RAND has contributed more to thinking about how to deal with the longer-range future than any other organization. RAND's early methodological work started in the late 1950s and 1960s with the developments of the Delphi method and scenario analysis. This work continued sporadically through the 1970s and 1980s—and since the 1990s—computational technology has enabled new futures methodologies such as Robust Decision Making and Scenario Discovery.

Additionally, many Pardee RAND Graduate School dissertations use and advance long-range methods like exploratory modeling and Robust Decision Making.

RAND is again leading the way in putting these methods to use in dealing with the challenges of the future.

  • How Can AI Help People Become Better Versions of Themselves?

    AI could enable radically different futures in terms of how people live and work, the values and choices people can pursue, and risks they will face. This essay offers an initial exploration of the near-term policy implications of one aspect of this potential for a transformed, AI-enabled future.

    Sep 6, 2023

  • Transportation Planning for Uncertain Times

    Transportation agencies must pursue ambitious goals in the face of intense, large-scale, and increasingly fast-paced change. Through the decision making under conditions of deep uncertainty (DMDU) approach, researchers offer a guide for Metropolitan Planning Organizations to account for and manage future uncertainties as part of their regular transportation planning process.

    Jul 11, 2023

  • Seeking COVID-19 Exit Strategies for Reopening California

    Researchers used simulation models and the Robust Decision Making (RDM) approach to stress-test California's reopening strategy and other alternatives. They found that adaptive plans that respond aggressively to initial outbreaks are required to control the pandemic.

    Apr 27, 2021

  • 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).

    Mar 8, 2021

  • Modeling the Uncertainty of Potential Impacts on Robust Stormwater Management

    Researchers explored the impact of two long-term population growth scenarios for the Pittsburgh region using a method that applies high-spatial resolution population-based scenarios to pre-existing stormwater models.

    Feb 4, 2021

  • 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.

    Nov 24, 2020

  • Managing Heavy Rainfall with Green Infrastructure

    Urban stormwater management is a growing challenge in many U.S. cities. An evaluation of Pittsburgh's Negley Run watershed, an urgent flood-risk challenge, shows investment in green stormwater infrastructure could reduce flooding and provide net positive economic benefits.

    Oct 26, 2020

  • Engaging Multiple Worldviews With Quantitative Decision Support

    Many of today's pressing policy challenges—such as climate change and inequality—are characterized as wicked problems. How might decision making under deep uncertainty be used to demonstrate methods that may help resolve the tension between differing approaches for addressing these problems?

    Aug 25, 2020

  • Robust Decision Making and Scenario Discovery in the Absence of Formal Models

    RDM was intended for use with formal models. This paper shows a model-less RDM application to a portfolio planning problem — selecting U.S. Army security cooperation activities with a partner country — seeking to achieve several objectives.

    Apr 21, 2020

  • Defining the Solution Space to Accelerate Climate Change Adaptation

    Decisionmakers need better insights about solutions to accelerate adaptation efforts. Defining the concept of "solution space" and revealing the forces and strategies that influence this space can help accelerate climate change adaptation.

    Mar 24, 2020

  • 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.

    Feb 11, 2020

  • 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.

    Jan 30, 2020

  • 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.

    Jan 3, 2020

  • Flood Damage Reduction Benefits and Costs in Louisiana's 2017 Coastal Master Plan

    Louisiana's coastwide master plans include substantial investments in coastal restoration and hurricane flood risk reduction over 50 years. Modeling of different future scenarios showed implementing the plans could yield net economic benefit for coastal Louisiana in many plausible future scenarios.

    Oct 23, 2019

  • Sacramento Area Council of Governments Peer Review

    The Southern California Association of Governments held a peer review to promote information exchange in the transportation planning and modeling community. The primary objective of the peer review was to help agencies understand the use of models to better manage uncertainties in long-range planning.

    Sep 25, 2019

  • A World-Building Workshop on the Future of Artificial Intelligence

    How might artificial intelligence (AI) be used to shape a new world? A workshop engaged a group of innovative thinkers in an approach called large-scale speculative design to sketch desirable, AI-enabled future worlds.

    Jun 21, 2019

  • Pathways to 2050: Scenarios for Decarbonizing the U.S. Economy

    Climate change is among the most profound challenges of all time, and the private sector is an essential partner in any decarbonization pathway. Timely business leadership can help ensure choices that are beneficial for both companies and society as a whole.

    Jun 4, 2019

  • Decision Making Under Deep Uncertainty: From Theory to Practice

    This open-access book provides an overview of the different approaches to Decision Making Under Deep Uncertainty (DMDU) and their applications to a range of policy areas.

    Apr 11, 2019

  • Robust Decision Making

    Decisionmakers often seek predictions about the future to inform policy choices. But a reliance upon analytic methods that require them can prove counter-productive and sometimes dangerous in a fast-changing, complex world. Chapter 2 of Decision Making under Deep Uncertainty: From Theory to Practice describes Robust Decision Making.

    Apr 10, 2019

  • 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.

    Apr 10, 2019