Relevance Tree Analysis

Relevance tree analysis is a normative forecasting method that decomposes a high-level objective into a hierarchy of sub-objectives, functions, and contributing technologies, and then assigns relevance numbers that quantify how much each branch contributes to its parent. By normalizing these numbers so that the children of every node sum to one and multiplying them down each path, the method produces an overall relevance score for every technology or task at the leaves, which ranks them by their importance to the top objective. Unlike exploratory forecasting, which projects what the future will be, relevance trees work backward from a desired goal — they are 'normative,' starting from where you want to go and identifying what must be developed to get there. Originating in defense and aerospace planning and codified in Glenn and Gordon's Futures Research Methodology, the technique remains a standard tool for research-and-development priority-setting and mission analysis.