We set out to revisit and further develop methods for assessing the economic value of weather, water and climate forecasts to evaluate value of ESP products envisioned by the OSTP Fast Track Action Committee on Earth System Predictability Research and Development and the NASEM Committee on Advancing a Systems Approach to Studying the Earth: A Strategy for the National Science Foundation. Physical science advancements are improving predictability, increasing forecast value, but work is also needed to improve usability of improved ESP. While forecast skill is obviously important to its value, so is the risk/reward structure of the weather- or climate-sensitive decision. Argument: Current weather, water and climate predictions are already underutilized by decision makers. ESP advances can be improved by advancing decision support. This is especially true for probabilistic predictions and multi-model ensemble output, which convey information that can be difficult for decision makers, from farmers to highway snow and ice managers, to ingest into their Decision Structures. Decision structures are not all idiosyncratic—with classes that can be defined and matched with ESP types: • Short-term, short-fuse decisions (e.g., road de-icing) • Multi-day choices with thresholds (e.g., hurricane evacuation, river flood preparations) • Cumulative & predicted seasonal conditions (cattle grazing; drought water supply management) • Annual to decadal decisions (decision to switch cropping systems) We developed initial decision support systems for each of these classes, and report two cases here: cattle grazing (seasonal scale) and crop switching (annual to decadal) applying decision analysis, probabilistic arrival times, decision thresholds, and decision recipes tuned to the relevant ESP structure.