Product Data Is Only as Strong as Its Weakest Handoff

Manufacturers are distributing product information across an expanding mix of digital and traditional channels. In The Product Data Paradox, Inriver found that 79% of respondents had added digital channels over the previous two years, while more than half were still publishing product information into print catalogs and PDFs.

That means new digital requirements are being layered onto existing ones, increasing the number of formats, approvals, updates, and handoffs product-data teams have to manage.

Inriver surveyed 405 technology, data, and marketing executives at industrial manufacturing and wholesale distribution organizations in the US and Europe for the study. Its Product Data Maturity Index measures how effectively companies can manage product information across increasingly automated and AI-driven operations.

The findings show that manufacturers are advancing those capabilities unevenly. Different verticals lead in different areas, but strengths in product-data operations often sit alongside weaknesses elsewhere in the same product-data process. Across the seven verticals, no industry led on more than one of the capabilities Inriver assessed.

Strength in One Area Does Not Fix the Rest

The vertical analysis from the Index shows why progress in one part of the product-data process can give an incomplete picture of maturity. A company can automate launches, adopt AI, or improve measurement while problems remain in the surrounding systems and workflows.

Building Materials companies provide the clearest example. Roughly four in 10 respondents reported end-to-end automated launches with an audit trail. Yet the vertical posted below-average publish readiness and above-average weekly integration failures.

A similar split appears among companies in the Industrial Equipment and Industrial Materials & Consumables verticals. Those respondents reported the strongest adoption of AI in product-data workflows, but also the most frequent integration failures and the lowest rates of attribution-grade measurement.

Electronics shows the opposite pattern. Just under half of respondents use closed-loop measurement that ties product content to commercial outcomes, the highest rate in the study, while the vertical made the fewest claims of being ready for agentic commerce.

The results show why no single capability measures the whole operation. The harder task is making those improvements reinforce each other across the product-data process.

Manual Workarounds Keep Product Data Moving

One reason those weaknesses can persist without stopping the operation is that employees continue to bridge the gaps manually. They check failed transfers, correct incomplete records, confirm specifications with other teams, and move information between systems when automated processes fall short.

Inriver’s data shows how common that intervention remains: 45% of respondents experience failures between product-data systems at least monthly. One in five encounter them weekly or daily. Only 13.6% have end-to-end product-data automation with an audit trail.

Respondents described spreadsheets sent by email, manual data entry, phone calls to verify specifications, and approval chains dependent on particular employees. Those workarounds can still get a product launched or an update published, but they make the process dependent on people knowing where problems occur and how to fix them.

That can also make the underlying weakness difficult to see. A process may appear successful because the required outcome is eventually delivered, even when substantial manual effort was needed to get there. This helps explain how companies can make real progress in one part of product-data management while still carrying weaknesses.

How Inriver Connects the Product-Data Process

The benchmark identifies problems that appear at different points in the product-data lifecycle: information fails to synchronize between systems, employees fill gaps manually, catalogs are not consistently ready to publish, and many companies have limited visibility into how product content performs once it reaches a channel.

Inriver’s response is to bring more of that work into a connected product-information layer. Its PIM platform synchronizes product information from ERP, PLM, and supplier systems, then gives teams workflows to enrich, validate, approve, and distribute that information.

In SAP environments, Inriver’s BTP ERP Cloud Connector links that layer to SAP S/4HANA, while its SAP Commerce Cloud Adapter carries enriched content downstream. SAP can remain the source for operational product records while Inriver manages the additional descriptions, assets, translations, classifications, and other content required by commerce and digital channels.

Inriver also applies AI to onboarding, enrichment, validation, and compliance checks, and provides feedback on listing performance after content is published. Those capabilities correspond closely to three areas the benchmark says manufacturers need to strengthen: integration reliability, automation, and measurement.

What This Means for SAPinsiders

• The weakest handoff can cap overall maturity. Strong automation or measurement in one part of the process cannot compensate for unreliable transfers elsewhere. Product-data performance depends on how well capabilities connect.
• Manual resilience can hide structural limits. Experienced employees can keep product information moving despite incomplete automation or failed integrations. That makes current performance look healthier than the process may prove under higher volumes or greater automation.
• PIM becomes more valuable as responsibilities separate. Keeping operational product records in SAP while enrichment and distribution happen elsewhere creates clearer roles. It also increases the importance of reliable synchronization across ERP, PIM, and downstream channels.