Blockchain and industrial flow traceability maturity
Your flow traceability, measured by maturity level and translated into a roadmap.
10 themes, a 5-level scale. And the action that moves each level to the next.
The framework’s 10 themes, already written from L1 to L5. One company, one business unit, or 300 at once.
Blockchain and industrial flow traceability maturity
10 themes, 5-level scale.
Nordhavn Industries
53 / 100
They measure their maturity with Datamensio
An example
This could be your situation.
Take one company as an example: three sites, three spreadsheets, no shared answer.
Nobody can consolidate.
Nordhavn Industries, 2,400 people in Hamburg, Lyon and Porto. A client asks where the group stands. Each site answers in its own spreadsheet, with its own scales.
Three weeks, a single base.
One Datamensio maturity framework · blockchain and industrial flow traceability (distributed ledgers, product identifiers, value chain data exchange) assessment launched across all three sites at once, from the managers’ interview notes. The framework was already written, its 10 themes and levels L1 to L5 too.
Two costs avoided before being committed.
A score of 53 out of 100, with the gap concentrated on three themes. The AI companion spotted that two actions duplicated those of another audit. The committee report took one sentence to request.
What it saved them
- 3sites measured on the same base, instead of three questionnaires to reconcile
- 2duplicate actions caught before the spend
- 1committee report, with no manual rework
These figures are an example. They could be yours.
The standard imposes processes. Datamensio says where you stand.
01
The framework is already written
Themes, questions and levels L1 to L5, all written. You do not start from an empty spreadsheet.
02
The score lands the same day
Online, by self-assessment link or in interview. Theme by theme, comparable over time.
03
The gap becomes a costed plan
Every step up carries its action. The AI prioritises on expected effect, not on the order of the standard.
04
Progress can be demonstrated
Campaign after campaign, against your target and against your own past. That is what your board asks for.
The maturity scale
One level, the next, and the action that links the two.
It is this mechanism (a level, a higher level, and the action that links the two) that turns an observation into a trajectory.
Can you reconstruct the complete lineage of a product, from raw material through to delivery?
- N1
No reconstruction is possible without an investigation. Information is scattered across paper documents, production files and team memory.
- N2
Lineage can be reconstructed for certain workshops or ranges, through manual extracts and file cross-checking.
- N3
Upstream and downstream lineage is available in the system for all products manufactured in-house, with a known response time.
- N4
Lineage includes outsourced operations and supplier components, with completeness checks and monitoring of the missing data rate.
- N5
Lineage is shared with partners under defined rights, its integrity is attested, and the system is proven through documented periodic recall exercises.
Action to move from L2 to L3
Extend event capture to uncovered workshops and link each production order to the batches consumed in the MES, then measure the reconstruction time at the monthly quality review until it becomes stable.
« With Datamensio, we meet our objectives far more efficiently. The ERDF inspection services and our supervising ministry particularly appreciated an approach that gives them reliable data. »
Director, CCI 94CCI Île-de-France
« We believe this is the most suitable solution to scale our transformation project and measure impact according to our needs. »
Maja SucekChief Operating Officer, Interreg Danube
Rarely on its own
Frameworks combine. Put several together to cover your business, or have the AI write yours.
Take your first measurement
What this framework covers
This framework assesses an industrial organisation’s ability to identify, track and evidence its flows, from tier 2 suppliers through to final use. It covers unit or batch identification, tracking granularity, event capture at transformation and transfer points, the quality of the data produced, exchange with partners, and the possible use of distributed ledgers to guarantee the integrity and sharing of this evidence between parties who do not trust each other by default. It treats blockchain as a means, not an end.
The difficulty is rarely technological. It lies in the continuity of the data chain. What happens when a batch is split on the shop floor, then reconstituted in packaging: is the lineage preserved or lost? How long does it currently take to reconstruct the full history of a serial number, and how many people need to be involved? Do your suppliers send usable data, or files reworked by hand before integration? While these answers remain vague, the subject stays a pilot project and never becomes an industrial capability.
The context has shifted on one specific point: the digital product passport, introduced by the EU Ecodesign for Sustainable Products Regulation (Regulation EU 2024/1781), will make it mandatory for successive product categories to provide composition, repairability and origin data attached to a unique identifier. Batteries lead the way. This requirement turns traceability into a structuring capability that goes beyond quality alone and involves design, procurement and information systems.
One confusion deserves to be cleared up: recording data in a distributed ledger guarantees it has not been altered afterwards, not that it was accurate at the point of recording. The value of a traceability system is decided upstream, in the reliability of capture and the governance of identifiers. The assessment therefore distinguishes these two levels. It asks a different question from a compliance check: not whether a system exists, but at what level of control it operates and what action moves it to the next level.
The framework is ready to use in Datamensio and adapts to your sector. AI adjusts the themes, questions and levels to your context (food and beverage, pharmaceuticals, aerospace, electronics), or builds a variant from your own documents: traceability specifications, quality procedures, production system architecture diagrams.
Reference standard: Datamensio maturity framework · blockchain and industrial flow traceability (distributed ledgers, product identifiers, value chain data exchange)
The themes assessed
Strategy and use cases
Objectives assigned to traceability (quality, recall, anti-counterfeiting, proof of origin, customer requirements), product and site scope, trade-off between centralised database and shared ledger, budget ownership.
Identification and granularity
Identifier policy, standards used (GS1, matrix codes, RFID, direct marking), tracking level chosen (unit, batch, pallet), identifier management during splitting and grouping.
Event capture
Reading points along the flow, automation versus manual entry, timestamping, transformation, transfer and dispatch events, coverage of outsourced operations.
Data quality and governance
Common data model, naming rules, completeness and rejection rates, anomaly correction, data ownership, retention period.
Integration with the industrial information system
Interplay between MES, ERP, WMS, LIMS and automation systems, interfaces and flows, handling network outages on the shop floor, dependency on manual extracts.
Distributed ledgers and integrity of evidence
Choice of technology and network governance model, data recorded versus data referenced, anchoring and timestamping, key management, cost and footprint of the system, reversibility.
Exchange with value chain partners
Exchange formats and protocols, integration of tier 1 suppliers and beyond, contractual conditions for data transmission, confidentiality and segregation of competing data.
Operation and reporting
Upstream and downstream lineage reconstruction, response time to a recall request, indicators tracked, reporting to customers, authorities and auditors.
Product compliance and digital passport
Regulatory data attached to the product, preparation for the digital product passport, sector serialisation requirements, proof of origin and material declarations.
Skills and change management
Adoption by operators, training in scanning and declaration tasks, roles dedicated to traceability data, feedback and improvement of the system.
A short version of the framework is available for the online self-assessment.
Frequently asked questions
Do we already need to use a blockchain to take this assessment?
No. The framework first assesses traceability itself: identification, capture, data quality, exchange with partners. Distributed ledgers are one theme among others. Many organisations achieve a useful score without having deployed any blockchain at all.
Does this assessment deliver a certification?
No, and no certification exists on this subject. The assessment measures a maturity level and produces a roadmap. It can, however, serve as documented evidence during a customer audit or a sector evaluation.
How does this differ from a conventional traceability audit?
An audit checks whether a system exists and concludes with a gap. The assessment places your practices on a progressive scale and indicates the action that moves you to the next level. It lends itself to comparison across sites and over time, which an audit report does not allow.
How long does the assessment take?
The short version takes 20 to 30 minutes to complete by a manager who knows the flows. The full version, run collaboratively with production, quality, supply chain and information systems, generally spans one to two weeks, most of the time going into data collection.
Can the framework be adapted to our sector?
Yes. The questions, levels and themes can be modified, and AI generates a sector-specific variant from your documents. A pharmaceutical manufacturer subject to serialisation and an electronic components maker are not assessing the same things.
How do we compare several plants against each other?
The same framework is rolled out to each site, then scores are compared theme by theme. AI groups common gaps into a cross-site roadmap, which avoids funding the same action ten times across ten sites.
Does the assessment prepare us for the digital product passport?
It lays the groundwork. The dedicated theme compares the regulatory data expected against what is actually available in your systems, and the gap feeds the action plan with a cost and a timeline.
Where is the data hosted?
In France, with OVH, with backup at Scaleway. No transfer outside the European Union. The AI models used can be selected, including from European solutions.