Data Control in Manufacturing-X: How to Share Data Without Giving Away Know-How?

Data control in Manufacturing-X is a topic that goes far beyond the IT department. If you are responsible for production, quality, traceability, plant digitization, or system integration, it directly affects your work.

More and more often, you need to share data with someone outside your company: a customer, supplier, auditor, technology partner, or regulator. Sometimes that means sharing data about a batch, component, process parameters, material origin, carbon footprint, or product history.

At that point, you may start asking yourself: how can you share information without giving up control over your company’s knowledge?

Getting familiar with Manufacturing-X can help you find the answer. It gives manufacturers a model for data exchange between companies, where access depends on role, purpose, scope, and time. International Manufacturing-X describes this ecosystem as federated, decentralized, and based on FAIR principles.

Manufacturing-X is an international initiative promoting a way for industrial companies to work together and exchange data without moving all production knowledge into one place.

Manufacturers can then define more clearly:

That is what data sovereignty looks like. You do not cut yourself off from partners, but you keep control over what happens to your production data.

In a well-prepared model, control stays with the data owner, meaning the company that creates, collects, or shares the data.

A file should not travel without oversight. The manufacturer should know who has access to data, what scope they can see, for how long, and for what purpose.

As a result, a customer asking about a batch of components does not need to see the full production technology, a partner calculating carbon footprint does not need access to complete machine settings, and an auditor should not receive information unrelated to the inspection.

Data control in Manufacturing-X protects company knowledge while making collaboration easier.

Production increasingly operates through connected networks. One product may involve many suppliers, several assembly stages, separate service processes, later use, and reporting obligations across the entire life cycle.

Regulations are also becoming part of the picture. The Data Act has applied in the EU since September 12, 2025, and increases the role of access to data generated by connected devices, including industrial machines. The European Commission points out that data from industrial devices can help companies manage production and supply chains more effectively.

The Digital Battery Passport is another example. Starting February 18, 2027, the passport is expected to be required for selected battery categories, including EV, LMT, and industrial batteries above 2 kWh. Battery Pass materials indicate that for EV batteries, the requirement covers around 80 data attributes across the product life cycle.

This clearly shows the scale of the shift. Data cannot be collected only when a customer asks for a report. It needs to be consistent, current, and ready to be shared safely outside the company.

Data exchange often still follows a familiar pattern: an ERP export, an Excel file, an email to the customer, a correction from quality, another file version, and then the question of which table is current.

With a small number of partners, this can still work. With a larger network, errors, manual work, and unnecessary questions increase.

The biggest change is trust. A manufacturer is more willing to share data when it knows it is not giving away full process knowledge. A customer trusts a supplier faster when the data is consistent, not assembled manually from several sources.

A strong example is the Digital Battery Passport demonstrator prepared as part of the International Manufacturing-X Council for Hannover Messe 2026.

At explitia, as Poland’s representative, we were responsible for the stage where individual parts become a finished battery, and distributed data is connected into a consistent product picture. This is where information about components, production, environmental footprint, later use, and recycling comes together.

This example matters because a battery gains a data layer that is created together with the product, not later, when someone tries to reconstruct batch history from reports, emails, and spreadsheets.

The manufacturer needs to know:

The same pattern will increasingly apply to automotive, electronics, machinery, energy, and products with long life cycles.

Losing control over data, or not having enough control in the first place, may seem harmless at the beginning.

Someone sends a customer a report that is too broad. The quality department has a different version of the data than production. ERP shows one status, MES shows another, and Excel shows a third. An audit gets closer faster than you can collect the full product history.

Over time, costs appear:

The most frustrating part is that you often already have the information you need. It is just distributed, named differently, and difficult to share safely.

You do not need to start with a large program. It is better to choose one process that already takes too much time: complaints, audits, traceability, customer reporting, assembly data, or preparation for the Digital Product Passport.

Create a simple map of sources:

The main goal is to answer where the data is, who uses it, and which information is needed outside the company.

Not every piece of information should leave the plant. Divide data into three groups:

This division makes conversations between production, IT, quality, and management easier.

Machine data has value only when you know what it refers to. Temperature, pressure, or cycle time must be connected with a batch, order, operation, material, and product version.

This is where MES, traceability, and ERP integration play a major role.

Manufacturing-X requires a shared data language. That is why models such as the Asset Administration Shell, or AAS, are gaining importance.

In simple terms, MES collects facts from production, while AAS helps give them a structure that other systems and partners can understand. This is an important step toward DPP, reporting, and data exchange across the value chain.

If you want to take care of data sovereignty, you usually need to start by organizing what happens inside the plant: machine data, MES, ERP, quality, traceability, and reporting.

We can help you connect data from machines, devices, sensors, PLCs, ERP systems, other applications, and operator work. That way, you can build a consistent view of production instead of assembling it manually from many sources.

It creates a good foundation for DPP, AAS, data exchange with partners, and better order in the places where data is actually created.

Start with one process and answer the questions below:

If the answer to the last question is “not yet,” it is worth starting with the basics: MES, integrations, traceability, data organization, and access rules.

A good next step is a short review of one process: complaint handling, auditing, assembly, or customer reporting. Using one concrete example, it is easiest to check which data you already have, what is missing, and where you are losing control.

Manufacturing-X does not take control away from the manufacturer. A well-prepared model helps strengthen that control by organizing who sees the information, why they see it, and how long they can use it.

It means the ability to share data with partners, customers, or auditors based on clear rules. The manufacturer decides the scope, purpose, access time, and recipients.

No. Manufacturing-X is based on decentralized data exchange. A company does not need to move all information into one place.

Data sovereignty means that a company keeps control over its information: it knows where data is created, who has access to it, what purpose it is used for, and which data should remain inside the organization.

The Digital Product Passport needs data from many places: production, quality, components, logistics, service, and recycling. Manufacturing-X provides a model for exchanging this information between companies without full data centralization.

Start with a data map and one process that already takes too much time. Then check whether MES, ERP, machine data, and quality reports create one product history.