Manufacturing companies often work with complex products, many variants, and high demands for documentation, traceability, and data quality. Product data is not merely an operational necessity, but a strategic asset that connects development, production, sales, distribution, and aftermarket.
At Pico, we work with manufacturing companies where data must move consistently and in a controlled manner across systems, markets, and organisations – and where solutions must be able to grow and adapt over time.
Why is product data particularly complex in manufacturing?
In manufacturing companies, product data emerges early in the value chain and is continuously enriched. Data is used in many contexts simultaneously, including planning, production, quality assurance, sales, and documentation.
The complexity is often the result of a combination of:
Many product variants and configurations
Different requirements per market and customer
Technical specifications, tolerances, and material data
Documentation requirements, certifications, and compliance
Interaction between ERP, PLM, PIM, commerce, and external channels
Without a clear structure and governance, product data risks becoming inconsistent, outdated, or difficult to reuse across the business.
How does Pico work with manufacturing companies?
Pico starts from product data as a shared, business-critical foundation. The work begins with understanding the company's products, processes, and organisational reality – not just the system landscape.
We work systematically with:
Data modelling that reflects products, variants, and relationships
Clear ownership for the creation, maintenance, and quality of data
Alignment between technical data, commercial data, and documentation
Integration between core systems such as ERP, PIM, PLM, and commerce
Scalable structures that can handle new markets, channels, and requirements
The focus is on creating a robust setup where product data can be reused consistently – without locking the company into rigid structures.
PIM as a central hub
For many manufacturing companies, PIM serves as the unifying layer for product information. Here, data is structured and enriched so it can be used correctly in different contexts.
PIM is used, among other things, for:
Consolidating product data from multiple source systems
Managing variants, attributes, and classifications
Adapting data to markets, languages, and channels
Supporting documentation, data sheets, and technical descriptions
Ensuring consistency across digital and physical touchpoints
At Pico, PIM is not seen as an isolated system, but as part of a larger data ecosystem.
The connection between business, data, and technology
Manufacturing companies are often characterised by long lifespans for both products and systems. It is therefore essential that solutions are designed with respect for existing processes – while also creating room for development.
Pico works at the intersection of:
Business needs and operational processes
Data quality, structure, and governance
Technology platforms and integrations
This approach makes it possible to establish solutions that not only solve a current problem, but also support future needs.
What value does this create for manufacturing companies?
When product data is structured, consistent, and accessible, manufacturing companies achieve a range of long-term benefits.
This can mean, among other things:
Less manual work and fewer errors
Faster time‑to‑market for new products and variants
A better foundation for documentation and compliance
Greater transparency across the organisation
The ability to scale the business without a corresponding increase in data complexity
The value does not arise in the systems alone, but in the interplay between people, processes, and technology.
Typical connections to other areas at Pico
Work with manufacturing companies is often closely linked to several of Pico's other areas of expertise.
This includes, among other things:
Integration between PIM, ERP, and commerce
Data governance and organisational anchoring
Support for documentation and sustainability data
Preparation of product data for use in automation and AI‑based solutions
These connections are handled as parts of one cohesive whole, rather than as isolated initiatives.