Robust Decision Making

Achieving Tomorrow’s Goals Across an Uncertain Future

How might different short-term actions affect long-term outcomes? With sufficient knowledge and having unknowns well-characterized by probabilities, such decisions over choices are amenable to the tools of analysis. But when information is sparse or unavailable and probability estimates unreliable, these tools may be inoperable or their results misleading. We are then left to weigh alternative stories: “What if..? Suppose that..? Could this..?”. Instead of the rich tool kit of analytical methods for deductive reasoning, what remains are competing, unsystematic narratives.

The individual ability to reason over “What if...?” stories becomes even more challenging when a group (or assembly of groups) tries to reason collectively through complex and uncertain futures. Business and government processes become overburdened when confronted by an environment not imagined by their framers.

Robust Decision Making (RDM) is a method designed to supply the missing machinery for systematic, shareable reasoning and decision making under conditions of deep uncertainty (DMDU). RDM’s rigor comes from using the same models already being used to conduct more traditional analysis. The difference lies in the use of those models. Rather than seeking to enhance the ability to be predictive—unlikely to prove successful under deep uncertainty—RDM supports the systematic construction, testing and selection of short-term actions that will be consistent with long-term goals over many alternative futures. (That is, rather than decisions optimized for planning assumptions that may not anticipate how the future actually unfolds, robust decisions will achieve set threshold for indicators of satisfactory outcomes across a wide range of plausible futures.)

A Primer on RDM

Robust Decision Making is a widely used approach for Decisionmaking Under Deep Uncertainty. Originally developed at RAND, RDM asks “How can we make good decisions without first needing to make predictions?”

RDM focuses stakeholders’ attention on the characteristics of their policy options rather than on predictions of the future. Through an iterative process, stakeholder deliberation informs the kinds of analysis that are needed to answer key questions about the policy problem, and the analysis provides information over which stakeholders deliberate.

As part of the online tool Water Planning for the Uncertain Future, the authors developed an overview of RDM that explains this process.

Read the overview

Developing RDM Methods

RAND has played a leading role in the development of Robust Decision Making, beginning with early research on exploratory modeling, to the first report-length description and application of Robust Decision Making, and subsequent academic journal articles formalizing the method, explaining how it can be applied, and describing key techniques. Below are more recent RAND publications on RDM methods.

Applying RDM to Policy and Decisionmaking

RAND not only works to develop RDM as a methodology, we also apply it to a wide range of disciplines and problems.

Jump to: Decarbonization and climate policy | Water resources planning and climate change adaptation | Coastal resilience planning | Climate risk management and global sustainability | Energy planning | Insurance, finance, and fiscal issues | Stormwater management | Transportation

Decarbonization and Climate Policy

  • The Benefits and Costs of Decarbonizing Costa Rica's Economy

    Costa Rica set the ambitious goal of becoming carbon-neutral by 2050. An evaluation of the benefits and costs of its National Decarbonization Plan, conducted using Robust Decision Making methods, finds that under most plausible assumptions about the future, the plan would achieve or nearly achieve its goals and do so at a net economic benefit.

  • Robust Decision Making: Application to Water Planning and Climate Policy

    Long-term water planning is increasingly challenging, and there are also large uncertainties faced by policymakers addressing global climate change. Methods for Decision Making under Deep Uncertainty (DMDU) can be useful for addressing long-term policy challenges.

Water Resources Planning and Climate Change Adaptation

  • Water Planning for the Uncertain Future

    Through case studies focusing on the Colorado River Basin, Sacramento–San Joaquin River Basin, Pecos River–New Mexico Basin, Metropolitan Water District of Southern California, and Monterrey, Mexico, this interactive tool provides information about decisionmaking under deep uncertainty (DMDU) methods—specifically, Robust Decision Making (RDM).

  • Developing a Robust Water Strategy for Monterrey, Mexico

    Mexico's third-largest metropolitan area, Monterrey, faces future water security challenges as the region grows. Analysis of long-term trends and vulnerabilities in water management shows a robust, adaptive water management strategy can meet current and future needs.

  • Robust Decision Making: Application to Water Planning and Climate Policy

    Long-term water planning is increasingly challenging, and there are also large uncertainties faced by policymakers addressing global climate change. Methods for Decision Making under Deep Uncertainty (DMDU) can be useful for addressing long-term policy challenges.

  • RAND Releases Evaluation of the Jinan City Water Ecological Development Implementation Plan

    The Jinan Municipal Water Resources Bureau, with support from the Shandong Provincial Department of Water Resources, asked RAND to evaluate potential effects of demand and climate uncertainties on investments recently undertaken according to the Jinan City Water Ecological Development Implementation Plan. The RAND research team, led by David Groves and Debra Knopman, also assessed the potential of new investments and management strategies to help Jinan meet its long-term water resources goals.

  • Preparing for Future Droughts in Lima, Peru

    A rapidly growing population and expanding city will likely increase demand for water in Lima, Peru. This study evaluates the city's current drought management plan against future droughts and proposes augmentations.

  • A Strategy for Implementing Lima's Long-Term Water Resources Master Plan

    How can water resource agencies make smart investments to ensure long-term water reliability when the future is fraught with deep climate and economic uncertainty? This study helped SEDAPAL, the water utility serving Lima, Peru, answer this question by drawing on methods for decision making under deep uncertainty.

  • Evaluating Robust Water Management Strategies for the Colorado River Basin

    RAND worked with the U.S. Bureau of Reclamation and Colorado River Basin states to apply innovative robust decision methods to evaluate thousands of plausible futures on the Colorado River and develop and compare strategies to address future vulnerabilities.

  • Robust Water Management Strategies for the Inland Empire Utilities Agency

    As part of a multiyear study on climate-change decisionmaking under uncertainty, RAND researchers worked with water agencies in California to help them better understand how climate change might affect their systems and what actions, if any, they should take to address this challenge.

  • California's Water Challenges

    David Groves discusses an innovative approach to dealing with the many challenges that may contribute to sustainable and affordable solutions of long term water supplies in California.

  • Robust Decisionmaking May Help EPA's National Water Plan Manage Climate and Other Uncertainties

    Maintaining safe and reliable water supplies depends on timely investments in water treatment, storage, and delivery infrastructure. RAND undertook a project for the EPA to determine the utility of Robust Decision Making (RDM) methods for evaluating the agency's needs and priorities.

  • Simplified Planning Under Uncertainty Approaches Can Help Local Water Agencies Plan for Climate Change

    Research demonstrates how Robust Decision Making can help local water agencies include climate change and other uncertain factors in their long-term planning. Application to the El Dorado Irrigation District in California shows key trade-offs among future long-term water management strategies.

  • Using RDM Strategies for the California Water Plan Update

    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.

Coastal Resilience Planning

Climate Risk Management and Global Sustainability

  • Enhancing the Climate Resilience of Africa's Infrastructure

    Working with the World Bank, RAND researchers used robust decision methods to provide the first continent-wide evaluation of the potential effects of climate change on such investments. They also examined the potential impacts of climate change on five specific hydropower and irrigation projects.

  • Planning for Superstorms, Wildfires, and Deep 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.

Energy Planning

  • Measuring Electricity Sector Resilience to Climate-Driven Changes in Hydropower Generation

    Hydropower is expected to play an essential role in improving electricity access in East Africa, but variations in water availability due to a changing climate could leave hydro infrastructure stranded or result in underutilization of available resources. Researchers developed a framework of long-term models for electricity supply and water systems management to assess the vulnerability of potential expansion plans to the effects of climate change.

  • Natural Gas and Israel's Energy Future

    Israel can make natural gas usage a bigger part of its energy portfolio without jeopardizing its security, but even more importantly, the nation needs to make conservation measures a priority in its future energy plans.

Insurance, Finance, and Fiscal Issues

Stormwater Management


  • Meeting Climate, Mobility, and Equity Goals in Transportation Planning Under Wide-Ranging Scenarios

    Prediction-based approaches, the heart of current transportation planning practice, are inadequate for informing transportation decisions in today's rapidly changing conditions. Researchers show how could enhance current long-range planning by applying the approach to selected components of Sacramento Area Council of Government's regional transportation plan.

  • Implementing a New Mobility Vision in a Fast-Changing World

    Culver City's booming local economy contributes to significant traffic congestion. Its Transit Oriented Development (TOD) plan aims to reduce the reliance on cars by reshaping the urban landscape. An implementation plan for the Rancho Higuera neighborhood can help the city realize its TOD vision.

  • Deploying Autonomous Vehicles Before They're Perfect Will Save More Lives

    Autonomous vehicles should only have to be moderately better than human drivers before being widely used in the United States, according to modeling using Robust Decision Making methods. This approach could save thousands of lives annually even before the technology is perfected.