PIM for Digital Product Passports (DPP): Integrating LCA data & carbon footprints

In our Product Data X-Ray, Carbon Footprint & Life Cycle Assessment (LCA) is one of the criteria used to assess product data readiness for DPP. We evaluate the availability of environmental data, how accurately it is linked to the relevant product, and whether it can be reused across additional channels.

ESPR requires the data made available through the DPP to be accurate, complete, and up to date. The detailed scope of information, the data carrier, and the level of product identification – model, batch, or individual item – will be defined for specific product groups through delegated acts.

In July 2026, the technical architecture of the DPP gained further definition. On 20 July, the European Commission launched the Digital Product Passport registry together with its test environment. The registry stores unique identifiers and required metadata, while the full product data remains in decentralized source systems. Registration can be handled through both a user interface and an API. On 15 July 2026, references to six harmonized DPP standards were also published, covering areas including identifiers, data carriers, APIs, data exchange, data storage, and system interoperability.

Digital Product Passport (DPP) provides access to the required product information, while PIM (Product Information Management) serves as the layer for managing, validating, and publishing approved product data.

This builds on the architecture described in our previous Tandemite article, where PIM acts as the central hub for information from ERP, PLM, DAM, supplier systems, and other sources.

Why PIM is essential for your DPP strategy and carbon footprint tracking

ESPR is Regulation (EU) 2024/1781 on ecodesign requirements for sustainable products. It establishes the framework for ecodesign requirements and the Digital Product Passport, while detailed requirements for individual product groups will be defined through delegated acts. These may specify, among other things, the scope of data included in the passport, the level of product identification, access rules, and permissions for updating information. ESPR also allows for parameters such as recycled content and environmental footprint, including carbon footprint data in the Digital Product Passport where required for a specific product group.

Preparing for DPP requires a well-designed data architecture. PIM can serve as the central layer for managing product information, helping organizations structure, validate, and prepare data for publication in line with DPP requirements. Every LCA or PCF result should be linked to a specific product, data source, calculation method, assessment scope, and date of the most recent update. The table below shows which information the system needs to connect with each result so that the data can be used reliably across DPP, ESG reporting, and other channels.

This is where PIM can become the Single Source of Truth for approved product information. In a well-designed architecture, environmental data remains in the systems best suited to creating and maintaining it. Engineering data may come from PLM, BOM data from engineering systems, purchasing and supplier information from ERP, documents from DAM, and LCA or PCF calculations from specialist tools. PIM consolidates the result and its context at the product level, links it to the correct SKU or variant, and controls which data is ready for publication.

This model fits the nature of LCA, which includes data inventory, impact assessment, interpretation, and reporting. PIM serves as the management and publishing layer for product information, while LCA or PCF calculations remain in specialist tools.

In practice, the responsibilities can be divided as follows:

This division of responsibilities supports an effective PIM strategy, with each system responsible for the data and processes it is designed to handle. It also supports product compliance (EU compliance), as every published parameter can be traced back to its source, methodology, version, and responsible data owner. ESPR also requires interoperable data formats based on open standards, enabling machine-readable access, search, and data exchange without dependence on a single technology provider.

Integrating PIM with LCA data and carbon footprint metrics

Integrating PIM with an LCA tool makes it possible to incorporate approved environmental data into the same product information model that feeds the DPP, e-commerce platforms, B2B catalogs, partners, and other channels.

LCA-to-PIM synchronization should include the calculation result together with its context: methodology, data sources, assessment scope, version, and validity period. Product Life Cycle Assessment (LCA) evaluates aPCF  product’s life cycle by defining the goal and scope, compiling an inventory of inputs and outputs, assessing potential environmental impacts, and interpreting the results. Product Carbon Footprint (PCF) focuses specifically on one impact category: climate change. ISO 14067:2018 limits PCF to the climate change category, while a full LCA can cover a much broader range of environmental indicators.

This means that a PIM system supporting DPP and carbon footprint data should store each result together with the information needed to interpret it correctly.

Key LCA metrics and environmental data to track

The environmental data model in PIM should cover multiple dimensions:

In the EU’s Product Environmental Footprint (PEF) method, the environmental profile covers 16 impact categories: climate change, ozone depletion, human toxicity – cancer and non-cancer effects, particulate matter, ionizing radiation, photochemical ozone formation, acidification, three types of eutrophication, freshwater ecotoxicity, land use, water use, and the use of mineral/metal and fossil resources. For the climate change category, the key indicator is GWP – Global Warming Potential, expressed in kg CO₂e.

The scope of LCA indicators published in the Digital Product Passport will be defined by the delegated act applicable to the relevant product group. ESPR provides a catalogue of possible parameters, including carbon footprint and environmental footprint.

The data model should also account for Environmental Product Declarations (EPD) as supporting documentation for environmental product data. Since June 2026, the second edition of ISO 14025:2026 has been in force, setting out principles and requirements for Environmental Product Declarations and referring to ISO 14040 and ISO 14044 for their development. An EPD can serve as a source document or supporting evidence for environmental data linked to a product. The scope of information published in the DPP will depend on the requirements applicable to the relevant product group.

Similar care is needed with ESG Scope 3 reporting. The GHG Protocol Product Standard addresses emissions across the full life cycle of a specific product, while Scope 3 reporting operates at the level of an organization’s value chain. This leads to an important practical rule: structured PCF data in PIM can support ESG and Scope 3 reporting, provided that the appropriate boundaries, allocation rules, and accounting methodology are maintained. PCF describes the carbon footprint of a specific product, whereas Scope 3 covers emissions across the organization’s value chain, so product-level data needs to be recalculated and aggregated appropriately before it is used for reporting.

In July 2026, the European Commission also acknowledged that the availability of datasets fully compliant with Environmental Footprint requirements remains limited and published transitional rules for the use of alternative datasets for 2025-2028. PIM should therefore store each LCA result together with the source, version, quality, and provenance of the data used in the calculation.

End-to-end data centralization: From raw materials to finished products

PLM may contain product composition data, ERP may hold supplier and purchasing data, BOM may define the exact components, suppliers may provide recycled content data or material-level PCF results, the LCA tool may contain emission factors and calculation results, and DAM may store verified EPDs.

A practical integration architecture may therefore look like this:

Suppliers + ERP + PLM/BOM + environmental data sources → LCA/PCF engine → PIM → DPP/API + e-commerce + B2B catalogs + ESG reporting

DAM runs in parallel as the repository for supporting documents – EPDs, certificates, verification reports, and declarations – linked to the relevant product object in PIM.

PIM becomes the Single Source of Truth for approved product information intended for downstream distribution, while ERP, PLM, and LCA tools remain the source systems for their respective domains. This is particularly important in the context of ESPR, which requires the DPP to relate to a specific model, batch, or individual item, depending on the applicable delegated act, and for the data to remain complete and up to date.

In practice, this means that for every environmental result, PIM should be able to maintain the following relationship:

product → variant → BOM version → supplier/material → LCA assessment → PCF/GWP result → source document → DPP version

In this model, DPP data management in PIM covers the full process: data source, versioning, validation, product assignment, and publication.

“Carbon footprint data becomes valuable when a company can accurately link it to the right product and its current version. With thousands of products and frequent changes in materials or suppliers, this is where PIM helps structure the entire process and automatically deliver up-to-date data to the DPP.” - Maciej Pałubicki, CEO, Tandemite

This also changes how product carbon footprint monitoring should be approached. PCF is a versioned calculation result based on a defined set of input data. If the supplier changes, the share of recycled material changes, the weight of a component changes, the energy source changes, or another input relevant to the selected LCA methodology changes, the result may need to be recalculated. ISO 14044 shows that LCA is based on a defined scope, inventory, and impact assessment, so changes in input data can affect the outcome.

Automating data exchange: APIs, multi-channel distribution, and GS1 Digital Link

Product data automation becomes especially important when PIM manages thousands of SKUs and environmental indicators can change along with materials, suppliers, or product design revisions.

Since July 2026, there has been a much clearer technical reference point. The European Commission has published references to six DPP product data exchange standards, covering identifiers, data carriers, APIs, storage, and interoperability:

The standards were developed to support the requirements set out in Articles 10 and 11 of the ESPR, and references to them were published in the Official Journal of the European Union on 15 July 2026.

PIM integration with DPP should be built around APIs, identifiers, and structured data exchange based on open standards from the outset.

APIs can support two main data flows:

LCA → PIM: once the calculation is complete, the LCA tool sends the PCF result, relevant indicators, methodology, date, version, and source report identifier to PIM.

PIM → DPP: once a record has been approved through the workflow, PIM publishes the relevant attributes to the DPP service, while the required registration or update can be handled through the European Commission registry API. The registry, launched on 20 July 2026, supports both a user interface and an API. The Commission also provides a semantic repository containing machine-readable data models, definitions, and vocabularies.

GS1 Digital Link can also form part of this architecture. The GS1 standard allows identifiers such as GTIN to be encoded in a format that can be used in a data carrier and linked to online information. Within the GS1 identification hierarchy, a product identifier can also be combined with a batch/lot or serial number, which is particularly relevant when a DPP operates at batch or individual-item level.

GS1 Digital Link is one of the standards that can support DPP architecture. Specific requirements for product identification and data carriers will be defined by the applicable delegated act. ESPR allows different solutions that comply with the relevant standards, while EN 18220:2026 provides the horizontal standard for DPP data carriers.

Technical challenges: SKU variant management vs. ESPR compliance

One of the key challenges in implementing DPP in a PIM system is the difference between a commercial SKU and the actual history of the product.

Consider an office furniture manufacturer selling a chair model under the SKU CHAIR-420-GR. During the first half of the year, the chair frame is made from aluminum supplied by Supplier A. The manufacturer then changes suppliers, and subsequent batches use aluminum containing 20% recycled material.

From the customer’s perspective, it may still be the same model with the same internal SKU. From an environmental data perspective, however, there are now two product versions based on different materials and PCF calculations.

The PCF values below are entirely fictional and are included only to illustrate the mechanism. They do not imply that using 20% recycled material automatically results in a specific reduction in emissions.

Both PCF values must remain linked to the correct product versions and their respective validity periods.

If earlier units are still on the market, PIM needs to know which version of the result applies to which physical production batch. Otherwise, a customer scanning the passport of an older product could receive environmental data calculated for the newer material version.

ESPR addresses this type of scenario by leaving it to the relevant delegated acts to determine whether the DPP for a specific product group operates at model, batch, or individual-item level. Where a new DPP is created for a product that already has a previous passport, ESPR provides for linking the new passport to the previous one.

A PIM system supporting the Digital Product Passport should therefore distinguish at least between:

SKU ≠ product version ≠ production batch ≠ BOM version ≠ environmental data version ≠ DPP identifier

Whether a material change also requires a new GTIN is a separate consideration. Under GS1 rules, a change in formulation or functionality requires a new GTIN when it affects legally required declared information and the brand owner expects customers or supply chain partners to distinguish between the versions before and after the change. When switching to a material containing 20% recycled content, the applicable regulatory requirements, GS1 rules, and product identification approach should therefore be reviewed before determining whether a new GTIN is required.

A well-designed workflow could look like this:

supplier or BOM change → event sent to the LCA tool → new PCF/LCA calculation → new assessment version stored in PIM → validation → approval → link to the relevant version/batch → update of data published in the DPP

If the applicable delegated act requires the DPP to operate at batch level, PIM should link the specific batch/lot to the correct version of the environmental data. If identification at individual-item level is required, serialization is added. GS1 similarly distinguishes between product type identification, batch-level identification using GTIN + batch/lot, and individual-item identification using GTIN + serial number.

In this model, product carbon footprint monitoring becomes an ongoing part of product data lifecycle management.

How to prepare your PIM system for environmental data collection

Preparing PIM for DPP should start with designing a data model capable of handling different types of environmental information and adapting to future requirements introduced through delegated acts.

Attribute data modeling for Digital Product Passports

The most future-proof approach is to structure environmental data as separate, interconnected entities that form a relational product information model. If an organization uses a platform designed for managing diverse data types, the model may include entities such as Product/SKU, Variant, Material, Component, Supplier, BOM, Environmental Assessment, LCA Indicator, PCF, EPD/Certificate, Data Source, and DPP Record.

An LCA record in PIM should link the result to both the product and the context of the calculation, including the product and assessment identifiers, indicator, value and unit, methodology, system boundaries, data period, BOM version, source, supporting documentation, verification status, and validity period. This makes it possible to add further LCA indicators without changing the fundamental product structure. This flexibility is important because environmental information requirements under ESPR may vary between product groups and will be further specified in delegated acts.

Version control, historical logging, and audit trails

The second pillar is a complete change history. For every environmental data point, the organization should be able to determine who entered it, which system it came from, what was changed, when the change took effect, which documentation supported it, and which version of the information was published at any given time.

A complete change history also supports compliance with ESPR requirements for data accuracy and reliability, as well as access control over data entry and updates. EN 18221:2026 specifically addresses the storage, archiving, and persistence of DPP data.

For EU compliance, validation rules should therefore be applied before publication:

Access management is equally important. ESPR provides for delegated acts to define which user groups can access specific DPP data. The scope of information made available may therefore vary by audience. Consumers, business partners, recyclers, service providers, and market surveillance authorities may receive different data sets based on their respective access rights. PIM should be able to generate different views of the same record from a single, controlled set of information.

Implementing DPP in a PIM system primarily means building the data and process layer that supplies the passport with the right, approved information.

Conclusion: Your DPP implementation roadmap

Preparing PIM for the Digital Product Passport and environmental data is best approached in stages. Architecture work can begin now because many of the key building blocks are already known: ESPR defines the core principles of DPP, references to six harmonized technical standards have been in place since July 2026, and the DPP registry and its test environment are already operational. The detailed data requirements for each product group will still need to be aligned with the applicable delegated act.

A practical roadmap could look like this:

The best pilot candidate is a product with a well-defined BOM, reliable supplier data, and existing LCA or PCF results, allowing the entire process to be tested from source data through to publication. This provides a practical way to verify whether LCA-to-PIM synchronization works when a supplier, material, document, or product version changes.

During the design stage, it is also important to clearly define the role of the technology partner in a PIM project. The implementation partner can design the data model, APIs, workflows, and automation, while the organization remains responsible for defining data owners, authoritative sources, and approval rules. For more complex architectures, selecting a PIM implementation partner with experience in product data modeling and PIM integrations with ERP, PLM, DAM, and external systems is equally important.

DPP should be treated primarily as a product data and data architecture initiative. A QR code or other data carrier provides access to information whose reliability depends on the underlying BOM data, supplier systems, LCA and PCF calculations, EPD documentation, product identifiers, version history, and approval processes.

A well-designed PIM system for the Digital Product Passport brings these elements together in a controlled information model. As a result, a single change – such as a new material, a different supplier, or an updated PCF result – can trigger an automated process for validating and updating data across the DPP, e-commerce, B2B catalogs, and reporting systems.

The key role of PIM in the DPP context is to keep the correct, approved, and up-to-date environmental result linked to the right product and publish it in the appropriate version for the appropriate audience. This model supports ESPR requirements for data accuracy and currency while also enabling an interoperable DPP architecture.

Check whether your product data is ready for DPP

Product Data X-Ray helps assess product data readiness across key areas, including Carbon Footprint & Life Cycle Assessment (LCA). The analysis identifies gaps in data, integrations, and processes and shows where DPP preparation should begin.