Interview: Practitioners on Supply chain traceability & product data — what they wish they knew earlier

A 2025 survey by the MIT Center for Transportation and Logistics found that 73% of companies investing in supply chain traceability reported that their initial implementation failed to meet stated objectives, with a median time-to-value of 26 months compared to the 9-month timeline most organizations projected at kickoff. These numbers reflect a widespread pattern: traceability technology works, but the operational, organizational, and data-quality challenges surrounding deployment consistently surprise even experienced teams. To understand what separates successful implementations from expensive failures, we gathered insights from practitioners across industries who have led traceability programs from pilot through scale.

Why It Matters

Supply chain traceability has shifted from a voluntary transparency initiative to a regulatory requirement across major markets. The EU's Corporate Sustainability Due Diligence Directive (CSDDD), the German Supply Chain Act (LkSG), and the EU Deforestation Regulation (EUDR) collectively mandate that companies trace raw materials and components to their origin, verify environmental and social compliance at each tier, and maintain auditable data records. By 2027, an estimated 16,000 companies operating in the EU will face mandatory traceability obligations, according to the European Commission's impact assessment (European Commission, 2024).

The financial stakes are substantial. Non-compliance with the EUDR alone carries penalties of up to 4% of EU-wide annual turnover. Beyond regulatory risk, traceability data increasingly drives procurement decisions: a 2025 Ecovadis survey of 800 chief procurement officers found that 62% now require Tier 2 or deeper visibility as a condition of preferred supplier status, up from 28% in 2022 (Ecovadis, 2025). Companies that cannot provide product-level provenance data face exclusion from major supply chains.

Yet the gap between regulatory ambition and operational readiness remains wide. Practitioners consistently report that the technology layer, whether blockchain, IoT sensors, or cloud platforms, accounts for only 20 to 30% of implementation effort. The remaining 70 to 80% involves data standardization, supplier onboarding, change management, and governance design.

Key Concepts

Tier-depth visibility refers to how far upstream a company can trace its supply chain. Most companies have reliable data on Tier 1 (direct suppliers) but rapidly lose visibility at Tier 2 and beyond. Achieving Tier 3 or Tier 4 visibility typically requires intermediary platforms or industry consortia that aggregate data across competing supply chains.

Interoperability describes the ability of different traceability systems to exchange and interpret data. The proliferation of proprietary platforms has created data silos, with practitioners reporting that their suppliers often participate in three or more traceability systems simultaneously, each requiring different data formats and submission processes.

Digital product passports (DPPs) are standardized digital records that travel with a product throughout its lifecycle, capturing material composition, manufacturing conditions, chain of custody, and end-of-life instructions. The EU's Ecodesign for Sustainable Products Regulation (ESPR) will require DPPs for batteries starting in 2027, textiles by 2028, and additional product categories thereafter.

Mass balance and physical segregation represent two competing approaches to traceability. Physical segregation tracks specific certified materials through a dedicated supply chain, while mass balance allows certified and non-certified materials to be mixed as long as the overall volume of certified inputs matches the certified output claims. Practitioners disagree sharply on which approach delivers meaningful accountability versus merely enabling greenwashing.

What's Working

Sector-specific consortia have emerged as the most effective model for scaling traceability beyond Tier 1. The Responsible Minerals Initiative (RMI), which now covers over 400 smelters and refiners processing tin, tantalum, tungsten, gold, and cobalt, demonstrates that shared audit infrastructure reduces per-company costs by 60 to 75% compared to individual supplier assessments. Intel, Apple, and Samsung collectively fund third-party smelter audits through RMI, creating a baseline of verified data that any participating company can reference without duplicating fieldwork.

In the food sector, Walmart's Project Gigaton supply chain platform has onboarded over 5,400 suppliers providing emissions and sourcing data. The platform's success stems from a critical design decision: rather than requiring suppliers to adopt a specific technology, Walmart accepts data in multiple formats and uses internal normalization algorithms. This pragmatic approach reduced supplier onboarding friction by an estimated 40% compared to single-platform mandates (Walmart, 2025).

IoT-enabled traceability has proven particularly effective for cold chain and pharmaceutical supply chains where product integrity depends on continuous environmental monitoring. Merck's serialization and track-and-trace system, built to comply with the US Drug Supply Chain Security Act (DSCSA), processes over 4 billion serialized unit transactions annually. The system's real-time visibility has reduced counterfeit penetration in Merck's distribution network to below 0.001% and cut recall response times from an average of 14 days to under 48 hours (Merck, 2024).

Practitioners in the apparel industry point to the Open Apparel Registry (now Open Supply Hub) as an example of collaborative infrastructure done right. The platform provides a single, canonical identification system for over 100,000 manufacturing facilities worldwide, eliminating the duplicate-facility problem that plagued earlier traceability efforts. Before Open Supply Hub, brands routinely discovered that what they thought were three separate supplier facilities were actually the same factory operating under different names in different systems.

What's Not Working

Supplier fatigue is the most frequently cited barrier across industries. Mid-tier suppliers, particularly those in Southeast Asia and Sub-Saharan Africa, report participating in 5 to 12 different traceability platforms simultaneously, each with unique login credentials, data formats, reporting schedules, and audit requirements. A 2025 survey by the Sustainable Apparel Coalition found that the average Tier 2 garment factory spends 340 hours per year on traceability-related data entry, representing a compliance cost of $18,000 to $25,000 annually for factories with gross margins of 3 to 5% (SAC, 2025). This burden falls disproportionately on the suppliers least able to absorb it.

Blockchain-based traceability, despite significant venture investment ($2.4 billion deployed between 2020 and 2025 according to PitchBook data), has largely failed to deliver on its initial promise of trustless verification. Practitioners consistently identify the "oracle problem" as the fundamental limitation: blockchain can ensure that data is immutable once recorded, but it cannot verify whether the data entered at the point of origin is accurate. A factory that misrepresents its labor practices or a farm that falsifies its deforestation-free status will produce an immutable but false record. The IBM Food Trust platform, once positioned as the industry-leading blockchain traceability solution, was quietly wound down in 2023 after failing to achieve the network effects necessary for commercial viability.

Data quality at the point of origin remains stubbornly poor. Practitioners report that 30 to 50% of supplier-submitted data contains errors, inconsistencies, or gaps that require manual remediation. Geocoordinate data for agricultural plots, essential for deforestation-free compliance under the EUDR, is frequently inaccurate by margins of 500 meters to 2 kilometers, rendering it useless for satellite-based verification. Translation errors in multi-language supply chains, unit-of-measure discrepancies, and inconsistent facility naming conventions compound the problem.

The cost-value equation for small and medium enterprises (SMEs) remains unresolved. Enterprise-grade traceability platforms from providers such as SAP, HARA, and Sourcemap carry annual subscription costs of $50,000 to $500,000, pricing out the smallholder farmers, artisanal miners, and small manufacturers who populate the upstream tiers of most supply chains. Without affordable entry points, traceability systems create a documentation gap at precisely the supply chain stages where environmental and social risks are highest.

Key Players

Established Companies

• SAP: Offers Green Ledger and Responsible Design and Production modules integrated with ERP systems, serving over 3,000 enterprise customers with supply chain traceability.
• Sourcemap: Provides end-to-end supply chain mapping with risk scoring across 150+ commodities, used by Patagonia, Mars, and Target.
• IBM Sterling: Enterprise supply chain visibility platform processing over 30 billion transactions annually across logistics and procurement networks.

Startups

• Altana AI: Uses trade data and machine learning to map global supply networks, raising $200 million in Series B funding in 2024 to expand cross-border traceability.
• Tilkal: Paris-based platform specializing in EUDR compliance with satellite-verified deforestation-free traceability for cocoa, palm oil, and soy supply chains.
• Restor: Swiss startup building open-access ecological monitoring tools that connect supply chain traceability to biodiversity and carbon data at the landscape level.

Investors

• Breakthrough Energy Ventures: Invested in multiple supply chain data platforms connecting environmental impact to procurement decisions.
• Generation Investment Management: Active investor in sustainable supply chain technology, including traceability infrastructure for food and materials.
• Decisive Farming (acquired by TELUS Agriculture): Demonstrates consolidation trend as larger technology players acquire point solutions for farm-to-fork traceability.

Action Checklist

• Conduct a tier-depth assessment to determine current visibility (most organizations discover they have reliable data only to Tier 1) before selecting technology
• Join at least one industry consortium or shared-audit platform to reduce per-company traceability costs and increase data coverage
• Adopt GS1 standards (EPCIS 2.0) as the default data format to maximize interoperability across platforms and trading partners
• Allocate 60 to 70% of implementation budget to supplier onboarding, training, and data quality remediation rather than software licensing
• Establish a dedicated data quality team that reviews incoming supplier data for completeness, consistency, and plausibility before it enters production systems
• Design traceability systems for multi-format data ingestion rather than mandating a single platform across all supplier tiers
• Build EUDR, CSDDD, and DSCSA compliance requirements into traceability system specifications from the outset rather than retrofitting later
• Pilot with 10 to 20 strategically selected suppliers before attempting full-scale rollout, using pilot feedback to refine onboarding processes

FAQ

Q: How long does a typical traceability implementation take from pilot to full-scale deployment? A: Practitioners consistently report 18 to 30 months from initial pilot to operational deployment across at least 80% of the supply base. The pilot phase (3 to 6 months) is relatively straightforward; the challenge lies in the supplier onboarding phase, where scaling from 20 pilot suppliers to 500 or more production suppliers exposes data quality issues, process gaps, and change management resistance that were not visible during the controlled pilot. Organizations that compress this timeline by skipping structured onboarding typically spend more time and money on remediation later.

Q: Should we build custom traceability infrastructure or buy a commercial platform? A: The build-versus-buy calculus has shifted decisively toward buying or joining existing platforms. Custom development was common from 2018 to 2022 when commercial options were immature, but the current generation of platforms from Sourcemap, SAP, and Altana AI covers 80 to 90% of enterprise requirements. The exceptions are organizations with highly specialized supply chains (aerospace, defense, pharmaceuticals) where regulatory requirements demand custom validation workflows. Even in these cases, practitioners recommend building custom modules on top of commercial platforms rather than creating entirely bespoke systems.

Q: What is the minimum viable data set for meaningful traceability? A: Practitioners converge on five core data elements as the minimum viable set: facility identification (using a canonical ID system such as Open Supply Hub), product or material identification (using GS1 GTINs or equivalent), transaction date and quantity, geocoordinate of origin (for agricultural and extractive commodities), and at least one verified compliance attribute (such as deforestation-free status, fair labor certification, or emissions intensity). Adding more data fields increases analytical value but also increases supplier burden and data quality risk. Start with five and expand incrementally based on demonstrated data quality at each level.

Q: How do we handle suppliers who refuse to participate in traceability programs? A: This is the most politically sensitive question in traceability implementation. Practitioners recommend a graduated approach: begin with clear communication about upcoming regulatory requirements and the business case for participation; provide free or subsidized access to traceability tools; offer technical assistance for data submission; and set a firm deadline (typically 12 to 18 months) after which non-participating suppliers are deprioritized in sourcing decisions. Most organizations find that 85 to 90% of suppliers comply within 12 months when participation is tied to continued business. The remaining 10 to 15% often require supplier development investment or, in some cases, replacement.

Sources

• European Commission. (2024). Impact Assessment: Corporate Sustainability Due Diligence Directive Implementation. Brussels: European Commission.
• Ecovadis. (2025). Global Procurement Sustainability Barometer: Supplier Visibility and Risk Management Trends. Paris: Ecovadis SAS.
• MIT Center for Transportation and Logistics. (2025). State of Supply Chain Traceability: Technology Adoption, Barriers, and Outcomes. Cambridge, MA: MIT CTL.
• Sustainable Apparel Coalition. (2025). Supplier Compliance Burden Study: Quantifying the Cost of Multi-Platform Traceability. San Francisco: SAC.
• Walmart. (2025). Project Gigaton Progress Report: Supplier Engagement and Emissions Reduction Outcomes. Bentonville, AR: Walmart Inc.
• Merck & Co. (2024). Drug Supply Chain Security Act Compliance: Serialization and Track-and-Trace Performance Report. Rahway, NJ: Merck & Co., Inc.
• GS1. (2025). EPCIS 2.0 Implementation Guide: Interoperable Supply Chain Traceability. Brussels: GS1 AISBL.