pathways should remain subject to researcher evaluation and, where appropriate, external evidence or expert judgement.

Researchers should also document the role AI played. If AI generated potential consequences, combined participant responses or evaluated similarities between branches, this forms part of the analytical process and should be reported transparently. Human participants should remain able to preserve minority or unconventional consequences rather than allowing automated summarization to create artificial convergence.

Paradoxically, AI makes it easier than ever to create a Futures Wheel and more important than ever to ask whether its consequences are methodologically defensible.

When to Use Futures Wheel

Futures Wheel may be appropriate when:

• the research question concerns the possible consequences of a future change, trend, event or decision;
• indirect and unintended effects are important to the research problem;
• an emerging issue identified through environmental scanning requires deeper exploration;
• researchers need to distinguish immediate consequences from higher-order consequences;
• multiple stakeholder perspectives could reveal different impacts;
• the research is exploratory and does not require precise prediction of one future;
• a visual representation of consequence pathways would support analysis or stakeholder discussion; or
• the outputs will inform subsequent methods such as Delphi, scenario analysis or Cross-Impact Analysis.

The method is less appropriate when the research question requires statistically estimating the probability of a particular outcome, demonstrating causal effects from observed data or producing a precise forecast.

Dissertation Example

Consider a dissertation titled “Exploring the Future Implications of Generative AI Adoption for Entry-Level Employment in the UK Accounting Profession.” A Futures Wheel could be justified because the research objective concerns not merely the immediate effect of AI adoption but the wider direct and indirect consequences that may develop through interconnected changes in work, skills and organizational practices.

The methodology chapter could explain that widespread generative AI adoption in accounting work will form the central development. Initial consequences would be generated from a combination of environmental-scanning evidence and a workshop involving accounting professionals, technology specialists and academics. Participants would first identify direct consequences before systematically exploring second- and third-order effects, reducing the risk of following isolated branches prematurely.

The researcher could then evaluate important generated consequences according to plausibility, supporting evidence, magnitude, uncertainty, time horizon and stakeholder impact. The resulting analysis might identify consequences requiring additional investigation, such as changes in graduate recruitment, professional training requirements or career progression pathways.

The methodology chapter should make clear that these consequences represent structured explorations of possible futures rather than predictions. If selected consequences are subsequently assessed by an expert Delphi panel, the researcher should explain the distinct methodological function of each stage: the Futures Wheel generates and structures potential implications, whereas Delphi provides a process for systematically refining expert judgement about selected issues.

Exam Tip

If asked to explain the Futures Wheel in an examination or dissertation defence, do not simply say that it is “a diagram showing the effects of a future event.” Explain its consequence logic.

A strong answer identifies a central change or development, followed by first-order direct consequences and subsequent second- and third-order indirect consequences. It should also make clear that the wheel explores possible implications rather than predicting that every identified consequence will occur.

Remember the distinction:

Consequence order = position within the pathway.

Consequence importance = significance of the potential effect.

They are not the same thing.

Exploring the future implications of your dissertation topic?

Dudovskiy Research Assistant can help determine whether a Futures Wheel fits your research question, define an appropriate focal development, distinguish first-, second- and third-order consequences, and develop a defensible approach for evaluating the resulting possibilities.

References

Bengston, D.N. (2016). The Futures Wheel: A method for exploring the implications of social-ecological change. Society & Natural Resources, 29(3), 374–379.

Glenn, J.C. (1972). Futurizing teaching vs futures course. Social Science Record, 9(3), 26–29.

Glenn, J.C. (2009). The Futures Wheel. In J.C. Glenn & T.J. Gordon (Eds.), Futures Research Methodology—Version 3.0. The Millennium Project.

Glenn, J.C. & Gordon, T.J. (Eds.). (2009). Futures Research Methodology—Version 3.0. The Millennium Project.