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== Abstract == | == Abstract == | ||
− | '''Robust decision-making (RDM)''', is a new and innovative methodology in the science of decision support. The RDM framework is a key tool in decision-making processes under deep uncertainty and provides decision-makers with a method to make a plan for the future without having to predict it. When decision-makers have to make long-term decisions they're often called upon to anticipate future needs, resources and circumstances. The problem is that decisions made on predictions are less reliable the farther the prediction reach forward in time, as time entails the prediction to become more vulnerable to uncertainty. This uncertainty could e.g. be unforeseen economic crashes terrorism attacks, political instability, climate change, chains of actions or reactions leading to more possible outcomes than a single prediction can handle. In order to handle a large amount of possible futures, RDM uses computer simulations and advanced modelling techniques to stress-test strategies not only against one predicted future but against thousands or millions of possible futures[https://link.springer.com/chapter/10.1007/978-3-030-05252-2_2]. Thus the RDM framework is used for [[Decision Making under Deep Uncertainty (DMDU)]] [https://link.springer.com/referenceworkentry/10.1007%2F978-1-4419-1153-7_1140]. The main purpose of RDM is not to make a better prediction but through its concepts and processes to contribute with knowledge for the decision-maker to be able to design more robust strategies, that perform no matter what the future holds. | + | '''Robust decision-making (RDM)''', is a new and innovative methodology in the science of decision support. The RDM framework is a key tool in decision-making processes under deep uncertainty and provides decision-makers with a method to make a plan for the future without having to predict it. When decision-makers have to make long-term decisions they're often called upon to anticipate future needs, resources and circumstances. The problem is that decisions made on predictions are less reliable the farther the prediction reach forward in time, as time entails the prediction to become more vulnerable to uncertainty. This uncertainty could e.g. be unforeseen economic crashes terrorism attacks, political instability, climate change, chains of actions or reactions leading to more possible outcomes than a single prediction can handle. In order to handle a large amount of possible futures, RDM uses computer simulations and advanced modelling techniques to stress-test strategies not only against one predicted future but against thousands or millions of possible futures[https://link.springer.com/chapter/10.1007/978-3-030-05252-2_2]. Thus the RDM framework is used for [[Decision Making under Deep Uncertainty (DMDU)]] [https://link.springer.com/referenceworkentry/10.1007%2F978-1-4419-1153-7_1140]. The main purpose of RDM is not to make a better prediction but through its concepts and processes to contribute with knowledge for the decision-maker to be able to design more robust strategies, that perform no matter what the future holds. |
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+ | This paper will go more in-depth with the history of RDM, how it is implemented, as well as its limitations. | ||
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+ | This paper aims to explain SMART goals to other project participants, thereby enabling them to apply it to their projects, enhancing these. Therefore, is the paper initiated by a brief explanation of goal setting theory as it is the foundation on which SMART goals build upon. Thereafter, follows an in-depth explanation of the SMART goals, where I will describe SMART goals and its purpose. Hereafter will a guide on how to use the framework be presented. It will be utilized on a practical example—thereby showcasing how to utilize the outlined approach, the applicability of SMART goals, and the benefits of its usage. The paper ends with a critical reflection and investigation on SMART goals and its limitation. Here, I will provide the reader with the most profound limitations and criticism of SMART goals, to enable the reader to know both pros and cons of the framework. | ||
== Big idea == | == Big idea == |
Revision as of 12:42, 14 February 2021
Contents |
Abstract
Robust decision-making (RDM), is a new and innovative methodology in the science of decision support. The RDM framework is a key tool in decision-making processes under deep uncertainty and provides decision-makers with a method to make a plan for the future without having to predict it. When decision-makers have to make long-term decisions they're often called upon to anticipate future needs, resources and circumstances. The problem is that decisions made on predictions are less reliable the farther the prediction reach forward in time, as time entails the prediction to become more vulnerable to uncertainty. This uncertainty could e.g. be unforeseen economic crashes terrorism attacks, political instability, climate change, chains of actions or reactions leading to more possible outcomes than a single prediction can handle. In order to handle a large amount of possible futures, RDM uses computer simulations and advanced modelling techniques to stress-test strategies not only against one predicted future but against thousands or millions of possible futures[1]. Thus the RDM framework is used for Decision Making under Deep Uncertainty (DMDU) [2]. The main purpose of RDM is not to make a better prediction but through its concepts and processes to contribute with knowledge for the decision-maker to be able to design more robust strategies, that perform no matter what the future holds.
This paper will go more in-depth with the history of RDM, how it is implemented, as well as its limitations.
This paper aims to explain SMART goals to other project participants, thereby enabling them to apply it to their projects, enhancing these. Therefore, is the paper initiated by a brief explanation of goal setting theory as it is the foundation on which SMART goals build upon. Thereafter, follows an in-depth explanation of the SMART goals, where I will describe SMART goals and its purpose. Hereafter will a guide on how to use the framework be presented. It will be utilized on a practical example—thereby showcasing how to utilize the outlined approach, the applicability of SMART goals, and the benefits of its usage. The paper ends with a critical reflection and investigation on SMART goals and its limitation. Here, I will provide the reader with the most profound limitations and criticism of SMART goals, to enable the reader to know both pros and cons of the framework.
Big idea
Describe the tool, concept or theory and explain its purpose. The section should reflect the current state of the art on the topic
Application
Provide guidance on how to use the tool, concept or theory and when it is applicable
Limitations
Critically reflect on the tool/concept/theory. When possible, substantiate your claims with literature
Annotated bibliography
Provide key references (3-10), where a reader can find additional information on the subject.
https://link.springer.com/chapter/10.1007/978-3-030-05252-2_2 - Decision Making Under Deep Uncertainty: From Theory to Practice
https://findit.dtu.dk/en/catalog/2281533929 - 7.2.1 Robust Decision Making
https://www.tandfonline.com/doi/abs/10.1080/09544820010031580 - Robust decision-making for engineering design
https://link.springer.com/referenceworkentry/10.1007%2F978-1-4419-1153-7_1140 - Deep Uncertainty