Abstract

Life cycle assessment (LCA) reports are commonly used for sustainability documentation, but extracting useful information from them is challenging and requires expert oversight. Designers frequently face technical obstacles and time constraints when interpreting LCA documents. As AI-driven tools become increasingly integrated into design workflows, there is an opportunity to improve access to sustainability data. This study used a mixed-methods approach to develop life cycle design heuristics to help non-LCA experts acquire relevant design knowledge from LCA reports. Developed through in-depth interviews with LCA experts (n = 9), these heuristics revealed five prominent categories of information: (1) scope of analysis, (2) priority components, (3) eco hotspots, (4) key metrics, and (5) design strategies. The utility of these heuristics was tested in a need-finding study with designers (n = 17), who annotated an LCA report using the heuristics. Findings suggest a need for additional support to help designers contextualize quantitative metrics (e.g., carbon footprints) and suggest relevant design strategies. A follow-up reflective interview study with LCA experts gathered feedback on the heuristics. These heuristics offer designers a framework for engaging with sustainability data, supporting product redesign, and a foundation for AI-assisted knowledge extraction to integrate life cycle information into design workflows efficiently.