Regulatory Digital Product Passports as a Catalyst for U. S. Supply Chain Visibility
Persistent limitations in how supply chain data is expressed, shared, and analyzed constrain both public- and private-sector decision-making in the United States. Current practices remain largely single-threaded and tactical, with heavy dependence on third-party datasets that often lack completeness, consistency, and provenance. This paper examines whether emerging European Union( EU) and United Nations( UN) initiatives— particularly the EU Ecodesign for Sustainable Products Regulation( ESPR) and the UN / CEFACT United Nations Transparency Protocol( UNTP)— are likely to drive standardized, structured Digital Product Passport( DPP) data creation at scale, and whether that shift could significantly improve availability of actionable supply chain data in and through the United States.
This paper assesses compliance mechanisms, cross-sector adoption dynamics, and expected differences in newly available data( including product identity, composition, provenance, and verifiable claims). UNTP, while voluntary, provides an interoperability pathway designed to preserve data ownership while enabling verifiable, machine-readable exchange at scale. We argue that DPPs can function as high-confidence supply chain sub-graphs that, if accessible and aggregable, could be stitched into strategic meta-graphs for risk analysis, due diligence, sustainability reporting, and resilience planning. Whether this value is realized in the U. S. depends less on whether DPP data will exist than on how organizations can access it, normalize it across efforts, and handle confidentiality, privity, and proprietary constraints. Emerging open standards— particularly SPDX 3.1 with its Supply Chain and Hardware Profiles— provide a candidate technical substrate for serializing and exchanging DPP instance data in machinereadable bill of materials form, bridging DPP policy requirements to operational implementation.
1 INTRODUCTION
U. S. supply chain decision-making is often constrained by data that is incomplete, inconsistently structured, and difficult to aggregate for strategic insight. Supply chain data practices today remain largely " single-threaded " and tactical rather than strategic, relying heavily on third-party sources such as product-level and transaction-level shipping data, corporate reporting, and other indirect signals rather than first-party, structured product and provenance data [ 1 ]. The U. S. Customs and Border Protection( CBP) data is primarily focused on international flows through U. S. ports and is not broadly shared outside Freedom of Information Act( FOIA) requests. These characteristics limit higher-order aggregation and analysis. In parallel, the bill of materials( BOM) standards community— through SPDX 3.1 and CycloneDX— has been expanding beyond software inventories toward supply-chain-event and hardware-component modeling, providing a potential normalization layer for the kind of structured, provenance-rich data this paper examines.
At the same time, regulatory and standards-driven pressures are accelerating. The EU has enacted ESPR as a framework regulation that will require Digital Product Passports( DPPs) for prioritized product categories, supported by subsequent public consultations and delegated-act development [ 2 ]. In parallel, the UN / CEFACT has advanced UNTP as a protocol for
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