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future_fabulators:scenario_methods [2014-03-01 05:29] – [Scenarios] maja | future_fabulators:scenario_methods [2014-03-03 04:49] – [Scenario Methods] maja | ||
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There are many different variations of scenario building flow, and we won't attempt to collect them all. Our filter is looking at approaches that can help us move from forecasting to embodiment, from story to experience. As in Ffab we are primarily focused on creating (immersive) situations where possible futures / parallel histories or presents can be physically experienced (and then reflecting on how this experience can affect our present behaviours), | There are many different variations of scenario building flow, and we won't attempt to collect them all. Our filter is looking at approaches that can help us move from forecasting to embodiment, from story to experience. As in Ffab we are primarily focused on creating (immersive) situations where possible futures / parallel histories or presents can be physically experienced (and then reflecting on how this experience can affect our present behaviours), | ||
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==== Methods, comparisons ==== | ==== Methods, comparisons ==== | ||
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==== Scenarios ==== | ==== Scenarios ==== | ||
- | //When to use one, two, three or more axes// | + | //How to construct alternative future scenarios// |
* __Two axes method__: Scenarios generated using the ‘two axes’ process are illustrative rather than predictive; they tend to be high-level (although additional layers of detail can subsequently be added). They are particularly suited to testing medium to long-term policy direction, by ensuring that it is robust in a range of environments. Scenarios developed using this method tend to look out 10-20 years.[[http:// | * __Two axes method__: Scenarios generated using the ‘two axes’ process are illustrative rather than predictive; they tend to be high-level (although additional layers of detail can subsequently be added). They are particularly suited to testing medium to long-term policy direction, by ensuring that it is robust in a range of environments. Scenarios developed using this method tend to look out 10-20 years.[[http:// | ||
* __Branch analysis method__: The ‘branch analysis’ method is suited to developing scenarios around specific turning-points that are known in advance (e.g. elections, a referendum or peace process). This approach works best for a shorter time horizon: generally up to five years.[[http:// | * __Branch analysis method__: The ‘branch analysis’ method is suited to developing scenarios around specific turning-points that are known in advance (e.g. elections, a referendum or peace process). This approach works best for a shorter time horizon: generally up to five years.[[http:// | ||
* __Cone of plausibility__ method: offers a more deterministic model of the way in which drivers lead to outcomes, by explicitly listing assumptions and how these might change. Of the three techniques, this approach is most suitable for shorter-term time horizons (e.g. a few months to 2-3 years), but can be used to explore longer-term time horizons. It also suits contexts with a limited number of important drivers.[[http:// | * __Cone of plausibility__ method: offers a more deterministic model of the way in which drivers lead to outcomes, by explicitly listing assumptions and how these might change. Of the three techniques, this approach is most suitable for shorter-term time horizons (e.g. a few months to 2-3 years), but can be used to explore longer-term time horizons. It also suits contexts with a limited number of important drivers.[[http:// | ||
+ | * [[four generic futures]] by the Manoa School | ||
* CLA: probing deeper cultural foundations of core issues | * CLA: probing deeper cultural foundations of core issues | ||
* Manoa approach: "the scenarios it produces are generally much longer-term, | * Manoa approach: "the scenarios it produces are generally much longer-term, |