1 · Data layer
ERP (BOM, suppliers, batches), PLM (specs, materials) and MES (production events) capture data at source.
At mid-market scale, the DPP stops being a spreadsheet exercise. Your data lives in ERP, PLM and MES systems, your supplier base is broad, and you need a repeatable, integrated pipeline rather than manual passports. This guide covers the 12–18 month journey from pilot to production.
You don't need everything at once. Build the layers your products actually require, and keep the verification layer optional.
ERP (BOM, suppliers, batches), PLM (specs, materials) and MES (production events) capture data at source.
APIs and middleware move data between systems using standard schemas (JSON-LD, EPCIS).
A validation engine - or blockchain only if multi-party trust demands it - for audit trails.
QR / NFC on products, plus web portals for regulators and partners and a consumer view.
Centralised cloud is usually the right default for mid-market: faster deployment, lower complexity and easier integration than blockchain. Add cryptographic verification only where a specific customer or regulator requires tamper-proof trust.
Deploying across the whole portfolio at once is how programmes stall. Prove it small, then expand.
| Phase | Duration | Focus | Key outputs |
|---|---|---|---|
| 1 · Planning | Months 1–3 | Gap analysis, pilot selection | Scope, budget, data-field map, target SKU |
| 2 · Build | Months 4–8 | IT & supplier integration | ERP/PLM connectors, data model, platform config |
| 3 · Pilot | Months 9–12 | Testing & validation | Live passports on one line, validated outputs |
| 4 · Scale | Months 13–18 | Production rollout | Portfolio coverage, automated validation |
Map affected SKUs to source systems. Identify where BOM, material composition, carbon-footprint and traceability data live - and where they don't.
Standardise product identifiers across systems, define product-level vs. batch-level data, and link supplier, component and material records into a digital chain of custody.
Connect ERP and PLM to your DPP platform with middleware. Use event-driven updates for dynamic data and batch sync for static material data.
Test data capture, QR labelling, access control and regulatory reporting on a limited SKU set and a small supplier group. Fix the bottlenecks you find.
Expand SKU by SKU, onboard more suppliers, and add automated data-validation rules so quality holds as volume grows.
Most of a passport's data originates upstream. Segment suppliers so you spend effort where the spend and risk concentrate.
Roughly 5–10% of suppliers but 60–70% of spend. Formal requirements, joint pilots, contractual data clauses.
20–30% of suppliers. Standardised data templates, group training sessions and progress monitoring.
60–70% of suppliers, small spend. Online resources and industry-average data where specifics are unavailable.
Start supplier communication in month 1–2. Capability-building and first data submissions realistically take 6–12 months, so it must run in parallel with your build - not after it.
You are almost certainly already gathering much of the required data for other obligations. Map these into your DPP data model to avoid duplicate effort.
Aligning to these now keeps your data portable and audit-ready as delegated acts firm up.
The enterprise guide covers global vs. federated architecture, multi-jurisdiction data governance and large-scale supplier programmes.