Most companies approach the Digital Product Passport as a compliance deadline to survive. The organizations gaining competitive ground are treating it as the data infrastructure project they should have started years ago — one that pays back through every product channel, not just the regulatory checkbox.
In this PIMvendors.com webinar, Stephan Spijkers and Chris Jobse break down the DPP’s seven core data requirements, map the commercial value embedded in compliant product data, and walk through a practical six-step implementation path from scattered spreadsheets to a live, machine-readable passport. The session is built for brands, importers, and agencies navigating DPP obligations across textiles, batteries, machinery, and packaging — and for anyone who has not yet found a clear starting point.
Speakers:
Stephan Spijkers – Co-Founder, PIMvendors.com
Chris Jobse – Co-Founder, PIMvendors.com
Watch the Full Session
The full session is available on the PIMvendors YouTube channel. If your organization is facing DPP deadlines and still working out where the data actually lives, this session addresses the practical questions most compliance guides skip.
Key Takeaways
60–80% of the data a DPP requires already exists inside your organization. It sits in ERP systems, PLM environments, procurement inboxes, and PIM solutions — scattered, but present. The primary challenge is surfacing and structuring that data, not generating it from scratch. Organizations that start from this premise move faster and invest more accurately than those who scope the DPP as a data creation project.
The DPP mandates seven distinct data categories, and most companies already hold the majority. Product identification, compliance certifications, bill of materials, environmental impact (carbon footprint, water, energy), circularity and repairability, supply chain provenance, and end-of-life instructions all need to be machine-readable and role-accessible. The data is typically there — in PDFs, mail threads, and disconnected systems — but it is not yet in a format that meets the DPP’s structural requirements.
Treating DPP as a one-off project guarantees the data goes stale the moment it launches. A project-based approach produces a passport for today’s catalog. It does not produce the process, governance, or system architecture that keeps new products compliant as they enter the assortment. Building DPP compliance as a governed, repeatable workflow — anchored in a PIM or MDM — is the only model that scales across product launches and future regulatory mandates.
Compliant product data generates commercial return across every channel. The bill of materials required for DPP compliance becomes the foundation for spare parts sales, after-sales service, cross-sell relationships, and customer-facing content that competes on transparency rather than price. Organizations that capture this data once and reuse it across channels consistently see lower return rates, stronger service margins, and higher conversion on product content.
DPP and PPWR share the same underlying data foundation. Packaging regulation under PPWR draws on many of the same material, supply chain, and environmental data points the DPP requires. Organizations that build a governed single source of truth for DPP purposes can extend that foundation to cover incoming mandates without starting from scratch each time. The investment compounds across regulations, not just within one.
In most product categories, DPP compliance applies at category level, not individual SKU. One passport covers a product category — not every color, size, or variant within it. This significantly reduces the scope of the initial build and makes a focused pilot far more achievable than most teams initially assume. Starting with one best-selling product line establishes the governance model and surfaces real gaps before full-catalog scope is introduced.
The DPP is both an end destination and a starting point in the customer journey. A compliant passport closes the loop on circularity and end-of-life — but it also opens a channel for spare part identification, repair guidance, reordering via QR scan, and verified sustainability claims that premium buyers are increasingly willing to pay for. Organizations that design their DPP implementation with both use cases in mind extract significantly more value from the same data investment.
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