Global non-profit, Textile Exchange has launched an updated version of their Preferred Fiber and Materials Matrix (PFMM) tool. This tool, now open-source for the industry, evaluates the sustainability performance of various material categories using 80 qualitative and quantitative measures.
Beth Jensen, Climate+ Impact Director at Textile Exchange, said to the press “We are excited to introduce the initial updates to the Preferred Fiber and Materials Matrix tool. It will offer a comprehensive perspective on impacts, going beyond just LCA data.” The PFMM aims to help both brands and standards systems understand what qualifies as a ‘preferred’ material for ethical manufacturing.
The interactive PFMM tool assesses standards systems across impact areas, including Climate, Water, Chemicals, Land, Resource Use and Waste, Biodiversity, Human Rights, and Animal Welfare. It shows what is covered and what is not within these impact areas, allowing standard system owners to view their performance in a standardised way.
It is notable that the previous version of the tool also covered these impact areas, however the updated version serves a refreshed methodology and has added indicators for Human Rights and Initiative Integrity. The user interface has been updated for improved usability, including separating paired standard systems (such as EU Organic Regulation and Global Organic Textile Standard (GOTS), enabling users to view the performance of each. This also allows users to better understand how standards can be paired, to gain greater coverage of environmental and social practices across supply chain tiers. Along with this, the overall performance score has been removed, encouraging users to focus on the scoring within impact areas.
The next phase of PFMM development will focus on expanding the assessment of standards systems within the cotton material category. Looking ahead to 2024, the goal is to make the tool applicable to a broader range of initiatives, including branded fibres and other types of sustainability programs.
