Researchers Prosper Dzidzienyo, Saeed Rahimpour and Luana Dessbesell, writing in Environmental and Sustainability Indicators, have developed what they call a Traceability Degree Score, a systematic framework for grading individual pieces of product data on how reliably they can be captured, verified and exchanged along a supply chain. Rather than asking whether data exists, the framework asks whether each data element can be systematically linked to its point of origin, checked for accuracy and transmitted across supply chain partners in a digitally structured format. That distinction matters, because the authors’ analysis of a full textile lifecycle suggests that most of the data needed for passports currently sits in a grey zone: present in some form, but far from trustworthy or interoperable.

The framework rests on four indicators drawn from maturity-model theory, information quality research and supply chain traceability standards. The first is standardisation, which measures whether data are defined and reported in harmonised formats with persistent identifiers, so that a batch number means the same thing to a pulp mill in Finland and a retailer in Paris. The second is automation, assessing whether information is captured by sensors and enterprise systems rather than typed in by hand. The third is reliability, which captures whether measurements are accurate, consistent and independently verifiable. The fourth, blockchain readiness, is deliberately misnamed in the eyes of no one: it does not assume distributed ledgers are required, but instead evaluates whether data are structured, uniquely identifiable and linked to discrete lifecycle events, properties that any immutable, event-based traceability architecture would demand. Each data element is scored from one to five on every indicator, and the four scores are averaged into a single composite value.

To test the approach, the researchers constructed a detailed case study of a man-made cellulosic textile, a fabric made from 80 percent certified renewable wood and 20 percent recycled textile waste, both sourced in Finland. This hybrid of bio-based and circular material streams was chosen precisely because it mirrors the sourcing complexity that passport regulation is meant to address. Drawing on EU regulatory texts, the CIRPASS project’s passport prototypes, stakeholder consultations and life cycle assessment literature, the team identified 336 individual primary data elements spread across ten lifecycle nodes, from forestry and pulping through fibre, yarn, fabric and garment production to distribution, consumer use and end-of-life.

The results are striking for how unevenly traceability is distributed. Half of all data elements scored at the moderate level, meaning they exist in structured form but lack the full automation, verification or interoperability that seamless passport integration requires. Only 20 percent achieved the highest maturity, being digitally standardised, automatically captured, externally verified and ready for distributed ledger transmission. A quarter showed limited traceability, hampered by manual entry or inconsistent templates, while the remainder were essentially untraceable, concentrated in the consumer-use and end-of-life phases. In other words, the single most important stage for circular decisions — what happens to a garment after the sale — is exactly where the data infrastructure is weakest.

The node-by-node comparison sharpens that picture. Distribution and retail scored highest, with a mean traceability degree of 4.30, closely followed by dissolving pulp production at 4.28 and textile recycling at 4.13. The authors attribute the retail result to the quiet success of existing logistics standards: GS1 identifiers, batch numbering and trade barcodes have been standardised for decades, so the data foundations there are already mature. Manufacturing nodes such as fibre production, fabric making, yarn spinning and garment assembly landed in an intermediate band between 3.78 and 3.89, reflecting partial digitisation within factories but limited data exchange between companies. Raw material sourcing scored 3.55, while consumer use collapsed to 2.00 and end-of-life managed only 3.13. No single node achieved uniformly high scores across all four indicators, a finding the researchers say confirms that traceability maturity cannot be reduced to digitalisation alone.

The study also exposes a structural tension at the heart of the EU’s circular economy agenda. Digital Product Passports are explicitly intended to enable downstream value retention — reuse, repair and recycling — yet the phases where those decisions are made are the ones with the poorest data readiness. Consumer behaviour, device heterogeneity and the absence of standardised reporting at the end of a product’s life mean the data trail simply frays out. The researchers note that harmonised data definitions alone are insufficient: many nodes scored well on standardisation while lagging badly on automation and blockchain readiness, showing that agreeing on what to record is a very different problem from being able to record it reliably at scale.

Methodologically, the framework fills a gap that previous approaches left open. Earlier efforts to prioritise passport data, including ranking systems based on importance, availability and sensitivity, largely captured stakeholder perceptions of what data matters. Industry 4.0 maturity models, meanwhile, assess whole organisations rather than individual data points. By scoring data elements themselves, the new approach converts qualitative regulatory demands — data must be verifiable, data must be machine-readable — into a consistent numerical index that can pinpoint exactly where along a supply chain investment is most needed. The authors stress that the framework is technologically neutral: blockchain readiness measures architectural compatibility, not adoption, and European regulations remain agnostic about implementation technology.

The researchers acknowledge limitations. The case scores were derived from secondary sources reflecting average industrial realities in a Finnish context, and values would shift across regions, technologies and firms; the point of the exercise is to demonstrate a reproducible method rather than to deliver fixed numbers. The assessment is also a snapshot in time, whereas passport requirements and data systems will both evolve rapidly, calling for longitudinal studies and operational pilots. Inter-rater reliability and automated scoring are flagged as priorities for future work, as is validation across other product categories — the framework operates at the level of generic data elements, making it directly applicable to batteries, electronics, construction materials and other sectors that the passport regulation will eventually touch.

Still, the message for industry and policymakers is clear. As passport implementation accelerates, the readiness of product data is not a binary yes or no but a measurable, multi-dimensional capability that currently varies wildly across the lifecycle of even a well-documented textile. With only one in five data elements in the case study achieving full traceability maturity, and with the circular economy’s most critical decision points sitting at the bottom of the maturity curve, the gap between regulatory intent and operational data reality is wide. Diagnostic tools like the Traceability Degree Score offer a way to map that gap precisely — and, the authors argue, a way to close it with targeted investment rather than hopeful assumptions.

Subject of Research: A traceability assessment framework for primary data elements in textile digital product passports

Article Title: A framework for evaluating the traceability of primary data elements for textile digital product passports

Article References: Dzidzienyo, P., Rahimpour, S., & Dessbesell, L. (2026). A framework for evaluating the traceability of primary data elements for textile digital product passports. Environmental and Sustainability Indicators, 32, Article 101514. https://doi.org/10.1016/j.indic.2026.101514

Image Credits: AI Generated

DOI: 10.1016/j.indic.2026.101514

Keywords: digital product passports, textile supply chains, traceability, EU regulation, ESPR, circular economy, data quality, blockchain readiness, standardisation, automation, man-made cellulosic textiles, sustainability indicators