Designing scenarios to guide robust decisions

By Bonnie McBain

What makes scenarios useful to decision makers in effectively planning for the future? Here I discuss three aspects of scenarios:

• goals;
• design; and,
• use and defensibility.

Goals of scenarios

Since predicting the future is not possible, it’s important to know that scenarios are not predictions. Instead, scenarios stimulate thinking and conversations about possible futures.

Key goals and purposes of scenarios can be any of the following:

• inform and educate;
• allow us to determine what our goals are;
• help us investigate our assumptions;
• highlight important processes and decision points;
• engage different stakeholders;
• provide insight into what is possible;
• provide visions of the future which motivate actions toward a desirable goal or away from an undesirable one;
• show where differences between stakeholder priorities or worldviews lie in order to analyse potential areas of conflict between them;
• communicate complex information to non-scientific audiences;
• make infinite potential options for the future more manageable; and,
• explore the adaptability of policy.

While scenarios will not resolve uncertainties, exploring uncertainty is a pivotal aspect of the exercise, as is helping decision-makers make better decisions in the face of uncertainty.

Designing scenarios

Scenarios can have qualitative or quantitative aspects or both. A common approach is to combine a descriptive story line with numerical modelling.

Story lines are particularly useful for aspects of the scenario for which something is not quantifiable or there is insufficient data to quantify it with the required accuracy. For instance, story lines allow social, cultural and institutional factors to be addressed explicitly, even if current knowledge does not allow these uncertain factors to be treated in a quantitative way.

Development of qualitative storylines typically involves stakeholder engagement to negotiate plausible futures that are coherent and internally consistent. This process could involve a formal or informal dialogue (workshops, interviews, surveys, etc) involving both experts and stakeholders.

Quantitative scientific modelling is often used to examine different assumptions or actions, such as the consequences of a single course of action under different key assumed uncertainties or the outcomes resulting from different policy actions.

Development of the qualitative and quantitative aspects of scenarios can happen concurrently and will then be iteratively refined in response to each other.

In general, the following iterative development process is used:

• identifying the main driving forces affecting the state of a system;
• determining the current state;
• identifying the critical uncertainties;
• making assumption about how uncertainties will evolve;
• identifying options for mitigation; and,
• analysing the implications.

Scenario exercises can be exploratory or normative. Exploratory scenarios contrast one or more baseline scenarios with one or more policy scenarios that consider the role of deliberate human actions and choices in shaping the future. Baseline scenarios reflect uncertainty (for example of driving forces or other parameters), so that there can be more than one baseline covering different aspects of uncertainty. Normative scenarios, on the other hand, develop stories about preferred futures. They provide a vision of a transition to a desired or alternate future.

Despite the almost infinite range of possible futures that they could consider, scenarios should be limited in number. For exploratory scenarios, an even number of baseline scenarios is better than an uneven number, in order to prevent the decision-maker from settling for a ‘middle ground’. Four baseline scenarios are better than two, in order to avoid the decision-maker interpreting two scenarios as ‘extremes’. The appropriate use of scenarios refrains from ‘picking’ any particular chain of events, but rather focuses on how a range of scenarios describes the most important uncertainties at stake.

Although limited in number, scenarios should also be diverse and represent a range of future visions, values and world-views. There are, in general, more policy than baseline scenarios, however, the number of policy scenarios must be kept manageable in order to avoid scenario fatigue.

It is also an advantage if scenarios can incorporate surprises, although this may not be fully possible as baseline scenarios are ideally of limited number. Surprises can be positive or negative and include events such as a world war, ‘miracle’ technologies, an extreme natural disaster, a pandemic or a breakdown of the climate system. Plausible, yet unexpected, occurrences incorporated into scenario building exercises can help decision makers recognise the need for adaptive management strategies that can flexibly deal with surprises.

Scenarios should also span long time horizons of at least several decades to allow adequate consideration of slow, incremental change, the full consequences of which are only felt in a distant future.

Scenarios must have the ability to communicate options and outcomes clearly to a range of different stakeholders affected by them. The story line aspects of scenarios means that they can be used to communicate complex information to non-scientific audiences in an exciting and clear way.

Producing useful and defensible scenarios

In order to be useful for decision makers, scenarios must be:

• plausible, integrated, coherent and internally consistent;
• analytically sound with regard to use of data and scientific theory;
• able to incorporate the global scale as well as to be disaggregated to a regional and, ultimately, sub-regional scale;
• able to consider environmental drivers along with the socio-ecological system. This makes scenario development more complicated and requires a broader base of expertise to ensure that scenarios have an internally consistent set of assumptions about key relationships and driving forces from a social, economic and environmental point of view.

For scenarios to be defensible, they must also be transparent and well documented. This ensures:

• understanding of the reasoning behind the scenarios and the assumptions made;
• informed criticism and further improvement by identifying any bias in scenario production and focusing subsequent argument on underlying uncertainties; and,
• informing potential users of appropriate conditions under which scenarios might be used, not used or modified.

Conclusion

What has your experience been in using and producing scenarios? Is it in line with the suggestions above? Are there points you disagree with or do you have additional issues to add?

This blog post is a modified version of three previously published blog posts, which contain multiple links and references:

1. Scenarios – creating alternate futures when we just don’t know: [Moderator update – In April 2023, this link was no longer available and so the link structure has been left in place but the active link deleted: uonblogs[dot]newcastle[dot]edu[dot]au/herdingthegreenchicken/2017/05/16/scenarios-creating-alternate-futures-just-dont-know/]
2. Scenarios – what form do they take? [Moderator update – In April 2023, this link was no longer available and so the link structure has been left in place but the active link deleted: uonblogs[dot]newcastle[dot]edu[dot]au/herdingthegreenchicken/2017/06/05/scenarios-form-take/]
3. Scenarios – guiding robust decisions if they’re well designed: [Moderator update – In April 2023, this link was no longer available and so the link structure has been left in place but the active link deleted: uonblogs[dot]newcastle[dot]edu[dot]au/herdingthegreenchicken/2017/06/05/scenarios-guiding-robust-decisions-theyre-well-designed/]

Biography: Bonnie McBain PhD is a senior lecturer at the University of Newcastle, Australia. She has research and teaching interests that focus on sustainability. In particular, she is interested to discover how the theories of complexity and resilience can inform action towards a more sustainable future. She has extensive experience in community engagement both within the university sector and in state government. She researches ecological footprint policy development having developed a global ecological footprint model that is used to explore the effectiveness of future policy scenarios. She also has a research interest in learning for sustainability. She is extensively engaged in community change projects. Bonnie shares her expertise in a blog called [Moderator update – In April 2023, this blog was no longer available] Herding the Green Chicken, in The Conversation, via Twitter @TheGreenChook, via LinkedIn, and on YouTube.