Best-selling author Bernard Marr recently wrote an article for Forbes on the 5 ESG Trends That Will Shape Business In 2026. His central message is that successful companies see the business value of delivering on their ESG commitments despite the recent back-peddling on ESG requirements globally.
In a nutshell, Marr argues that “businesses will need to back up their claims with data if they don’t want to risk penalties, lawsuits and, most damagingly of all, catastrophic loss of customer trust.”
Marr is not alone in putting an emphasis on ESG data in 2026. The Institute of Sustainability Studies (ISS) predicts that “as expectations around transparency and accountability grow, companies will face pressure to move beyond vague targets and produce high-quality, decision-grade ESG data.”
In an interview with Vogue, Jody Plows, CEO of British womenswear brand Nobody’s Child shines a light on the challenge of accumulating ESG data. She states that ESG compliance requires “about 110 data points per product.” She adds that “suppliers aren’t used to sharing this level of detail. We’re asking them for everything from fiber origins to energy sources. It’s a massive mindset shift.”
Do you really need that many ESG data points?
As an early adopter of Digital Product Passports, Nobody’s Child has chosen to collect this level of product detail well ahead of the EU law going into effect in 2030. For many of the larger retailers and brands I work with, the sheer volume of products, materials, and suppliers makes collecting and consolidating ESG data a herculean task.
Their typical approach to addressing this challenge is to:
- Work backwards from legal requirements and ESG commitments to determine what data is needed, whether they have it, and, if so, how accurate it is.
- Develop a phased approach to closing the gaps and improving the quality of the data.
- Centralize the data and make it visible to decision makers across the organization.
As Ms. Plows mentions, this approach often puts a lot more work on the plates of tier one and tier two suppliers. It may also require retailers to adjust business processes associated with product design, development, and sourcing.
Materials and fibers are a good starting point
Material- and fiber-level ESG data is needed to support many global regulatory requirements, as well as the two most common ESG commitments—100 percent sustainably-sourced products and reducing Scope 3 emissions 30-40 percent by 2030. You cannot measure either of these things without specific details about the raw materials that go into a product and the processes that went into transforming those raw materials into a finished product.
This is why I have seen retailers focus their initial efforts on expanding the list of required fields in their material and material-supplier libraries, including:
- Base material composition breakdowns (e.g., 60% cotton and 40% polyester) augmented by raw material splits within each base material (e.g., 75% of the polyester is virgin and 25% is Ground to Good™).
- Country of origin, chemicals used, yarn formation methodology, and other applied processes for each raw material.
- Material-level textile formation and finishing processes (e.g., weaving and dyeing methods, waterproofing).
- Material-supplier level traceability data and scope-certificate details (e.g., percent traceable to the source, percent organic or recycled content).
“Can we do this without building a Fiber Library?”
Many retailers weigh the pros and cons of incorporating this data into a separate fiber library along with an associated Tier 3 (raw material) supplier library.
The main advantage is accuracy. You’re going to get more precise estimates for specific raw material suppliers than estimates based on generic, representative versions of that raw material.
Let’s look at organic cotton. Impact estimates for generic organic cotton relies on global averages. Yields in India, China, Australia, etc., are all thrown together to create one average. By contrast, Better Cotton uses what it describes as a “farm footprinting” approach to measurement relying on regional assessments that take into account differences in things like soil health, irrigation methods, and yields. Estimates for Better Cotton produced in India are going to be more accurate than generic organic cotton estimates because there is less variability in these input parameters.
Now to the cons. Let’s suppose that a retailer builds out a Tier 3 supplier library and uses it to assign specific raw material suppliers to material-level BOMs (as shown in the graphic below).
This creates two potential headaches. The first headache is entering in and maintaining what could be a massive number of Tier 3 suppliers for the same raw material. No, I am not saying that a retailer is going to add all 2,200 Better Cotton suppliers to its Tier 3 library. But someone will need to add all of the Better Cotton suppliers that work directly with its Tier 2 material suppliers. That burden would likely fall on the Tier 2 suppliers themselves.
The second headache is the potential for the raw material supplier chosen in the material BOM to not be the eventual supplier when the material is actually created. The Tier 2 supplier could have every intention to use the specified raw material supplier, but not have enough inventory from them in stock to complete the order. Or maybe they got a better price from another supplier.
“I’ve conquered materials and fibers. What’s next?”
Raw materials and material production only account for 30-40 percent of a product’s GHG emissions. This is why Lifecycle Assessment (LCA) and Product Environmental Footprint (PEF) tools—like Worldly’s Product Impact Calculator, Glimpact and SimaPro—include details on how a product is assembled, along with downstream processes such as shipping logistics, energy usage in stores, how the consumer uses the product, and what happens to the product when the consumer is through with it.
When combined with material-level attributes, the product-level attributes required to estimate the impact in each of these areas can easily reach the 110 data points cited by Jody Plows.
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