Measuring What Matters: LCA and Data Quality in Fashion

The transition from voluntary sustainability communication to regulatory compliance is reshaping how Life Cycle Assessment (LCA) is applied within the fashion industry. This presentation examines how data quality, functional definition, and contextual adaptation determine the reliability and comparability of LCA results in a sector characterised by fragmented supply chains, heterogeneous materials, and evolving policy frameworks. A three-axis model is proposed: LCA Data Quality (primary data availability, representativeness, verification), Functional Precision (well-defined product functions and intermediate performance metrics such as durability, repairability, and recyclability), and Contextual Adaptation (fit-for-purpose modelling from screening to verified compliance LCA). Within this framework, attributional, interaction-based, and system LCA are compared for operational relevance, highlighting trade-offs between precision, scalability, and decision-making value across design, supply chain, and market phases. The talk concludes that “measuring what matters” requires aligning methodological choices with intended use—early design guidance, consumer communication, or legal substantiation—to avoid misleading comparisons and support informed innovation in materials, circularity, and business models.