Quantitative analysis is often indispensable for making sound policy choices. But when decisionmakers confront today’s conditions of fast-paced, transformative, and even surprising change, they sometimes find that commonly used quantitative methods and tools prove counterproductive or lead them astray. Typically, quantitative analysis provides decisionmakers with information about the future by making predictions. But predictions are often wrong, and relying on them can be dangerous. Moreover, decisionmakers know that predictions are often wrong; this can cause them to discount or ignore the crucial information that quantitative analysis can provide. Fortunately, the combination of new information technology and new insights from the decision sciences now enables innovative ways to support decisions with quantitative analysis. This talk describes how one such approach—Robust Decision Making (RDM)—informs good decisions without requiring confidence in and agreement on predictions and offers examples of its increasing impact in a wide range of policy areas.