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The Basics of the Scenario Method

The scenario method consists, for a given subject, to imagine a small number of distinctive, plausible scenarios of the future.

Plausible scenarios focus on plausible yet uncertain aspects of the future, unlike forecasting, which focuses on predictable aspects of the future, that is on probable futures. This is not to say that scenario leave trends and probable developments aside: these will be part of every scenario. Thus scenario builds on both the likely and less likely dimensions of the future.

The scenario method makes possible to explore different uncertainties of the future: drivers or developments that can lead to very different, sometimes opposite outcomes. It is these outcomes, combined together in a consistent manner, that build the different scenarios.

The different scenarios (typically 3 to 5) represent as many futures in which to project the business or subject of inquiry (e.g., the future of cash, of architecture as business and field of activity, of a region's sustainable future, etc.).

What would it mean for our topic? What would success look like?

What would we need to change?

On that basis, we can devise of decisions that are "robust", i.e. that cover as many different scenarios as possible.

The scenario method thus help us uncover new avenues and opportunities for our organisation or subject of inquiry, based on a systematic exploration of uncertainties in the future.

Desirable or exploratory scenarios?

Whether you are working on the future of your organisation, a business area, or a broader theme (e.g. the future of democracy in Europe), the first step is to determine whether the objective is to develop "desirable" or "exploratory" scenarios.

  • Desirable scenarios consist in imagining different inspiring and mobilising futures for your organisation or field of activity, in order to support you in your choices and decisions.

  • Exploratory scenarios are concerned with exploring plausible futures (i.e. not the most probable futures but plausible outcomes of uncertainties), so that you can better anticipate and prepare for eventualities otherwise not identified.

Defining the "givens": what is taken for granted

The second step is to define the "givens" or initial hypotheses, i.e. the conditions that we take for granted and do not challenge during the scenario process.

Making the givens explicit is one of the characteristics of a rigorous foresight approach.

Examples of possible conditions set as givens:

A small number of highly contrasted scenarios

The third step is to identify the key factors relevant to your issue, typically through a brainstorming exercise.

These key factors (typically 20 to 30) need to be further sorted into real uncertainties (with many different possible outcomes) or probable developments (i.e. (mega) trends leading to a single outcome). Only the real uncertainties are retained.

Finally, you need to identify and retain only those uncertainties that have a significant impact on your topic, in order to obtain 5 to 10 (12) critical, key uncertainties.

The fourth step is to imagine 2 to 5 different and plausible outcomes or effects for each of the key uncertainties. This can typically be done by groups taht work each on 1-2 key uncertainties.

The 5th step is to build the scenarios. This involves identifying the outcomes that are consistent across all the key uncertainties. The consistent combination of outcomes produces the scenarios.

Each scenario must be clearly distinguishable from the others and must be based on a set of clearly differentiated uncertainties about the future.

A set of 3 to 5 scenarios is considered ideal.

Step 6 is to describe the scenarios and their main drivers, rationals, indicators (quantifiable attributes) and predictors of occurrence.

The benefits of scenarios? Strategic orientation

Scenarios are different environments into which to project your future (step 7) in order to draw strategic decisions, actions, recommendations, or research avenues (step 8).

Gathering these different strategic lessons enables us to define decisions and actions said "robust", i.e. covering several scenarios (step 9).

Credible and plausible scenarios

In all cases, scenarios need to be credible and plausible to those for whom they are intended. Otherwise, they will be useless as a decision-making aid.

Internally consistent

Scenarios must follow an internally consistent logic.

All hypotheses must be explained and justified.


Scenarios must challenge the dominant visions of the future and the status quo.

Three alternative scenarios methods

The easy method :

The "Four images of the futur" by Dator

To design the scenarios, you can take inspiration from Prof. J. Dator, a reference in the field, who saw four main types of scenario or images of the future:

  • Continued Growth or Business as usual

  • Collapse

  • Discipline, reform

  • Transformation

(Dator, 1979) SeongWon Park, Journal of Futures Studies, 2013, 18(2):15

The 4 quadrant or matrix 2x2

Along the same lines, you can also identify 2 key uncertainties and their opposing effects. Cross them to obtain 4 quadrants which then give you the 4 orientations of your 4 scenarios.

A slightly more complex method: Key factors

A slightly more complex method consists of defining the most decisive key factors for the subject in question (brainstorming).

On this basis, a distinction is made between key factors that are trends and those that are the uncertainties that interest us. The aim is to reach a number of 5 to 10 uncertainties.

The consistent combination of an effect for each uncertainty produces the 3 to 6 scenarios. On this basis, you can consolidate the scenarios and describe their main drivers and justifications/indicators.

Key factors: a more complex version

A more complex version consists, once the uncertainties have been identified, in determining the extent to which they influence each other.

To do this, you need to enter your uncertainties in a matrix of interaction (a table where they appear both horizontally and vertically) and then indicate which key factor influences which key factor on a scale (from 1 to 4 - 7).

You'll then get a matrix of the results, displaying the various uncertainties on a vector map. Scenarios will be formed by grouping uncertainties geographically. On this basis, you can go into more detail about the scenarios and describe their main drivers and arguments/indicators.


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