Robust Decision Making: better decisions under uncertainty
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= Abstract = | = Abstract = | ||
| − | Robust Decision Making (RDM) | + | Robust Decision Making (RDM) is a computational framework integrating Decision Analysis, Assumption-Based Planning, Scenario Analysis, and Exploratory Modelling. This article critically reviews RDM, its principles, and applications in project management. The article suggests that RDM enables project managers to effectively address uncertainty, offering a powerful analytical framework. |
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= Conceptualising Robust Decision Making at times of Uncertainty= | = Conceptualising Robust Decision Making at times of Uncertainty= | ||
| − | == Origins == | + | == Origins and Functions == |
| − | Robust Decision Making (RDM) emerged in the 1980s, when analysts of the RAND Corporation, a California-based think tank affiliated with the U.S. Government, developed a framework to evaluate the effectiveness of nuclear weapon systems <ref name= | + | Robust Decision Making (RDM) emerged in the 1980s, when analysts of the RAND Corporation, a California-based think tank affiliated with the U.S. Government, developed a framework to evaluate the effectiveness of nuclear weapon systems <ref name=”RAND corp”/> <ref name=”Lempert RDM”/>. Designed to mitigate the uncertainty and ambiguity experienced by U.S. Government officials involved in the planning and implementation of nuclear deterrence strategies, RDM included simulation techniques, sensitivity analysis, and real options analysis. In the 1990s and 2000s, RDM received increasing interest from private companies interested in exploring new project management techniques applicable to a wide range of industries, including construction, software development, and environmental management. Today, RDM is an established approach in project management, recognized for its ability to help project managers making well-informed and timely decisions under pressure and at times of uncertainly. |
| − | + | According to former United States Secretary of Defence Donald Rumsfeld, there are different types of knowledge: known knowns, known unknowns, and unknown unknowns. Known knowns refer to things that we know for sure. Known unknowns refer to things that we know we do not know. However, the most challenging category is the unknown unknowns, which refers to things that we do not know we do not know <ref name="Rumsfeld"/> <ref name="Defence">. The decision-making process in situations affected by a great level of uncertainty is defined as ''decision making under deep uncertainty'' (DMDU) <ref name="Lempert RDM"/>. | |
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| − | According to former United States Secretary of Defence Donald Rumsfeld, there are different types of knowledge: known knowns, known unknowns, and unknown unknowns. Known knowns refer to things that we know for sure. Known unknowns refer to things that we know we do not know. However, the most challenging category is the unknown unknowns, which refers to things that we do not know we do not know <ref name="Rumsfeld"/> <ref name="Defence" | + | |
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| − | + | Robustness is a crucial aspect of effective DMDU <ref name="Rosenhead 1972"/> <ref name="Metz 2001"/>. Conventional decision-analytic techniques for risk and decision analysis are designed to identify optimal strategies based on a characterization of uncertainty that follows the axioms of probability theory <ref name="Morgan 1990"/>. However, in scenarios where there is uncertainty about the system model or the distributions of its inputs, traditional decision-analytic approaches often utilize sensitivity analyses to assess the dependence of the optimum strategy on the specification of model and distributions <ref name="Saltelli 2000"/>. While this approach may be suitable when the optimum strategy is relatively insensitive to these key assumptions, it can pose both conceptual and practical challenges when this is not the case. RDM is part of a new breed of computational, multi-scenario simulation approaches that integrates ideas from scenario-based planning into a quantitative framework <ref name="Morgan et al. 1999"/> <ref name="van Asselt 2000"/> <ref name="Metz 2001"/> <ref name=" Nakicenovic 2000"/>. It inverts traditional sensitivity analysis by seeking optimization strategies which good performance is insensitive to the most significant uncertainties. Beginning with one or more system models that link optimization strategies to outcomes and a collection of several plausible probability distributions over the uncertain input parameters to these models, RDM describes uncertainty with various, plausible perspectives of the future <ref name=" Lempert et al. 2006"/>. RDM suggests robust strategies, identifies vulnerabilities, and suggests new or modified strategies. | |
== Foundations of Robust Decision Making == | == Foundations of Robust Decision Making == | ||
| − | RDM | + | RDM combines four crucial concepts - Decision Analysis, Assumption-Based Planning, scenarios, and Exploratory Modelling - to provide evidence-based analysis that informs choices. This approach empowers decision-makers to navigate uncertainty, assess vulnerabilities, and identify robust strategies that can withstand potential futures. |
'''Decision Analysis (DA)''' | '''Decision Analysis (DA)''' | ||
Revision as of 10:52, 2 May 2023
Abstract
Robust Decision Making (RDM) is a computational framework integrating Decision Analysis, Assumption-Based Planning, Scenario Analysis, and Exploratory Modelling. This article critically reviews RDM, its principles, and applications in project management. The article suggests that RDM enables project managers to effectively address uncertainty, offering a powerful analytical framework.
Conceptualising Robust Decision Making at times of Uncertainty
Origins and Functions
Robust Decision Making (RDM) emerged in the 1980s, when analysts of the RAND Corporation, a California-based think tank affiliated with the U.S. Government, developed a framework to evaluate the effectiveness of nuclear weapon systems Cite error: Invalid <ref> tag;
refs with no content must have a name Cite error: Invalid <ref> tag;
refs with no content must have a name. Designed to mitigate the uncertainty and ambiguity experienced by U.S. Government officials involved in the planning and implementation of nuclear deterrence strategies, RDM included simulation techniques, sensitivity analysis, and real options analysis. In the 1990s and 2000s, RDM received increasing interest from private companies interested in exploring new project management techniques applicable to a wide range of industries, including construction, software development, and environmental management. Today, RDM is an established approach in project management, recognized for its ability to help project managers making well-informed and timely decisions under pressure and at times of uncertainly.
According to former United States Secretary of Defence Donald Rumsfeld, there are different types of knowledge: known knowns, known unknowns, and unknown unknowns. Known knowns refer to things that we know for sure. Known unknowns refer to things that we know we do not know. However, the most challenging category is the unknown unknowns, which refers to things that we do not know we do not know [1] Cite error: Closing </ref> missing for <ref> tag
Cite error:
<ref> tags exist, but no <references/> tag was found
