Robust decision making (RDM) is an analytic framework that helps identify potential robust strategies, characterize the vulnerabilities of such strategies, and evaluate trade-offs among them. RDM is being used at RAND to to help decisionmakers in areas such as water resources planning, energy, and coastal resilience — areas often plagued with "deep uncertainty," in which stakeholders do not know or agree on the relationships among actions, consequences, and probabilities.
Research conducted by:
Pardee Center for Longer Range Global Policy;
RDMlab: Robust Decision Making for Good Decisions Without Predictions;
RAND Justice, Infrastructure, and Environment;
Environment, Energy, and Economic Development Program
Featured at RAND
A collaboration among RAND, the Pardee RAND Graduate School, Evolving Logic, and network partners, RDMlab promotes the development and use of Robust Decision Making (RDM) methods for policy and decisionmaking.
The Colorado River Basin Study evaluated the river system's resiliency and compared resource management options. The Robust Decision Making methodology helped to identify vulnerabilities and compare portfolios of options.
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Two key analytic tools can be used to evaluate how coastal protection and restoration decisions made now will play out over time, even given an uncertain future. For example, a community weighing whether to implement a marsh-building project can see how the project fares against different rates of rising sea levels over time.
Two key analytic tools can be used to evaluate how coastal protection and restoration decisions made now will play out over time, even given an uncertain future.
Changing how we make development decisions requires a cultural shift as much as it requires an analytical shift. Methodological innovations like Robust Decision Making can help. By motivating and equipping analysts to manage uncertainty, they can shape how we think about, discuss, and make decisions.
Robust Decision Making showed El Dorado Irrigation District managers the results of key trade-offs among future strategies and how expectations for future vulnerable conditions can guide decisions to augment their long-term plan.
RAND worked with the U.S. Bureau of Reclamation to explore the use of Robust Decision Making in the Bureau's long-term planning for the Colorado River.
Robust Decision Making is used in a wide range of applications, most critically in water and flood risk management.
The Colorado River Basin Study evaluated the river system's resiliency and compared resource management options using the Robust Decision Making methodology.
This report describes a proof-of-concept analysis using Robust Decision Making to evaluate water resource management response packages for California's Central Valley under future uncertainty for the California Water Plan Update 2013.
Scenario discovery offers a new means to characterize and communicate the information in computer simulation models under conditions of deep uncertainty.
A new set of scenarios, referred to as Shared Socio-economic Pathways (SSPs), examines challenges to mitigation and challenges to adaptation. Developing SSPs with a "backwards" approach could help inform the development of SSPs to ensure the storylines focus on the driving forces most relevant to distinguishing between the SSPs.
Many objective robust decision making (MORDM) combines concepts and methods from many objective evolutionary optimization and robust decision making (RDM), along with extensive use of interactive visual analytics, to facilitate the management of complex environmental systems.
The Coastal Louisiana Risk Assessment model (CLARA) facilitates comparisons of current and future flood risk under a variety of protection system configurations in a wide range of environmental, operational, and economic uncertainties.
Limiting climate change will require transformation of energy and other systems. A new model that uses Robust Decision Making tools enables decisionmakers to compare the long-term sustainability of alternative carbon emission reduction policies.
A computer-based decision-support tool, called the Coastal Protection and Restoration Authority (CPRA) Planning Tool, provided technical analysis that supported the development of Louisiana's 2012 Comprehensive Master Plan for a Sustainable Coast through CPRA and community-based deliberations.
Ho Chi Minh City faces significant and growing flood risk. Recent risk reduction efforts may not work if climate and socio-economic conditions diverge from earlier projections. Robust decisionmaking can help Vietnam's capital develop integrated flood risk management strategies despite this uncertainty.
The path to climate change preparedness should start at the intersection of resilience and robustness — that is, building resilient communities with the individuals and organizations within those communities making robust decisions, ones designed to work well over a wide range of ever-changing conditions.
This essay will argue that long-term emissions reduction goals currently proposed before Congress at best only highlight the magnitude of the climate change challenge, without contributing much to a solution.
Quantitative analysis is often indispensable to sound planning, but with deep uncertainty, predictions can lead decisionmakers astray. Robust Decision Making supports good decisions without predictions by testing plans against many futures.