Google’s new pilot aiming to measure the environmental impact of the fashion industry
Nick Martin
Head of Retail, UKI, Google Cloud
Now more than ever, the fashion industry is heeding the call to sustainability. Its environmental impact is significant and growing—among other statistics, the fashion industry accounts for 20 percent of wastewater and 10 percent of carbon emissions globally.
Much of this impact occurs at the raw materials stage in the production process, where brands have little to no visibility. This is an industry wide problem, where supply chains are highly fragmented and with little transparency. Many organizations and brands have been trailblazers in an effort to collect and surface data that can lead to better sourcing decisions, but gaps in the data continue to persist due to its complexity and global nature.
After working with Current Global, an innovation consultancy that empowers fashion brands to reach their sustainability goals through the use of relevant technologies, we determined that Google could help be part of the solution through the use of cloud-based tools for data collection and analysis. Today at the Copenhagen Fashion Summit, one of the fashion industry's key sustainability events of the year, we’re announcing an experiment to do exactly that.
To bring our experiment to life, we’ll be collaborating closely with Stella McCartney. This brand has been a pioneer in leading the fashion industry towards sustainability, helping to launch the UN Fashion Industry Charter for climate change and recently introducing Stella McCartney Cares Green, one of the arms of the Stella McCartney Foundation, to further promote sustainability and environmental protection. By working together through this pilot project, we hope to translate data into meaningful insights so the industry can take action.
“At Stella McCartney we have been continuously focusing on looking at responsible and sustainable ways to conduct ourselves in fashion, it is at the heart of what we do. We are trying our best –we aren’t perfect, but we are opening a conversation that hasn’t really been had in the history of fashion.” Stella McCartney.
To start, we’ll be building a tool that uses data analytics and machine learning on Google Cloud to give brands a more comprehensive view into their supply chain, particularly at the level of raw material production, referred to in the industry as Tier 4 of the supply chain.
We’ll be looking initially at cotton and viscose, each chosen due to the scale of their production, data availability and impact considerations. More specifically, cotton accounts for 25 percent of all fibers used by the fashion industry, with a notable impact on water and pesticide use. Viscose production is smaller but growing in demand, and has links to the destruction of forests—some endangered—which are critical in mitigating carbon emissions. This pilot will enable us to test the effectiveness of the tool on these different raw materials, building out the possibilities for expansion into a wider variety of key textiles in the market down the line.
We plan to include data sources that allow companies to better measure the impact of their raw materials, relevant to key environmental factors such as air pollution, greenhouse gas emissions, land use and water scarcity. Our goal is not only to be able to determine the impact of producing these raw materials, but also compare the impacts of these in different regions where they are produced.
This is the first phase of our experiment. We are actively working with fashion brands, experts, NGOs and industry bodies with the ambition of creating an open industry-wide tool, and plan to continue driving collaboration with other key players—large and small. We hope that our experiment will give fashion brands greater visibility of impact within their supply chain and actionable insights to make better raw material sourcing decisions with sustainability in mind.
For more information on Google Sustainability projects see here and for more information on Google Cloud for retail see here.