Excel import is an excellent start, but at high volume (thousands of products a month) the Digital Product Passport has to be automated. This is where ERP/PLM integration comes in: the product data lives where it already resides — in SAP, in Teamcenter, in an in-house system — and flows from there into the DPP.
Where does DPP data live today?
DPP fields are rarely in one place:
- ERP (for example, SAP): material master, GTIN, supplier, quantity.
- PLM (for example, Siemens Teamcenter): technical parameters, BoM, material composition.
- GHG/ESG system: carbon footprint, energy data.
- Supplier spreadsheets and email: recycled content, due diligence.
- Document store: declaration of conformity, certificate, test report.
The point of integration is to connect these and harmonise them according to the DPP schema.
Integration patterns
1. Batch synchronisation
A scheduled export from the ERP → import into the DPP platform → validation → issuance. Simple and robust; a good starting pattern.
2. API-based (near real time)
The DPP platform pulls or receives data from the ERP through API connectors. Scalable and automated; suited to higher volumes.
3. Event-driven
When a product reaches a "ready to place on the market" status, the DPP is generated automatically. The most mature pattern, but the one that needs the most preparation.
Mapping is the key
Most of the work is field mapping: linking the ERP/PLM fields to the DPP schema fields (for example, DIN DKE SPEC 99100, Annex XIII). A good platform:
- validates the incoming data (GTIN, unit of measure, enum),
- flags gaps (gap analysis),
- and documents the mapping (so the certifier can see it too).
Data sovereignty and integration
ERP integration often touches sensitive internal systems. That is why the deployment model matters: with on-premise deployment the DPP platform sits behind the firewall and integrates directly with the ERP — the data never leaves the network.
How to get started
1. Data-source inventory: which DPP field comes from which system? 2. Pilot on one product type: batch first, with manual mapping. 3. Refine validation: based on the recurring errors. 4. Automate: API or event-driven, when the volume justifies it. 5. Two-way flow: Excel export and re-import for manual correction, without duplication (stable identifier).
Frequently asked questions
Do I need a full SAP project?
Not necessarily. You can start with export and import; API integration comes later, gradually.
What if the data comes from several systems?
The platform unifies it in the mapping; the source systems remain untouched.
Does on-premise make integration harder?
On the contrary — a direct, secure connection to the internal ERP can be built.
Your data where it is — the DPP where it is needed. ReadyPass's API-first architecture fits SAP, Teamcenter and other ERP/PLM systems, in an on-premise or cloud model.
Sources: ESPR (EU) 2024/1781; DIN DKE SPEC 99100. For information only.
