The hidden costs of poor product data

A customer requests the current material specifications for PET packaging. A routine request, really.

The sales team checks the ERP system. Product management searches through several Excel files. Quality assurance is asked to confirm the details and finds two documents with different values. No one knows off the top of their head which version is correct.

After [X] emails exchanged between [Y] departments and [Z] workdays, the customer receives a response. The information was available the entire time. Finding it and verifying its accuracy is what caused the effort.

This results in costs that don’t appear in any budget line item: searching for information, resolving discrepancies, correcting errors, and maintaining the same data multiple times. This effort is rarely tracked. That’s why it’s missing from every cost estimate.

Drei Fachkräfte besprechen die technischen Spezifikationen einer transparenten PET-Flasche in einer Produktionsumgebung. Im Hintergrund sind eine Abfüllanlage und digitale Produktzeichnungen zu sehen. — When product information is unclear, even simple customer inquiries can turn into a time-consuming coordination effort involving multiple departments.

The Hours Nobody Counts

Poor product data rarely results in a major cost center. Instead, it causes small time losses spread across departments, processes, and workdays. Each one seems harmless on its own, but together they add up to a significant burden.

Searching for and comparing Excel files
Material data, technical specifications, and recycling information are stored in various systems and files, often in multiple versions.
Follow-up Questions and Coordination Loops
Is the recycled content up to date? Who approved the change? Without clear accountability, such questions get passed back and forth between sales, product management, and quality assurance.
Correcting Erroneous Data
Incorrect or incomplete information triggers additional checks. If these issues aren’t caught until they reach the customer or are discovered during an audit, the resulting rework becomes costly.
Maintaining the Same Data Multiple Times
Product information is scattered across ERP systems, PIM systems, customer portals, and data sheets. Without a single source of truth, every change must be entered and verified in multiple places.

Five minutes for a follow-up question. Ten minutes to find the right file. Half an hour to resolve conflicting information. No one keeps track of these minutes; they eventually become part of the daily work routine.

But what happens when it’s not just one person, but 20, 50, or 100 employees who regularly lose time due to unreliable product data?

What happens when not just one person, but 20, 50, or 100 employees regularly lose time this way? Do the math for your company.

How much does poor product data cost your company?

How much working time is potentially lost due to searching for, verifying, and correcting product information? Please adjust the values to see how this applies to your business.

Employees who work with product data 50

Time lost per employee per day 20 min

Estimated labor costs per hour 60 €

Lost work hours per year 3,667 h

Calculated cost of lost work time 220,000 €

Sample calculation based on 220 working days per year. The results are estimates and do not represent industry benchmarks or guaranteed cost savings. Actual costs depend on your organization, your processes, and your labor costs.

Why Costs Continue to Rise

The more frequently product information is needed, the more its shortcomings become apparent. Three trends are driving an increasing demand for it in the packaging industry.

Customers expect information quickly

A brand manufacturer requests up-to-date information on material composition, recycled content, and recyclability for 200 packaging variants. If this data is not available in a standardized format, someone has to compile it variant by variant and verify it individually. This ties up skilled staff, delays the preparation of quotes, and can strain the customer relationship.

PPWR Increases the Pressure

The EU Packaging Regulation (PPWR) has been in effect since August 12, 2026. A declaration of conformity and technical documentation are required for packaging. Starting in 2030, minimum recycled content requirements will be added—30 percent for food-contact PET packaging. Anyone who has to piece this information together from ERP systems, Excel spreadsheets, and emails incurs the same effort with every inquiry.

AI Solves Data Problems

AI assistants answer product questions in seconds. If they access outdated or contradictory data, they report the errors just as quickly. Conversely, AI can automatically detect missing information and inconsistencies. To do so, it needs reliable reference data and clear validation rules. The more processes that access product data, the more costly each error in that data becomes.

The result: The more processes that access product data, the more costly it becomes if that data is incorrect.

How Companies Can Reduce Time Loss

The good news is that companies don't have to overhaul their entire IT infrastructure right away to reduce the costs associated with poor-quality product data. Often, the first step toward improvement is to critically evaluate existing processes and make changes as needed.

Identify Wasters

An assessment reveals which product data items are regularly searched for, inquired about, or require manual correction. Such day-to-day questions immediately highlight where the greatest potential for improvement lies.

Give real trust

Clear lines of responsibility and approval processes put an end to time-consuming coordination loops. A defined single source of truth provides clarity on which source is authoritative, ensuring that data is not maintained multiple times.

Ensuring Quality

Regular checks—some of which are automated or AI-powered—help prevent new data errors. The benefits of these measures can be directly measured using metrics such as response times to customer inquiries or the error rate.

Conclusion: Poor product data costs more than it seems

The costs associated with this are rarely itemized on an invoice. They manifest in delayed quotes, unnecessary coordination, repetitive data maintenance, and work hours that could be spent on more important tasks.

That’s why it’s especially worthwhile for companies in the PET and packaging industries to take a closer look. Organizing product information reliably not only reduces errors and wasted time—it also creates better conditions for customer service, compliance with regulatory requirements, and the effective use of AI.

The key question isn’t just how good a company’s product data is—it’s also how much work time is lost every day because information has to be searched for, verified, or corrected.