One of the biggest hurdles fashion brands face in their sustainability journey is the sustainability data problem in fashion. Accurate, reliable data collection remains a significant challenge, particularly across supply chains. Brands are bogged down by manual processes, inconsistent data, and the absence of robust technology solutions, creating data gaps in sustainable fashion.
The Challenges of Sustainability Data Collection
Sarah’s Journey Through the Data Maze
Meet Sarah, a sustainability manager at a leading fashion brand. Her mission? Calculate the company’s carbon footprint and set impactful goals to reduce their environmental impact. But Sarah quickly finds herself battling data gaps in sustainable fashion, making the path toward sustainability feel more like a maze of spreadsheets and manual work.
Data challenges in the fashion industry
Tackling Scope 1 and Scope 2 Emissions
The first step for Sarah is managing data for Scope 1 and Scope 2 emissions. This should be the simplest part, yet the information is scattered across departments and systems. Sarah recalls having to dig through invoices, retrieve electricity, gas, and cooling data for over 80 stores, and navigate inconsistencies like stores with utilities included in rent.
The Overwhelming Scope 3 Challenge
Scope 3 emissions, which cover the supply chain, are where the sustainability data problem in fashion becomes most pronounced. Sarah depends on platforms like Higg FEM for supplier data but often finds it riddled with inaccuracies—”units are off by thousands,” she recalls. Scope 3 emissions account for more than 80% of total GHG emissions for fashion brands and require more granular data reporting. You can read more about the challenges specific to Scope 3 emissions in the fashion Industry in our another blog here.
Scope 3 emissions account for the majority of total GHG emissions
Why Data Gaps in Sustainable Fashion Persist
The Supply Chain Data Conundrum
Even when suppliers submit data, Sarah faces long waits, inconsistent formats, and hours of manual validation. One brand representative highlights this ongoing issue, stating, “Data is all over the place and not well-structured”. Another notes, “There’s no standardization or automation, which makes the process exhausting”.
This Vogue article “How to close fashion’s sustainability data gap” further highlights the challenges of luxury brands like Mulberry and Capri Holdings.
The Need for Data-Driven Sustainability
Moving Beyond Spreadsheets
Sarah’s story mirrors the experience of countless fashion brands. The lack of automation, standardization, and actionable insights hinders their ability to measure their true environmental impact and make informed decisions.
Transforming Data into Action
For brands to close the data gaps in sustainable fashion, the industry must shift towards AI/ML technology that automates data collection and ensures accuracy. Robust systems are critical to helping brands move from spreadsheets to actionable intelligence, enabling them to transparently communicate progress to stakeholders.
Conclusion
The sustainability data problem in fashion is a roadblock for brands seeking meaningful change. To create a more sustainable future, the industry must address these challenges with innovative solutions that streamline processes and empower decision-makers like Sarah. By overcoming data gaps in sustainable fashion, brands can accelerate their journey toward transparency and environmental responsibility.
