Data Quality as a Key Success Factor

Why the Digital Product Passport Is Failing Due to Poor Data

The Digital Product Passport (DPP) is considered one of the central pillars of the European sustainability strategy. In the future, companies will be required to provide detailed information on origin, materials, repairability, recyclability, and CO₂-footßprint of their products.

The vision behind this is clear: greater transparency throughout the entire value chain.

But in practice, it quickly becomes apparent: The biggest challenge is not the technology itself, but the quality of the underlying data.

Many companies already have modern systems, powerful interfaces, and digital platforms. What is often missing, however, is consistent, complete, and reliable product data. This is precisely what determines whether a digital product passport succeeds or fails.

Why Data Quality Is Critical for the DPP

A Digital Product Passport aggregates information from a wide variety of sources: ERP systems, supplier databases, Excel files, PIM systems, production systems, or external platforms. If this data is incorrect or incomplete, massive problems arise:

• Incorrect or contradictory product information
• Missing sustainability data
• Inconsistent information across different channels
• High manual maintenance effort
• Difficulties with regulatory requirements

The DPP highlights what has been a problem in many companies for years: poor master data quality.

Typical sources of errors in product data

Inconsistent data structures

A common error lies in inconsistent naming conventions and formats. While a product is maintained as “Aluminum” in one system, another system simply lists it as “Alu.” Units of measurement differ, attributes are named differently, or value formats vary.

Such inconsistencies are critical for the Digital Product Passport, as data must be processed and exchanged in a standardized manner.

Duplicates and redundant data records

In many companies, identical products exist multiple times in the system—sometimes with different information. These duplicates often arise due to missing processes or isolated data maintenance across different departments.

The result:

• Unclear data basis
• Higher maintenance costs
• Incorrect routing in shops, marketplaces, or DPP platforms

Missing attributes

Sustainability and material information, in particular, is often completely missing. While companies possess technical product data, they lack structured information regarding:

• Recyclability
• CO₂-values
• Supply Chain Information
• Repair instructions
• Material compositions

However, the Digital Product Passport requires precisely this transparency.

Technology alone does not solve the problem

Many companies initially invest in new software solutions or interfaces. But without clean data, the benefits remain limited.

A modern system cannot automatically correct poor-quality data. Instead, errors are simply spread more quickly—across stores, platforms, and in the future also via the Digital Product Passport.

That is why successful digitalization always requires a clear data strategy.

Governance structures as a foundation

Data quality does not happen by chance. It requires clear responsibilities and defined processes.

Key elements of a data governance strategy are:

Clear responsibilities

Who is responsible for:

• Product attributes?
• Sustainability data?
• Approvals?
• Data maintenance?
• Quality controls?

Without clear responsibilities, inconsistencies and information gaps arise.

Uniform standards

Companies should define binding rules:

• Required attributes
• Naming Conventions
• Data Formats
• Classifications
• Translation Guidelines

Only standardized data can be processed efficiently and used automatically.

Defined approval processes

Product data should not be published without being reviewed. Effective workflows help identify errors early on and maintain consistently high quality.

Automation reduces manual effort

Manually maintaining thousands of product data entries is error-prone and expensive. That is why automation is becoming a key success factor.

Modern systems enable:

• automatic validations
• Required field checks
• Duplicate detection
• rule-based data enrichment
• Automated imports from supplier systems

This not only reduces the effort involved but also significantly lowers the error rate.

Continuous quality control is particularly important. Data quality is not a one-time project, but an ongoing process.

The role of PIM systems such as Pimcore

A Product Information Management System (PIM) often forms the central foundation for high-quality product data.

Solutions like Pimcore help companies:

• consolidate data sources
• Centrally manage product information
• Standardize data structures
• Automate workflows
• Enforce quality rules

Centralized data management is indispensable, especially in the context of the Digital Product Passport.

Pimcore offers the advantage of flexibly combining different data types—from technical product data to sustainability and supply chain information.

In addition, data can be automatically distributed across various channels:

• Online stores
• Marketplaces
• Apps
• Partner Portals
• DPP Platforms

This creates a consistent and scalable database.

Data quality becomes a competitive advantage

The Digital Product Passport is far more than a regulatory requirement. Companies with high data quality benefit in the long term from:

• more efficient processes
• faster product launches
• lower error costs
• better customer experience
• greater transparency
• better scalability

At the same time, clean data lays the foundation for further digital initiatives—from AI applications to automated supply chain processes.

The success of the Digital Product Passport depends not primarily on the technology, but on the quality of the data.

Companies that invest today in clean data structures, governance processes, and central platforms such as Pimcore lay the foundation for sustainable digitalization and regulatory compliance.

Because in the end, the following applies:
A digital product passport is only as good as the data that fills it.