Scenario Analysis

Scenario Analysis aims to describe logical and internally consistent sequences of events to explore how the future may, could or should evolve from the past and present. The future is inherently uncertain. Different alternative futures can be explored through scenario analysis. As such, scenario analysis is also a tool to deal explicitly with different assumptions about the future. A definition is “Scenarios are descriptions of journeys to possible futures. They reflect different assumptions about how current trends will unfold, how critical uncertainties will play out and what new factors will come into play” (UNEP, 2002). Another definition is: “A scenario is a description of the present state of a social and or natural system (or a part of it), of possible and desirable future states of that system along with sequences of events that could lead from the present state to these future states.” Other definitions also include the purposes of the use of scenarios.

Different types of scenarios can be distinguished. For instance, Alcamo (2001) discerns baseline vs. policy scenarios, exploratory vs. anticipatory scenarios and qualitative vs. quantitative scenarios.

Baseline scenarios present the future state of society and environment in which no (additional) environmental policies do exist or have a discernible influence on society or the environment. Policy scenarios depict the future effects of environmental protection policies. Exploratory scenarios start in the present and explore possible trends into the future. Anticipatory scenarios start with a prescribed vision of the future and then work backwards in time to visualise how this future could emerge. Qualitative scenarios describe possible futures in the form of narrative texts or so-called “story-lines”. Quantitative scenarios provide tables and figures incorporating numerical data often generated by sophisticated models.

Finally, scenarios can be surprise-free or trend scenarios, that extend foreseen developments, on the one hand or include surprises and exploring the extremes (e.g. best case / worst case) on the other hand.

 

Resources required
Scenario analysis requires creativity and ability to think outside the scope of the familiar and the present. Furthermore, it requires insight in dynamics, relationships, in synergies of systems and their environment and thus it requires a broad knowledge of the field involved. Therefore, scenarios analysis should take place in an interdisciplinary team. In the case of a quantitative approach, computer models or spreadsheets or other software are needed to run/visualise scenarios. Access to relevant data is important in order to be able to construct the scenarios.

In the case of a qualitative approach, input has to be collected from experts, stakeholders or users in workshops with stakeholders to be able to develop storylines. Basic skills for facilitating groups are required. Both approaches are time and resource consuming.

Objectives of scenraio analysis
Typical objectives of scenario analysis in environmental assessment are (Alcamo, 2001):

 

  • Providing a picture of future alternative states of the environment in the absence of additional environmental policies (baseline scenarios).
  • Illustrating how alternative policy pathways can achieve an environmental target
  • Identifying the robustness of environmental policies under different future conditions
  • Raise awareness about different (future) environmental problems and the connection between them
  • Help stakeholders, policymakers and experts to take into account the large time and space scales of a problem
  • Combine qualitative and quantitative information about the future evaluation of an environmental problem

Alternative baseline scenarios can be used to evaluate the consequences of current policies taking into account uncertainties in driving forces, such as economic and socio-cultural developments. Also alternative baseline scenarios can be used to take into account uncertainties about environmental processes occurring in nature and about impacts of environmental conditions on human health. In the same way policy scenarios can be used to evaluate environmental and economic impacts of environmental policies or other policies taking into account uncertainties in e.g. societal driving forces and environmental processes.

Exploratory scenarios can be used when the objective is to explore the consequences of a specified future trend in driving forces, or the consequences of implementing a policy. Anticipatory scenarios can be used when the objective is to investigate the steps leading to a specified end state, such as an environmental target.

Qualitative scenarios analysis can be used when the objective is to stimulate brainstorming about an issue, when many views about the future have to be included or when an idea has to be formed about for example general social and cultural trends. Quantitative scenario analysis can be used for assessments that require data and numbers, for example on the magnitude of air pollutant emissions.
Combinations are also possible, e.g. the "Story-and-Simulation" (SAS) approach, which combines the development of qualitative "storylines" by a group of stakeholders and experts and the use of models to quantify the storylines (Alcamo, 2001).

The principal elements of  typical scenarios used in environmental studies are (adapted from Jansen Schoonhoven and Roschar, 1992 and  Alcamo 2001):

 

  • Description of  the present situation
  • Several alternative views on future developments, e.g. by means of story lines
  • Description of step-wise changes in the future state of society and the environment i.e. trajectories consisting of logical sequences of events that correspond with and are consistent with each view on future developments.
  • Driving forces influencing the step-wise changes
  • Base year
  • Time horizon and time steps

The main methods for in developing scenarios are:

  • Scenario writing (qualitative scenarios): policy exercises
  • Modeling analysis (quantitative scenarios)

The University of Kassel developed a method to combine both qualitative and quantitative approaches: the  SAS is approach as mentioned above. (Alcamo, 2001)

The SAS approach includes the following steps:
1. The scenario team and scenario panel are established
2. The scenario team proposes goals and outline of scenarios
3. The scenario panel revises goals and outline of the scenarios, and constructs zero order draft of storylines
4. Based on the draft story line the scenario team quantifies the driving forces of the scenarios
5. Based on the assigned driving forces , the modelling teams quantify the indicators of the scenarios
6. At the next meeting of the scenario panel , the modelling team report5s on the quantification of the scenarios and the panel revises the storylines
7. Steps 4,5 and 6 are repeated until an acceptable draft of storylines and quantification is achieved.
8. The scenario team and panel revise the scenarios based on results of the general review
9. The final scenarios are published ad distributed.

Sorts and locations of uncertainty addressed
Scenario Analysis typically addresses ignorance, value-ladenness of choices (assumptions) and  "what-if" questions (scenario uncertainty) with regard to both the context of the (environmental) system considered in the assessment and assumptions about the environmental processes involved. Furthermore Scenario Analysis addresses ignorance, value-ladenness of choices  and scenario uncertainty associated with input data and  driving forces used in models.

Strengths and limitations
+ Scenarios are often the only way to deal with the unknown future;
+ Assumptions about future developments are made transparent and documented
+ Gives insight in key factors that determine future developments;
+ Creates awareness on alternative development paths, risks, and opportunities and possibilities for policies or decision-making.
- The analysis is limited to those aspects of reality that can be quantified (quantitative scenarios);
- Difficult to test underlying assumptions (qualitative scenarios);
- Frequently scenarios do not go beyond trend extrapolation (quantitative scenarios) and are surprise-free;
- Frequently models used contain only one view, which will make the outcomes narrow in scope, thus not doing justice to the wish to explore fundamentally different futures.

References
Alcamo J (2001) Scenarios as tools for international environmental assessments. Environmental issues report. Experts corner report. Prospects and Scenarios No.5, European Environment Agency, Copenhagen

Van Der Heijden K (1996) Scenarios: The Art of Strategic Conversation, John Wiley & Sons; ISBN: 0471966398

UNEP (2002) Global Environmental Outlook 3: Past, present and future perspectives, Earthscan. 32