The fashion and textile industry is navigating a critical pivot point, driven by a surge in global mandates such as the EU’s Digital Product Passport (DPP) and the Corporate Sustainability Due Diligence Directive (CSDDD). These regulations are fundamentally changing the role of supply chain traceability — elevating it from an optional sustainability initiative to a “non-negotiable license to operate.”
Here, Shameek Ghosh, CEO and co-founder of the AI-powered traceability platform TrusTrace, details how brands can move beyond treating compliance as a cost center. He explains how centralizing product-level evidence — from supplier data and certificates to chain-of-custody — creates a single source of truth for proactive risk management, audit-ready proof, and measurable impact intelligence. Ghosh also provides executives with the framework for building a compelling ROI case and outlines how to avoid the most common pitfalls when scaling traceability across vast global supply networks.
HGI: How would you describe the core value proposition that your AI-powered traceability platform delivers to fashion and textile brands looking to shift from compliance-driven initiatives to true, measurable supply chain impact and consumer trust?
Shameek Ghosh: TrusTrace is the control center for supply-chain data — an AI-powered platform that lets brands collect once, validate once and reuse everywhere. When all primary, product-level evidence (supplier, facility, process, certificates, audits, geodata, chain of custody) lives in one hub, you unlock three outcomes:
- Proactive risk management: See the actual risk in your network and your products, versus generic risks in theoretical networks, so teams fix what matters before it escalates, and stop spending time on risks that are not relevant or material.
- Regulator-ready proof: Generate audit-ready evidence packages for laws and regulations such as ESPR, DPP, EPR, EUDR, Eco score, Forced Labor, CSDDD etc., without duplicating work. Proof builds trust with regulators, customers and consumers.
- Impact intelligence: Spot real hotspots (e.g., dyeing/finishing/logistics), calculate LCAs with higher confidence based on actual product data, and prioritize Scope 3 reductions based on verified activity data, not averages.
In short: TrusTrace provides a scalable supply chain data infrastructure that turns evidence into compliance, resilience and brand trust.
HGI: How is the incoming legislation in the EU fundamentally changing the necessity of supply chain traceability from a ‘nice-to-have’ competitive advantage to a non-negotiable license to operate?
SG: The tsunami of global regulations raises the bar from claims to verifiable evidence. Treating each regulation in isolation is already unworkable and costly, and with the accelerating amount and granularity of regulations coming, companies must act now to set up systems to manage this, or get left behind. Our approach is a system of record for supply-chain evidence, guided by The TrusTrace Compliance Canvas, which maps common data requirements across regulations, and launched June 2025 to enable brands (and suppliers) to collect and validate data once, and reuse it across regulatory and reporting needs.
With DPP and EUDR tying market access to data availability and quality, traceability is no longer a marketing advantage, it’s operational permission to sell. Brands that standardize evidence flows now will stay agile as rules evolve.
HGI: Traceability implementation can seem like a significant upfront cost. What is the most compelling business case and measurable ROI that executives can present traceability as an investment in operational efficiency and long-term brand value creation?
SG: Traceability becomes a value engine when evidence is centralized and reusable. Typical gains we see:
- Cost and time savings: Automated ingestion/validation eliminates manual consolidation across emails, spreadsheets and portals, cutting cycle time and freeing teams for higher-value work.
- Risk and revenue protection: Proactive risk management enables companies to discover and eliminate risks before they affect market access and/or brand reputation, faster investigations with clearly mapped supply chains with evidence-chains at a product level; lower greenwashing/reputational risk with audit-ready proof of conduct.
- Efficiency and growth: Building trust and loyalty with consumers through credible product communication, ensuring future market access, optimizing supply chain networks with high-performing and low-risk suppliers.
- Future fees avoided/reduced: EPR and eco-modulation favor brands with product-level evidence and circularity proof. Having validated data leads to lower fees.
Executives can frame ROI across three lines: lower operating expenditures (hours saved, rework reduced); risk avoided (market-access, legal, reputation); and value created (faster compliance, stronger claims, customer preference).
HGI: For brands and retailers who are just starting their traceability journey, what framework can they use to effectively evaluate their current supply chain needs and the technology that best fits their specific product categories and sustainability objectives?
SG: What type of data you need, in terms of granularity, timeliness and evidence backing, depends on your use case. There are different stages of maturity that all brands need to go through, and depending on their starting point there is a clear path forward. We generally think in terms of network and product data as the foundation upon which you can run analytics and reporting across risk, compliance and impact.
A typical pathway looks like this:
Build the network foundation (supplier-centric): Map out the suppliers and facilities in your network across the tiers, and collect core evidence (audits, certifications, process/energy/water). Brands typically communicate with tier 1 and 2, who then own the data collection for deeper tiers, as they have the relationship and direct communication with those suppliers.
Link evidence to products (product-centric): Map out the specific chain-of-custody for products at a PO or batch level. This enables you to understand the most critical nodes in the network; and how they tie to the main product lines and revenue.
This can be done in two ways. Product-backwards (after-the-fact) for changing chains or limited upstream visibility, or material-forward (near real-time) for stable, repeatable chains needing granular proof and waste/inventory control.
What you chose depends on specific use cases and accepted risk-levels. Product backwards requires less resources and can work well if you want to ensure you can collect data when you need it — but do not need data in real-time, e.g. for a WRO. Material-forward requires more of the network to continually share information, but also gives you a real-time view across your supply chain network, and ensures you have evidence for each product and batch as it reaches a market.
For example, if you need to be able to make product material claims — mass balance will not be enough — and you’ll need a chain-of-custody for each product, including evidence like scope and transaction certificates for that material to credibly make that claim.
You need to then run data-based risk and due diligence. Unified network and product data is needed to drive due diligence at any level; such as geography, material or product while leveraging a unified data hub to analyze and pull data as needed — for compliance evidence, internal or internal reporting, and improving impact.
This framework shifts from reactive to proactive risk and impact management, with a central infrastructure for managing data, with suppliers in the loop.
HGI: What are the most common critical pitfalls that established brands encounter when trying to scale their traceability efforts across multiple product lines or hundreds of global suppliers?
SG: Major pitfalls fall into two buckets – internal and external readiness — both of which can delay or derail efforts to scale traceability.
The first is internal readiness (misalignment, weak systems, poor data).
The pitfall: Conflicting objectives, no clear ownership, fragmented tools and low data quality stall scale. This happens when companies see traceability as the job of one department, rather than a fundamental digital transformation covering all functions working with the supply chain.
What “ready” looks like: A CEO-sponsored program with a shared roadmap, RACI [Responsible, Accountable, Consulted, Informed] across sustainability, compliance/legal, IT/data, sourcing and procurement, and a single data hub unifying network plus product evidence. Strong PLM/ERP integration, defined data standards, and automation replace manual reconciliation.
Outcome: Faster, better decisions from one source of truth — and a traceability capability that actually scales.
The second is external readiness (weak supplier ties, fatigue and inconsistent evidence).
The pitfalls: Thin supplier relationships make it hard to secure buy-in for traceability. Multiple portals, formats and duplicative requests create friction and poor data. The challenge is sharper for brands with weaker relationships, e.g. as they rely on agents, don’t nominate material suppliers or frequently shift networks.
The fix: Go supplier-first. Onboard and support suppliers (virtual or on-the-ground, in local languages) so the why is clear and participation is easy. With TrusTrace, suppliers collect data once, and reuse it for many use cases via harmonized, AI-assisted data capture: upload invoices, shipping records, audits and certificates; the platform translates, reads and links them into chain-of-custody with evidence, flags risks and triggers targeted questionnaires, audits, or CAPs.
Result: less admin, faster approvals, higher NPS and visible compliance readiness for their customers.
