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Scenarios
Scenario planning is one of the most well-known and most cited as a useful technique for thinking about the future.
Scenario planning questions assumptions we all make about the future. The method creates plausible views of the future that decision-makers can use to determine their best response and how to react to alternative plays.
Scenarios are qualitatively distinct visions, told as stories, of how the future looks. They make explicit the assumptions of how the world works. Building scenarios helps us to:
As the project progresses, the process will move from wide exploration to a narrowing of focus, from horizon scanning to envisioning potential futures and determining response as the diagram above shows.
The key in creating scenarios of best/worst case options is in finding that strategy that represents the best middle ground on which to base subsequent action plans.
Almost all formal scenario planning is done manually in workshop settings and the approaches are usually deductive using quadrant-based models or inductive (determine all of the potential futures that could be problematic or opportunistic, and mix them and match them into commonly-themed groups). Both of these approaches can be very useful and insightful, but are intrinsically limited -- there are only so many possibilities that mere humans can come up with in the limited time and with the limited tools that are typically available.
The most effective way of trying to exhaustively identify futures that could be on particular interest is to do it abductively with technology. Essentially teams identify the specific domain/environment that is of interest (e.g. terrorism, renewable energy, alternative healthcare, etc.) and spend the time to build a systems model -- identifying the major nodes (e.g. market elements, government regulation, social values, manufacturing processes, etc.) and how they contribute/interact with the other nodes, both positively and negatively.
Once the high value/driving nodes within the system are understood, then the technology can be used to exercise/iterate the system through every possible state or future. You end up with hundreds if not thousands of scenarios . . . that can then be rather easily be evaluated to determine which ones are high value and need to be monitored for. Since you understand how the system works and which nodes contribute particularly toward a specific scenario, you now know where to monitor for what kinds of changes that could contribute to that particular scenario.
Next: Analytical Back: Monitoring To: Shaping Tomorrow
Copyright: Some rights reserved. This work is licensed under a Creative Commons License.
Scenario planning questions assumptions we all make about the future. The method creates plausible views of the future that decision-makers can use to determine their best response and how to react to alternative plays.
Scenarios are qualitatively distinct visions, told as stories, of how the future looks. They make explicit the assumptions of how the world works. Building scenarios helps us to:
- Understand the realm of possible options
- Makes us live the future in advance so as we can take better decisions today
- Changes our vision of how the world works
- Generates a common understanding of the real issues
- Lets us test our decisions against a range of possible worlds
- Helps us to deal with complex adaptive environments where the outcome is uncertain
- Identify risks to, and opportunities over a desired time period
- Expose long term challenges for strategies and policies
- Deal with a mix of wide ranging qualitative and quantitative inputs
- Enable assumptions to be made clear and explicit
- Make real the implications of these challenges
- Encourage collaboration
- Support and improve vision and policy making by starting grounded and challenging conversations about choices, trade-offs, and conflicts
- Build capacity among staff in futures work
As the project progresses, the process will move from wide exploration to a narrowing of focus, from horizon scanning to envisioning potential futures and determining response as the diagram above shows.
The key in creating scenarios of best/worst case options is in finding that strategy that represents the best middle ground on which to base subsequent action plans.
Almost all formal scenario planning is done manually in workshop settings and the approaches are usually deductive using quadrant-based models or inductive (determine all of the potential futures that could be problematic or opportunistic, and mix them and match them into commonly-themed groups). Both of these approaches can be very useful and insightful, but are intrinsically limited -- there are only so many possibilities that mere humans can come up with in the limited time and with the limited tools that are typically available.
The most effective way of trying to exhaustively identify futures that could be on particular interest is to do it abductively with technology. Essentially teams identify the specific domain/environment that is of interest (e.g. terrorism, renewable energy, alternative healthcare, etc.) and spend the time to build a systems model -- identifying the major nodes (e.g. market elements, government regulation, social values, manufacturing processes, etc.) and how they contribute/interact with the other nodes, both positively and negatively.
Shaping Tomorrow's toolkit partnered with Parmenides/Eidos(c) is one of several in this arena.
Once the high value/driving nodes within the system are understood, then the technology can be used to exercise/iterate the system through every possible state or future. You end up with hundreds if not thousands of scenarios . . . that can then be rather easily be evaluated to determine which ones are high value and need to be monitored for. Since you understand how the system works and which nodes contribute particularly toward a specific scenario, you now know where to monitor for what kinds of changes that could contribute to that particular scenario.
Next: Analytical Back: Monitoring To: Shaping Tomorrow
Copyright: Some rights reserved. This work is licensed under a Creative Commons License.
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Latest page update: made by thryller
, Jul 20 2009, 2:51 AM EDT
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