In order to get a good forecast, you have to start with a good question. Each individual question must be specific and falsifiable, and the questions you ask should complement each other and give a deeper understanding of a broader topic or goal. As a result, it isn’t always easy to figure out what these questions should be. 

Additionally, the types of people who consume forecasts don’t always want the same thing. Some are analysts who love getting into the nitty gritty of individual forecast question results. Others are high-level decision makers who think at a big picture level. To serve these different populations with forecasts that are both specific and actionable, the RFI team uses Issue Decomposition, a process developed by Cultivate Labs based on structured analytic techniques used within the U.S. intelligence community.

Issue Decomposition harmonizes two very different approaches to preparing for the future: scenario planning and probabilistic forecasting. Scenario planning involves identifying key uncertainties, reviewing potential scenarios where some combination of uncertainties comes to pass, and then planning potential courses of action for each. Scenario planning can help you make sense of complex problems, but the intrinsic difficulty in preparing for all possible scenarios can make it too hard to act. Probabilistic forecasting, on the other hand, uses models and data to calculate odds and quantify risk for specific scenarios. However, the farther out you try to predict, the less accurate forecasts become. 

Because both approaches have their strengths, Peter Scoblic and Phil Tetlock advocated for combining the two by “developing clusters of questions that give early, forecastable indications of which envisioned future is likely to emerge” in their Foreign Affairs article “A Better Crystal Ball.” A Georgetown think tank and Cultivate partner, the Center for Strategic and Emerging Technologies (CSET), began realizing what Scoblic and Tetlock proposed through their public crowd forecasting site Foretell (evolving into INFER Public and now RFI), which contributed to the development of this decomposition process. You can read more about the origins of Issue Decomposition in this blog post by Cultivate Labs CEO Adam Siegel. 

Issue Decomposition, or simply “decomposition,” is the result of breaking down a strategic issue or question into smaller parts in order to identify specific forecast questions that could help us better understand the future direction of the issue. RFI’s typical decomposition framework depicts the top-down relationship between the strategic issue, its contributing factors and sub-factors, and the resulting forecast questions. 

Once questions have collected forecasts, we can use the decomposition model to synthesize and analyze data from individual forecasts and glean information about how a strategic issue or question might trend. This is recomposition—the process and product of combining forecasts together to provide insight into a broader topic. 

Senior management, data analysts, and other subject matter experts inform our understanding of how different forecasts interact as part of the bigger picture question, and we put all that knowledge and insight together to help drive action. This final recomposition can take many forms, e.g., a dashboard, a summary report, or an index. 

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