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

Published in: Futures & Foresight Science, Volume 1, Issue 3–4, page e22 (September–December 2019). doi: 10.1002/ffo2.22

Posted on RAND.org on April 21, 2020

by Steven W. Popper

Read More

Access further information on this document at Futures & Foresight Science

This article was published outside of RAND. The full text of the article can be found at the link above.

Robust decisionmaking (RDM) is a method for aiding decision making under deep uncertainty that uses models not as predictors but as generators of cases exploring assumptions and outcomes. RDM was intended for use with formal models. However, we show 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. In the absence of formal models, the analysis tests candidate actions against different explicit statements of causal relationships to allow more systematic reasoning over choices and outcomes. Doing so renders assumptions about complex systems explicit, characterizes uncertainties in terms of effect on weighting policy choices rather than as presently unknowable probabilities, provides a venue for planners and evaluators to share findings and insights, and yields explicit expressions of theories of causation (TOC) that themselves act as formal models where none had previously existed. RDM allows important scenarios for decision planning to be generated analytically.This may address for several scenario applications the question of determining important futures and also how scenario results may be used directly to inform policy and operational decisions.

Research conducted by

This report is part of the RAND Corporation external publication series. Many RAND studies are published in peer-reviewed scholarly journals, as chapters in commercial books, or as documents published by other organizations.

The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.