How to Test and Assure a Digital Product Passport

Executive Summary

An organisation can build every component of a Digital Product Passport capability correctly and still be unfit to deploy it. The integration works. The validation rules fire. The evidence repository holds current certificates. The passport page renders. The data carrier resolves. Every component passes its own test, and the capability as a whole has never been tested at all.

That gap is what this article addresses. The preceding Implementation articles established how an organisation prepares (How Should Organisations Prepare for Digital Product Passports?), how it sequences delivery (How to Build a Digital Product Passport Implementation Roadmap), how it brings suppliers into scope (How to Prepare Suppliers for Digital Product Passports), how it controls information (How to Validate Digital Product Passport Data) and how it governs supporting material (How to Manage Evidence for Digital Product Passports). This article asks the question that follows all of them: how does an organisation determine whether the resulting capability is actually ready to deploy and scale?

The answer set out here is The DPP Assurance Model, a vendor neutral framework in two parts. Eight assurance domains define what is assured: requirements, data, identity and association, evidence, integration and process, access and security, lifecycle and change, and operations. A seven step assurance cycle defines how assurance is performed: scope, acceptance criteria, test design and execution, assurance evidence, defect assessment, remediation and retest, and a governed decision. The cycle concludes in one of three tieback educational decision states: READY, READY WITH CONDITIONS or NOT READY.

Three ideas carry the article. Assurance is a decision, not an activity, and a decision needs an owner, a scope and a record. Failure behaviour reveals more about production readiness than any successful demonstration, so the negative and exception paths deserve at least as much design effort as the happy path. And assurance is never finished: material change to architecture, product scope, regulation, suppliers, identity, publication, security or evidence control triggers proportional reassurance rather than a one time sign off that ages quietly into fiction.

Table of Contents

• Definition
• Why DPP Testing and Assurance Matter
• Testing vs Validation vs Assurance
• The DPP Assurance Model
• Domain 1: Regulatory and Requirements Assurance
• Domain 2: Data Assurance
• Domain 3: Identity and Association Assurance
• Domain 4: Evidence Assurance
• Domain 5: Integration and Process Assurance
• Domain 6: Access, Security and Publication Assurance
• Domain 7: Lifecycle and Change Assurance
• Domain 8: Operational Assurance
• The Seven Step Assurance Cycle
• Ready, Ready With Conditions and Not Ready
• Building an Assurance Decision Record
• Requirements Traceability
• Testing Failure Paths
• End to End Testing
• Pilot Assurance
• Regression Testing and Reassurance
• Assurance Roles and Responsibilities
• Practical Example
• Assurance Metrics
• Common Mistakes
• Frequently Asked Questions
• Key Takeaways
• Related Glossary Terms
• References

Definition

Two boundaries in that definition matter. Testing is an activity that produces findings. Assurance is a decision that consumes them. And the scope of the decision is explicit: an implementation is never assured in the abstract, only for a stated set of products, markets, audiences and requirements.

Why DPP Testing and Assurance Matter

A passport is a published, structured, addressable, machine readable statement about a product, made available to audiences the organisation does not control, at a scale it cannot manually review. That combination changes the consequence of error.

Four practical reasons make assurance unavoidable.

Errors are public and persistent. An incorrect figure in an internal spreadsheet is a data issue. The same figure published against a product identifier, resolvable by anyone with the data carrier, retrievable by market surveillance and comparable across a category, is an exposure. It is also durable: it may be scanned, cached, screenshotted and cited long after correction.

The failure surface is wider than the build surface. Most DPP defects found in production are not coding errors. They are association errors, permission errors, expiry handling errors, event ordering errors and unhandled exceptions in flows nobody designed a test for, because nobody designed the flow either.

Scale removes manual compensation. A pilot of fifty products can be checked by hand. A hundred thousand cannot. Whatever manual inspection is compensating for during a pilot must be replaced by a tested control before scale, or it silently disappears.

Readiness is a decision somebody owns. In the absence of an explicit decision, deployment happens by momentum: a date arrives, the demonstration goes well and the capability goes live. The purpose of the assurance cycle is to make readiness a recorded judgement with a named owner, a stated scope and a reproducible basis.

Testing vs Validation vs Assurance

Four related questions are routinely conflated, and the conflation is the single most common cause of premature deployment.

These are related. They are not synonyms. Validation operates on an information element. Evidence management operates on the material supporting a claim. Testing operates on the capability. Assurance operates on the decision.

The operating chain

A Digital Product Passport should not be considered production ready merely because the passport page renders correctly or an interface returns data. Assurance tests the complete chain:

SOURCE → INTEGRATION → IDENTITY → VALIDATION → EVIDENCE → DPP SERVICE
       → ACCESS → AUDIENCE → LIFECYCLE CHANGE → OPERATIONAL RESPONSE

Every link in that chain can be individually correct while the chain as a whole is broken, and the last two links, lifecycle change and operational response, are the ones most often omitted from test scope entirely. The implementation must also behave correctly when something goes wrong.

The DPP Assurance Model

The framework has two parts that are used together.

Part A, the eight assurance domains, defines what is assured. They are not sequential stages and not a maturity ladder. They are simultaneous fields of concern, each with its own failure modes, each requiring coverage proportional to risk.

Part B, the seven step assurance cycle, defines how assurance is performed. The cycle is applied across the domains, not after them, and it repeats whenever a reassurance trigger occurs.

The domains without the cycle produce a checklist nobody acts on. The cycle without the domains produces energetic testing of whichever areas the team already understands. Used together, they produce a bounded, traceable, recorded readiness decision.

The Eight Assurance Domains

Domain 1: Regulatory and Requirements Assurance

Test whether the implementation reflects the scope and requirements the organisation actually defined.

Coverage areas include applicable product scope, jurisdiction and market, known regulatory requirements, delegated act dependencies, access requirements, information requirements, effective dates, recorded assumptions and requirement traceability.

The characteristic questions are:

• Are implemented requirements traceable to their source, and is that source identified as legislation, a delegated act, a standard, a conformity route, a contract or an internal control?
• Are assumptions clearly distinguished from enacted obligations, and can somebody list the assumptions the implementation currently depends on?
• Can a requirement change without becoming invisible technical debt, or does a rule change quietly leave a stale implementation behind it?

Where product category requirements are not yet final, the correct assurance outcome is not silence. It is a recorded assumption with an owner and a review trigger.

Domain 2: Data Assurance

Test whether the required information exists, comes from the intended source, passes applicable validation, has appropriate ownership, is current, is correctly associated and handles missing or invalid states predictably.

This domain builds on the product data quality model (TBF-025) and the DPP Data Validation Control Model (TBF-033) rather than recreating them. Its assurance contribution is to test that those controls are actually operating in the deployed capability: that the rules configured in a design document are the rules running in the pipeline, that a failed rule blocks what it should block, and that an element sourced from the wrong system is detected rather than silently accepted.

The most informative data assurance tests are the ones about absence. What is published when a required element is missing? Is the passport suppressed, is the element omitted, is a placeholder shown, or is a stale prior value retained? Any of those may be a defensible design decision. None of them should be a surprise discovered in production.

Domain 3: Identity and Association Assurance

Test whether information is attached to the correct product, model, variant, batch, lot, component, material, facility, supplier and lifecycle context.

This domain tests both the product identifiers themselves and the relationships between them. A technically valid value associated with the wrong product is still a serious failure, and it is a failure that no amount of format validation will detect: the value passes every rule it is measured against, and describes something else.

Representative tests include resolving a data carrier to the intended item, confirming that a variant does not inherit an inapplicable sibling’s data, confirming that batch level information is not presented as model level information, confirming that component or material level claims are not silently promoted to product level, and confirming that a facility scoped record is not applied to products the facility did not produce.

Identifier schemes vary by organisation, sector and market. Where an organisation uses a particular scheme, the assurance question is whether resolution, uniqueness and relationship handling behave correctly under that scheme, not whether the scheme itself is the industry favourite. No single identifier standard is universally mandatory across product categories.

Domain 4: Evidence Assurance

Test whether the evidence required for the defined scope is available, correctly associated, validated, reviewed or verified where required, current, appropriately controlled, accessible to authorised users, and updated when it is superseded, revoked or expired.

This builds directly on the DPP Evidence Lifecycle (TBF-034) and does not recreate it. The assurance contribution is behavioural: what does the capability actually do when evidence changes state?

• When accepted evidence reaches its expiry date, does anything happen to the claims that depend on it, or does the passport continue publishing a claim whose support has lapsed?
• When evidence is revoked by its issuer, is there a route by which that revocation reaches the published claim, and how long does it take?
• When evidence is superseded by a revised version, does the association follow the new version, and is the earlier version retained for reproducibility?
• Can an authorised recipient reach evidence they are entitled to see, and only that evidence?

Domain 5: Integration and Process Assurance

Test the complete information flow across the relevant systems: source extraction, transformation, orchestration, interfaces, application programming interfaces, workflow, exception handling, retries, synchronisation, event processing and downstream updates.

The failure conditions matter more than the throughput. Test what happens when a source is unavailable, an interface fails mid transfer, a duplicate event arrives, two authoritative records conflict, an update is delayed beyond its expected window, or processing partially succeeds and leaves the capability in a half updated state.

Partial success deserves particular attention because it produces the least visible damage. A run that fails loudly gets investigated. A run that updates eight of ten attributes and reports success publishes an internally inconsistent passport that nobody is looking for.

Domain 6: Access, Security and Publication Assurance

Test whether the correct audience can access the correct information, and, equally, whether the wrong audience cannot.

Coverage includes public access, restricted access, economic operator access, authority access, authentication where applicable, authorisation, confidentiality, personal data, commercially sensitive information, publication controls and evidence access.

Two test classes are required, and the second is routinely omitted:

Authorised access. Can each intended audience reach the information intended for it, through the intended route, in the intended form?

Unauthorised access. Can someone who should not see restricted information gain access to it: by guessing an address, enumerating identifiers, following a stale link, reusing a superseded credential, requesting an interface directly rather than through the interface layer, or exploiting a permission rule that was correct for one audience and inherited by another?

The critical assurance question is not merely “can the user see the information?” but also “can someone who should not see it gain access?” A capability that answers the first question well and the second question badly is not assured; it is a disclosure incident with a launch date.

Not all passport information is public. Access classifications differ by information type, audience and applicable requirements, and the tests must reflect the classification the organisation has actually defined.

Domain 7: Lifecycle and Change Assurance

Test what happens after initial publication.

Representative scenarios include product data changes, evidence expiry, evidence revocation, supplier change, a lifecycle event, repair, return, recall, regulatory requirement change, access reclassification and identifier relationship change.

The Digital Product Passport must not be tested as a static webpage. A passport is a long lived published surface over information that changes for years after the product leaves the factory. Most of its operating life happens after go live, and almost none of that period resembles the conditions under which it was demonstrated.

Useful questions: how long does a source change take to reach the published passport, and is that latency acceptable and monitored? What happens to a passport when the product is recalled? What happens when a supplier is replaced and the new supplier’s data has a different structure? What happens when the access classification of an element changes after publication, does previously public information become restricted, and does anything about the earlier exposure need recording?

Domain 8: Operational Assurance

Test whether the organisation can actually operate the capability, as distinct from whether the capability functions.

Coverage includes monitoring, alerting, incident handling, exception ownership, supplier remediation, data stewardship, evidence renewal, change management, service performance, support, auditability, escalation and recovery.

The tests here are organisational as much as technical. If an integration stops running overnight, who is alerted, and by what? If a supplier’s evidence expires, who chases it, and what happens if they do not respond? If a passport publishes an incorrect value, who can correct it, how quickly, and what record is left? If the publication service is unavailable, what is the recovery path and what is the acceptable duration?

A capability that works but that nobody can operate is not ready. This domain forms the bridge to a future article on the DPP operating model; here it is assessed as a readiness condition rather than elaborated as a discipline.

The Seven Step Assurance Cycle

Step 1: Define Assurance Scope

Determine and record the products, markets, systems, suppliers, information, audiences, lifecycle scenarios and regulatory requirements included in the assessment, and, by implication, those excluded.

Assurance must have explicit boundaries. An unbounded assurance exercise produces an unbounded decision, which is the same thing as no decision. Recording exclusions is as important as recording inclusions, because the exclusions define what the eventual READY status does not cover.

Step 2: Define Acceptance Criteria

Determine what must be true for the implementation to be considered ready for that scope.

Criteria should be testable, traceable to a requirement or control, owned by a named party, and measurable where measurement is meaningful. “The restricted technical documentation is not retrievable by an unauthenticated request through any published route” is a criterion. “Security is adequate” is an aspiration.

Avoid the criterion that ends every unsuccessful assurance exercise: “it appears to work.”

Step 3: Design and Execute Tests

Create test scenarios across all eight assurance domains, proportional to risk. The design should deliberately include positive scenarios, negative scenarios, boundary scenarios, exception scenarios, lifecycle scenarios, access scenarios and failure and recovery scenarios.

A useful design discipline is to require, for each domain, at least one scenario in which something goes wrong and the capability is expected to respond in a specified way. If a domain has only positive scenarios, its exception behaviour is unspecified, and unspecified behaviour is not a passing result.

Step 4: Capture Assurance Evidence

Record evidence showing what was tested and what actually occurred: test results, logs, data comparisons, validation results, access results, defect records, approval records and scenario outcomes.

Screenshots are legitimate evidence of a rendered state and nothing more. They do not show which data was in the source, what the interface returned, whether the correct record was addressed or whether the result is reproducible. A screenshot supported by the underlying result set, the identifiers used and the recorded execution is assurance evidence; a screenshot alone is a photograph.

Step 5: Assess Defects and Exceptions

Classify findings by significance. Many taxonomies work: CRITICAL, HIGH, MEDIUM, LOW is a common one, and organisations with an established quality or risk taxonomy should use theirs rather than adopting a second. What matters is that the classification is defined, applied consistently and tied to consequence rather than to effort.

For each finding, assess impact, affected scope, regulatory relevance, data impact, access and security impact, availability of a workaround, ownership and remediation plan.

Severity should be driven by consequence, not by how difficult the fix looks. A one line permission misconfiguration that exposes commercially sensitive information is critical. A structural integration weakness that delays a non regulated attribute by a day may be low.

Step 6: Remediate and Retest

Material defects enter a controlled loop:

DEFECT → OWNER → REMEDIATION → RETEST → EVIDENCE → CLOSURE / REMAINING EXCEPTION

A code change, configuration change or process change is a remediation, not a resolution. The defect is resolved when the original scenario has been re-executed and the recorded result demonstrates the intended behaviour. Retesting should also consider whether the remediation could plausibly affect adjacent behaviour, and extend coverage accordingly.

Where a finding is not remediated, it does not disappear; it becomes a recorded exception carried into the decision.

Step 7: Make the Assurance Decision

The cycle concludes with a governed decision, made by a defined owner, for a defined scope, on a recorded basis, and captured in an assurance decision record.

Ready, Ready With Conditions and Not Ready

These are tieback educational decision states. They are not regulatory classifications, and no legislation defines them.

Ready

The capability meets the defined acceptance criteria for the approved scope, with no unresolved issue preventing deployment. READY is always scoped: ready for these products, these markets, these audiences, this requirements baseline.

Ready With Conditions

Deployment may proceed within explicitly defined constraints. Typical conditions include a limited product scope, a limited geography, a temporary manual control, an unresolved low risk issue, additional monitoring or a time bound remediation.

Every condition should carry an owner, a rationale, an affected scope, a due date or review point and a monitoring requirement. A condition without a date is a permanent defect with better manners.

READY WITH CONDITIONS is not a mechanism for approving serious defects with paperwork. If a condition exists because a critical access, regulatory or data integrity control does not work, the honest state is NOT READY.

Not Ready

Material deficiencies prevent responsible deployment for the intended scope. The decision should state the blocking issues, the affected scope, the remediation required, the responsible owners and the trigger for reassessment.

NOT READY for a broad scope is frequently READY WITH CONDITIONS for a narrower one. Reducing scope is a legitimate and often superior response to a failed assurance cycle, because it produces real operational experience while remediation proceeds.

Building an Assurance Decision Record

The assurance decision record is a practical implementation concept, not a prescribed regulatory document. Its purpose is reproducibility: an organisation should be able to explain, months or years later, what was approved, for what, on what basis, by whom, and what was known to be outstanding at the time.

Useful fields include:

Reproducibility is the reason the record exists. A decision that cannot be reconstructed cannot be defended, cannot be audited, and cannot be compared against the state of the capability today, which is precisely the comparison needed when deciding whether a change requires reassurance.

Requirements Traceability

Traceability is what connects a test to a reason. Without it, a test suite becomes an accumulation of scenarios whose original purpose nobody remembers, and which nobody dares delete.

The practical chain is:

REQUIREMENT → IMPLEMENTATION → TEST → RESULT → EVIDENCE → ASSURANCE DECISION

An organisation should be able to walk the chain in both directions. Forwards: this requirement is implemented here, tested by these scenarios, producing these results, supported by this evidence, included in this decision. Backwards: this test exists because of this requirement or control, and if the requirement changes, this is the test coverage affected.

Two failure modes are visible only through traceability. Requirements without tests are requirements the organisation believes it has met without ever checking. Tests without requirements are effort spent on coverage nobody asked for, which is defensible if deliberate and wasteful if accidental.

No particular requirements management tooling is implied. A governed spreadsheet with stable identifiers traces adequately; an expensive tool populated inconsistently does not.

Testing Failure Paths

This deserves disproportionate emphasis, because failure behaviour reveals more about production readiness than any successful happy path demonstration.

Representative failure scenarios:

• Missing required data. A required element is absent at publication time.
• Invalid identifier. A malformed, unknown or retired identifier is presented for resolution.
• Supplier evidence expired. Evidence supporting a published claim passes its validity date.
• Evidence revoked. An issuer withdraws evidence already relied upon.
• Conflicting authoritative sources. Two systems assert different values for the same element.
• Integration unavailable. A source system or interface is down during a scheduled run.
• Stale data. The pipeline runs but delivers information older than its defined tolerance.
• Duplicate lifecycle event. The same event is received twice, out of order, or replayed.
• Incorrect product association. Valid information is bound to the wrong item.
• Unauthorised access attempt. An unauthenticated or wrongly scoped request targets restricted content.
• Restricted information exposed publicly. A permission rule leaks confidential or commercially sensitive content.
• Publication service unavailable. The passport cannot be served when scanned.
• Update partially completed. Some attributes update and others do not.
• Remediation workflow fails. A defect is raised but never routed, owned or actioned.
• Regulatory rule changes. A requirement changes after implementation and the change must be detected.

For each, the assurance question is the same: what is the specified behaviour, is it implemented, is it detected, is it recoverable, and does anyone find out?

End to End Testing

Component testing is necessary and insufficient. Consider a capability where the enterprise resource planning integration works, validation works, the evidence repository works, the DPP service works and the data carrier resolves. Every component passes. None of that proves that the complete journey works correctly together.

End to end scenarios cross multiple assurance domains deliberately. Three representative examples:

Scenario A: New product introduction. A product is created in the system of record, enriched with supplier information and evidence, validated, assigned identity, published, and retrieved by a public user and by an authorised economic operator. Domains: 1, 2, 3, 4, 5, 6.

Scenario B: Evidence expiry during production life. A supplier certificate supporting a published claim expires; the change is detected, the claim’s status is handled per the defined behaviour, the exception reaches an owner, the supplier supplies a renewal, and the passport returns to a supported state. Domains: 4, 5, 7, 8.

Scenario C: Correction after a data error. An incorrect value is identified in production, corrected at source, propagated through validation and publication, and verified in the published passport within the defined latency, with a record of what changed and when. Domains: 2, 5, 7, 8.

Each scenario should have a defined expected outcome per domain, not a single overall pass or fail, because a scenario can succeed functionally while failing operationally, the correction propagated, but nobody was notified and no record was kept.

Pilot Assurance

The implementation roadmap (TBF-031) places pilot deployment at Stage 8. A pilot is the first opportunity to generate operational assurance evidence under real conditions rather than constructed ones.

An assurance useful pilot tests representative products, representative suppliers, real data complexity, realistic access patterns, genuine exceptions, actual operational ownership and lifecycle updates that occur during the pilot window. It should be long enough for at least one change to happen to something.

The temptation is to select the cleanest products, the most cooperative supplier and the simplest market. That produces a pleasant demonstration and no information. A pilot so simple that it cannot expose implementation weaknesses has not reduced risk; it has deferred discovery to the point where discovery is most expensive.

Regression Testing and Reassurance

Assurance is not a one time event. A decision describes a capability at a point in time, and capabilities change.

Triggers that may require partial or full reassurance include a major architecture change, a new product category, a new delegated act, a material regulatory change, a new supplier population, an identity model change, a publication model change, a significant validation rule change, a security change, a major incident and an evidence control change.

Regression should be proportional. Not every change requires repeating every test. A practical approach scopes regression by asking which assurance domains the change can plausibly affect, which requirements trace to those domains, and which scenarios cover those requirements, which is only answerable if traceability was maintained.

A useful default is that changes affecting identity, access or publication behaviour warrant broader regression than changes affecting a single non regulated attribute, because those three areas have the widest blast radius and the least visible failure modes.

Assurance Roles and Responsibilities

Responsibilities matter more than job titles, and the right distribution differs by organisation size, sector and structure.

One structural point is worth stating plainly: the party that builds a capability should not necessarily be the sole authority deciding whether it is adequately assured. Builders are systematically optimistic about their own work, and the incentive to reach a date is real. That does not mean every organisation requires formal independence, and independent third party assessment is required only where legislation or a conformity route requires it. What it does mean is that the readiness decision should be visible to someone whose judgement is not tied to the delivery date.

Practical Example

Assurance Metrics

Useful measures describe coverage, severity and behaviour rather than volume.

One caution outranks the rest. “95% of tests passed” may be entirely unacceptable if the failed 5% contains critical access or regulatory controls, and entirely acceptable if it contains cosmetic findings in an excluded scope. A pass percentage is a summary of effort, not a statement of readiness. Severity distribution and domain coverage carry the information; the headline percentage mostly carries comfort.

Common Mistakes

Frequently Asked Questions

Does any regulation prescribe this assurance model?
No. The DPP Assurance Model is a tieback educational framework. Legislation and delegated acts establish requirements about products and information; how an organisation tests and assures its own implementation is an enterprise control, unless a specific conformity assessment route imposes requirements in a particular context.

Are READY, READY WITH CONDITIONS and NOT READY regulatory statuses?
No. They are educational decision states used to make an internal readiness judgement explicit and recordable. They carry no legal meaning.

Is there a universal DPP testing standard?
No single universal standard governs Digital Product Passport implementation testing across all product categories. Sector standards, conformity requirements and enterprise quality frameworks may apply in particular contexts.

Does every product require identical tests?
No. Test depth should be proportional to product scope, regulatory exposure, claim significance, audience, data complexity and the number of systems and suppliers involved.

Does assurance require independent third party assessment?
Not universally. Independent assessment is required where legislation or a conformity route requires it. Otherwise the appropriate degree of independence is an organisational judgement, informed by risk rather than applied uniformly.

How is this different from the validation model in KB-0033?
That model asks whether specific information satisfies its rules before publication. This framework asks whether the whole capability behaves as intended, including access, identity, evidence currency, lifecycle change, integration reliability and operations. A passport can contain entirely valid data and still fail assurance.

What is the difference between claim evidence and assurance evidence?
Claim evidence supports product information or a claim, and is governed by TBF-034. Assurance evidence supports the conclusion that the implementation behaved as tested during a specific test cycle, and is governed by this framework. They are stored, owned and retained for different reasons.

How often should reassurance happen?
On trigger rather than on schedule, with a periodic review as a backstop. The triggers listed in this article, architecture, scope, regulatory, supplier, identity, publication, validation, security, incident and evidence control changes, are more reliable than an annual date.

Can a capability be READY for one market and NOT READY for another?
Yes, and recording that distinction is one of the main reasons the decision is scoped. Narrowing scope is often the most responsible outcome of a cycle that surfaced material findings.

Key Takeaways

Related Articles

• How to Build a Digital Product Passport Implementation Roadmap
• How to Manage Evidence for Digital Product Passports
• How to Operate a Digital Product Passport Programme
• How to Prepare Suppliers for Digital Product Passports
• How to Validate Digital Product Passport Data
• How Should Organisations Prepare for Digital Product Passports?
• How to Govern a Digital Product Passport Programme
• Building an Enterprise Digital Product Passport Architecture

Related Glossary Terms

• Digital Product Passport
• Product Data Quality
• Product Data Governance
• Product Data Stewardship
• Authoritative Source
• System of Record
• Product Master Data
• Data Architecture
• Product Identifier
• Product Lifecycle
• Product Traceability
• Economic Operator
• Delegated Act
• Conformity Assessment

Related Docs

• Implementation
• How to Manage Evidence for Digital Product Passports
• How to Validate Digital Product Passport Data
• How to Prepare Suppliers for Digital Product Passports
• How to Build a Digital Product Passport Implementation Roadmap
• Building an Enterprise Digital Product Passport Architecture
• How Product Data Moves Through the Supply Chain

References

• Regulation (EU) 2024/1781 establishing a framework for the setting of ecodesign requirements for sustainable products, including the Digital Product Passport provisions, Official Journal of the European Union: https://eur-lex.europa.eu/eli/reg/2024/1781/oj
• Regulation (EU) 2023/1542 concerning batteries and waste batteries, including the battery passport provisions, Official Journal of the European Union: https://eur-lex.europa.eu/eli/reg/2023/1542/oj
• Regulation (EU) 2019/1020 on market surveillance and compliance of products, Official Journal of the European Union: https://eur-lex.europa.eu/eli/reg/2019/1020/oj
• Decision No 768/2008/EC on a common framework for the marketing of products, including conformity assessment modules and technical documentation obligations, Official Journal of the European Union: https://eur-lex.europa.eu/eli/dec/2008/768/oj

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