Robust Decision Making (RDM)
(→General Idea) |
|||
| Line 6: | Line 6: | ||
As defined by Dr Dr Alistair Hunt , Robust decision making is “ a methodology which aims to identify adaptation options or strategies which can perform well over a wider range of possible futures. “. (https://econadapt-toolbox.eu/robust-decision-making) sThe particularity of this methods compared to the classic risk management tools, is that the goal is not to find the optimal solution to a problem but to create a robust solution that is satisfactory for a high number of potential futures (“Comparing Robust Decision-Making and Dynamic Adaptive Policy Pathways for model-based decision support under deep uncertainty”). In other terms, RDM doesn’t consist of trying to find the most plausible future and adapt your strategy to it. Instead, the gist of this method is to consider many potential future situations (see next parts for more details) and to assess the solutions regarding all the different scenarios. Then the one which gives the best tradeoff-the most robust is valorize compare to those which are optimal in one situation (https://doi.org/10.1007/978-3-030-05252-2 | As defined by Dr Dr Alistair Hunt , Robust decision making is “ a methodology which aims to identify adaptation options or strategies which can perform well over a wider range of possible futures. “. (https://econadapt-toolbox.eu/robust-decision-making) sThe particularity of this methods compared to the classic risk management tools, is that the goal is not to find the optimal solution to a problem but to create a robust solution that is satisfactory for a high number of potential futures (“Comparing Robust Decision-Making and Dynamic Adaptive Policy Pathways for model-based decision support under deep uncertainty”). In other terms, RDM doesn’t consist of trying to find the most plausible future and adapt your strategy to it. Instead, the gist of this method is to consider many potential future situations (see next parts for more details) and to assess the solutions regarding all the different scenarios. Then the one which gives the best tradeoff-the most robust is valorize compare to those which are optimal in one situation (https://doi.org/10.1007/978-3-030-05252-2 | ||
| + | === When to use it ?=== | ||
| + | As we mentioned it before, one specific point to RDM is to take into account multiple scenarios. This is why it is specifically adapted to the situation with a high level of uncertainties. (Comparing Robust Decision-Making and Dynamic Adaptive Policy Pathways for model-based decision support under deep uncertainty”). Indeed, a high level of uncertainties implies that it is not possible to determine a future situation. It is not even possible to put reliable probabilities or distributions on different scenarios. | ||
=== RDM fondations === | === RDM fondations === | ||
== Application == | == Application == | ||
Revision as of 10:13, 14 February 2022
Abstract: In some situations, decisions on projects or program management must been made under deep uncertainty. In this case, the classic risk management tools are not well adapted. Robust Decision Making (RDM) is one of the solutions which can be used to correctly consider this high level of uncertainty. In contrary of the classic risk management tools, RDM helps decision makers to choose not the optimal solution, but the solution (of set of solutions) which is the less bad regarding the set of possible future. After having briefly presented the history and main principles of RDM, this article aims to give a guideline so that the reader can implement it. This includes a short presentation of different useful tools and a step-by-step methodology. The relevance and limitations of RDM are also discussed at the end.
Contents |
Presentation of the RDM
General Idea
As defined by Dr Dr Alistair Hunt , Robust decision making is “ a methodology which aims to identify adaptation options or strategies which can perform well over a wider range of possible futures. “. (https://econadapt-toolbox.eu/robust-decision-making) sThe particularity of this methods compared to the classic risk management tools, is that the goal is not to find the optimal solution to a problem but to create a robust solution that is satisfactory for a high number of potential futures (“Comparing Robust Decision-Making and Dynamic Adaptive Policy Pathways for model-based decision support under deep uncertainty”). In other terms, RDM doesn’t consist of trying to find the most plausible future and adapt your strategy to it. Instead, the gist of this method is to consider many potential future situations (see next parts for more details) and to assess the solutions regarding all the different scenarios. Then the one which gives the best tradeoff-the most robust is valorize compare to those which are optimal in one situation (https://doi.org/10.1007/978-3-030-05252-2
When to use it ?
As we mentioned it before, one specific point to RDM is to take into account multiple scenarios. This is why it is specifically adapted to the situation with a high level of uncertainties. (Comparing Robust Decision-Making and Dynamic Adaptive Policy Pathways for model-based decision support under deep uncertainty”). Indeed, a high level of uncertainties implies that it is not possible to determine a future situation. It is not even possible to put reliable probabilities or distributions on different scenarios.
RDM fondations
Application
Useful tools
Step by Step methodology
Limitations
References
Sources: https://doi.org/10.1016/j.envsoft.2016.09.017
ISBN 978-3-030-05252-2 (eBook) https://doi.org/10.1007/978-3-030-05252-2
http://eprints.lse.ac.uk/68318/1/Conway_Barriers%20and%20opportunities%20.pdf
