Technical product data: The biggest challenges — and how PIM solves them

Why technical product data is critical

Technical product data is the basis for products to be used, installed and maintained. Incorrect dimensions, voltages, temperatures or safety information not only lead to returns, but in the worst case to damage and liability risks.

At the same time, technical data is often the most complex data in a company: many attributes per product, different standards, dependencies between parameters and variants. This is exactly why companies are quickly reaching their limits with grown Excel lists and unstructured data stores.

Typical challenges related to technical product data

1. High variety of attributes: Technical products quickly have several dozen to hundreds of attributes: power, voltage, amperage, temperature ranges, accuracy classes, tolerances, materials, protection classes, approvals and much more. Maintaining this data in tables is prone to errors and difficult to understand.
2. Different standards and markets: What is standard in one market may be special in another. Different standards, country-specific regulations and certifications mean that technical data becomes context-dependent. Companies need a way to represent these differences in a structured way.
3. Distributed data sources: Technical data is often stored in many places: in PLM, in CAD systems, in ERP master data, in individual Excel lists and often in the heads of experienced employees. A central view only occasionally exists — and it often quickly becomes outdated.
4. Media breaks in documentation: Technical data sheets, manuals and security documents are often maintained and manually updated in office or layout programs. Every product change entails a rat tail of document changes — and the probability of errors is high.

What a PIM system can do for technical product data

A PIM (Product Information Management) system is not just a marketing tool, but — set up correctly — can become the backbone for technical product data.

Key Features:

• Uniform attribute model per product family (e.g. all gearmotors with the same core attributes)
• Inheritance: base values at series or platform level, specific values at variant level
• Validation rules for value ranges (e.g. temperature -20 to +80 °C) and units (mm instead of any text)
• Mandatory fields per channel (e.g. specific safety information for data sheets and web shop)
• Automatic generation of data sheets and other documents from maintained data

From PLM to PIM: Clarifying the roles of systems

In many companies, the question is: If we already have a PLM — why do we still need a PIM for technical data?

A proven division of roles looks like this:

• PLM as a leading system for design-related data (3D models, parts lists, CAD information)
• PIM as a leading system for production and market-related data (technical product data in saleable form, marketing attributes, channel rules)
• ERP as a leading system for transactional data (prices, inventories, order processing)

Core technical information is transferred from PLM to PIM, where it is enriched and converted into a form that can be used for sales, marketing, e-commerce and documentation.

Step-by-Step: Structuring Technical Product Data in PIM

1. Select focus product line

Start with a clearly defined product family, such as a series of drives or control cabinets. The technical attributes are similar here, and you can build a practical model without tidying up the entire range.

2. Define attribute model

Together with product management and technology, you define which attributes are relevant for this product line:

• Key technical parameters (e.g. power, voltage, torque)
• Mechanical properties (e.g. dimensions, degree of protection)
• Ambient conditions (temperature range, purpose)
• Standards and certificates
• optional attributes for specific markets or variants

3. Define rules and mandatory fields

For each product class, you define which attributes must always be maintained before a product is considered approved. In addition, you define which value ranges are allowed and which units may be used.

4. Transfer data from existing sources

Technical data is then transferred from PLM, ERP and existing Excel lists to PIM. It is worthwhile not simply to import everything blindly, but to remove duplicates and harmonize values (e.g. uniform units, spellings).

5. Connect datasheets and channels

Once the technical data is structured in PIM, data sheets can be generated automatically or at least filled semi-automatically. Web shops, customer portals or configurators can also be provided with verified technical information.

Best practices from projects

• Integrate technology early on: Technical product data is not just a marketing topic. Without the expertise of design, development and quality management, you run the risk of building a PIM data model that bypasses practice.
• Consistently standardize units and standards: Don't mix mm, cm and inches into attributes at will. Define clear rules for each attribute and use central standard tables or code lists where appropriate.
• Make data quality visible: Use dashboards in PIM to show how complete and consistent technical data is per product line. This creates transparency and motivates continuous maintenance.

conclusion

Technical product data is complex — but that's exactly why it's worth managing it in a structured way. A PIM system plays the role of a central framework: It makes technical information understandable, reusable and usable for all channels. The professional quality remains with your teams of experts — the system ensures that this quality is received everywhere.