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| future_fabulators:scenario_methods [2014-02-21 07:02] – maja | future_fabulators:scenario_methods [2014-02-21 07:33] – [Scenario Methods] maja | ||
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| ===== Scenario Methods ===== | ===== Scenario Methods ===== | ||
| - | This page is an evolving, non-exhaustive collection of different methods and techniques that can be used in scenario building, particularly focusing on the ones that might be useful for Future Fabulators. There are many academic papers and consultants' | + | This page is an evolving, non-exhaustive collection of different methods and techniques that can be used in scenario building, particularly focusing on the ones that might be useful for Future Fabulators. There are many academic papers and consultants' |
| - | 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 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 |
| ==== Methods, comparisons ==== | ==== Methods, comparisons ==== | ||
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| * success criteria (what will make my question succeed or fail) | * success criteria (what will make my question succeed or fail) | ||
| - | ==== Change Drivers ==== | + | ==== Change Drivers |
| * how much analysis is appropriate for the types of scenarios and prehearsals we’re making? | * how much analysis is appropriate for the types of scenarios and prehearsals we’re making? | ||
| * how can we make assumptions and guesswork more apparent (i.e. indicating how drivers can be based on an assumption, guess or ' | * how can we make assumptions and guesswork more apparent (i.e. indicating how drivers can be based on an assumption, guess or ' | ||
| - | * what is the relevance of facts and data related to macro trends | + | * what is the relevance of facts and data related to drivers of change |
| - | * how can we have a more constructive discussion about the macro trends which results in something more meaningful than a list of assumptions? | + | * can we have a more constructive discussion about the macro trends which results in something more meaningful than a list of assumptions (without too much expert analysis needed beforehand)? |
| - | * how do we look at drivers as dynamic forces? should we be looking at responses to trends rather than trends in general? | + | |
| - | //What are existing ways of discussing | + | //How do we look at drivers as dynamic forces? should we be looking at responses to trends rather than trends |
| - | * See various methods on the [[horizon scanning]] page | + | (nouns -> verbs) |
| + | |||
| + | | ||
| + | * [[https:// | ||
| + | * [[www.cgee.org.br%2Fatividades%2FredirKori%2F3302& | ||
| + | * MA/FAR (see below) | ||
| - | * should we make our own STEEP (or related) cards to avoid the ' | + | // should we make our own STEEP (or related) cards to avoid the ' |
| * are there other well understood methods to group trends other than the customary STEEP (in which cultural changes seem to be clumped in with social or political)? see [[horizon scanning]] and [[http:// | * are there other well understood methods to group trends other than the customary STEEP (in which cultural changes seem to be clumped in with social or political)? see [[horizon scanning]] and [[http:// | ||
| //Is there another way to look at large scale changes aside from trends (without having to do a PhD in each of the changes)?// | //Is there another way to look at large scale changes aside from trends (without having to do a PhD in each of the changes)?// | ||
| - | (the Manoa approach | + | * weak signals, emerging issues, historical analogues |
| + | * the Manoa approach | ||
| - | * how effective are these methods and how can we usefully | + | // How effective are these methods and how can we usefully |
| + | |||
| + | It seems to be a big academic issue (see thesis by Mihaela Ghisa) | ||
| ==== Ranking critical uncertainties ==== | ==== Ranking critical uncertainties ==== | ||
| + | |||
| + | (this is relevant only for the 2x2 scenario method. other methods use more axes (but are equally vague about how to select them) | ||
| * what are different ways in which this is done by others? most approaches i could find use numbers, or conversation. | * what are different ways in which this is done by others? most approaches i could find use numbers, or conversation. | ||
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| * __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:// | ||
| + | * CLA: probing deeper cultural foundations of core issues | ||
| + | * Manoa approach: "the scenarios it produces are generally much longer-term, | ||
| + | * Harman Fan: " | ||
| + | * etc (see in methods above) | ||
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| * [[https:// | * [[https:// | ||
| * "a day in the life of..." (a character in a scenario, or one character in different scenarios) | * "a day in the life of..." (a character in a scenario, or one character in different scenarios) | ||
| + | * ... | ||
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| * How can we follow-up what happens to the groups after we finish the workshops (especially to understand what happens to commitments to actions and preferred possible futures)? | * How can we follow-up what happens to the groups after we finish the workshops (especially to understand what happens to commitments to actions and preferred possible futures)? | ||
| * How much do we need to be involved in the follow-up? | * How much do we need to be involved in the follow-up? | ||
| + | |||
| + | It all depends on the purpose of the workshop... | ||
nik