Uncertainty and Complexity: The Raison d'Etre of Scenarios as Policy Formulation Tools

Policymakers are faced with the complexity and uncertainty of possible future circumstances inherent in a highly dynamic, globalizing world. According to de Jouvenel (2004), policymakers often justify their decisions by claiming they had no other choice, but in truth they no longer had a choice because of a lack of foresight. In addition, politicians themselves are an important source of uncertainty by making changes in the structure of government throughout their term in office (Kelly et al. 2010). Scenarios are commonly prescribed as a tool to avoid constantly being forced to react to emergencies. They help to deal with uncertainty and complexity, and therefore enhance decision performance by supporting the definition of solutions for potential challenges.

Ways to explore the future depending on its uncertainty and complexity

Figure 3.1 Ways to explore the future depending on its uncertainty and complexity

Zurek and Henrichs (2007) use uncertainty and complexity as the main axes to define ways of exploring the future, specifically: (1) how uncertain we are about future developments of key drivers; and (2) how well we understand the complexity of the system and its causalities (see Figure 3.1).

Figure 3.1 helps to identify the type of futures study needed in policy formulation, depending on the degree of uncertainty and complexity of the policy question. Forecasting methods include trend extrapolations or model calculations and might be used to assess the consequences of assumed changes in policy measures, such as a rise in taxes or reduction in the number of immigrants. Speculations are often the best that can be achieved when levels of uncertainty and complexity are both relatively high. Scenarios, on the other hand, lie somewhere in between forecasts and speculations, that is, when the degree of uncertainty and complexity is of an intermediate level. The definition of scenarios used in the Millennium Ecosystem Assessment (MEA 2005) reflects this understanding of a scenario, describing them as plausible and often simplified descriptions of how the future may develop, based on a coherent and internally consistent set of assumptions about key driving forces and relationships. Scenarios therefore have an exploratory character. They could assume changes in external drivers that cannot be directly influenced by policy measures (for example, higher frequency of natural hazards, higher energy prices, and so on), as well as in internal drivers, such as certain policy changes.

We can distinguish three types of scenarios based on their degree of uncertainty and complexity:

1. Those extrapolating current trends and processes, for example, business-as-usual or reference scenarios (so-called prospective or predictive scenarios);

2. Those exploring alternative futures that are plausible, surprising or shocking, for example, scenarios that assume technological breakthroughs or events that impose a security risk (so-called explorative scenarios);

3. Those describing desired, not necessarily expected futures (so-called descriptive or normative scenarios). Visions are an example of normative scenarios.

It is interesting to note that in practice, tensions can occur between forecasters (for example, modellers, economists) and visionary, creative scenario developers who focus on discontinuities and desirable futures, as described by van't Klooster (2007) during the development of spatial planning scenarios.

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