The scenario method consists, for a given subject, to imagine a small number of well contrasted plausible scenarios.
Plausible futures are those that deal with uncertain aspects of the future, unlike forecasting, which deals with predictable aspects of the future, i.e. probable futures.
The method thus makes it possible to explore the uncertainties of the future and their relationships through distinct scenarios.
Their usefulness is to help us take a step back and take a fresh look at the subject in question, to discover new avenues and opportunities, and then to make decisions that are "robust", i.e. that cover as many different scenarios as possible.
The scenario method can therefore be understood as a learning process that invites us to adopt new perspectives on our current reality.
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 appealing 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 potential developments in the field under consideration, so that you can better anticipate and prepare for eventualities not yet identified.
Examples of scenarios of sustainability that can be perceived as desirable:
centralised state regulation accompanied by a new social contract, partial relocation of activities with a strengthening of the local economy and communities, flourishing entrepreneurship thanks to carbon-neutral innovations, etc.
Defining the "given": what is taken for granted
The second step is to define "given" or starting hypotheses, i.e. conditions which we take for granted and which will not be challenged during the process. Making explicit the given is one of the characteristics of a serious foresight approach.
Examples of possible conditions set as given:
the durability of the democratic political system and its major orientations, economic growth of X%, the commitment to achieve carbon neutrality by 2050 in accordance with the Paris Agreements, etc.
A small number of highly contrasted scenarios
The 3rd step is to determine the uncertainties and differentiate them from the trends.
Next, one need to imagine 2 to 5 distinct and plausible effects for each of these uncertainties (step 4).
The consistent combination of an effect of each uncertainty produces the scenarios (step 5).
Each scenario must be clearly differentiated from the others and be based on a series of clearly differentiated uncertainties about the future.
A number of 3 to 5 scenarios is considered ideal.
Step 6 is to examine the scenarios identified and describe their main drivers and arguments/indicators.
The benefits of scenarios? Strategic learning
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.
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
(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.