Manufacturing data sharing is often reduced to a technical checklist: connect systems, define interfaces, exchange data securely. That covers only part of the work. Once data moves across organisational boundaries, companies also have to decide why the data is shared, who is responsible for it, what partners may do with it, and how the exchange fits into everyday operations.
The IT department cannot close this gap on its own. Trusted data sharing requires a combination of managerial, technical, legal and operational skills. Manufacturing companies need all four perspectives if data cooperation is to move from a pilot into regular practice, even though the depth of expertise varies by role.
Managerial skills: connecting data sharing to business priorities
Managers do not need to understand every technical detail of a data space. They do need a clear sense of what the cooperation should achieve and what the organisation has to contribute to make it work.
In practice, that means defining a concrete business or operational problem for data sharing to address, judging whether the initiative justifies the time and resources, and deciding which activities come first. Managers also assign ownership so that decisions can actually be made, and they align objectives and expectations with customers, suppliers and other partners. Without this perspective, companies risk building technical connections that have no clear operational purpose.
Technical skills: making data exchange reliable
Data sharing across companies requires systems to exchange information in a consistent, secure and reusable way. Relevant skills may include data integration, interfaces, interoperability, data models, access management and an understanding of data-space technologies.
Apart from this, teams need to understand where the data comes from, whether it is reliable enough, how it is described and whether the solution can be reused when another partner or use case is added.
Legal and governance skills: knowing what may be shared
Being able to access data technically does not automatically mean that the data may be used for every purpose. Companies therefore need people who can answer questions such as:
- Who is accountable for the dataset and related decisions?
- For which purpose may a partner use the information?
- Which organisations or roles should be able to receive it?
- Which legal, contractual or regulatory requirements apply?
- When is specialist legal or data-protection advice needed?
This does not mean that every employee needs to become a legal expert. Responsibilities have to be clear and staff need to know when an issue requires specialist support.
Operational skills: making data sharing work in everyday operations
Production, quality, logistics, maintenance or purchasing staff are often the people who create, check or use the information being shared. They need to know why particular data is required, how it should be recorded, what quality standards apply, and what to do when information is incomplete or wrong.
Their knowledge also matters during critical implementation. IT may understand the system, but production and quality staff understand how the process actually works. Without their input, a technically correct solution may still fail in practice.
Why this is a cross-functional capability
Taken together, these four perspectives make data sharing a responsibility shared by several departments. The work can be divided across roles such as:
- Data Owner: decides why and under which conditions important data is used.
- Data Steward: supports data quality, definitions and documentation.
- Use Case Owner: connects the initiative to the operational objective.
- Technical Coordinator: manages systems, interfaces and interoperability.
- Ecosystem Coordinator: works with external partners and coordinates requirements.
In a large company, these responsibilities may be distributed across specialist teams. In an SME, several may be combined within existing roles. Where in-house capacity is limited, technology providers or specialised partners can support parts of the implementation. Job titles matter less than making sure every responsibility is covered.
Building the skills progressively
Manufacturers do not need to train everyone to the same level. A better approach is a common foundation, followed by role-specific learning and practical application in a real use case.
Module 5 of the VET4DATACOOPERATION training programme is being developed to address these skill gaps. It is designed to help learners identify the managerial, technical, legal and operational capabilities needed for trusted data sharing, assess who needs which level of knowledge, and turn those needs into practical learning and implementation actions.
VET4DATACOOPERATION is an Erasmus+ KA220-VET project developing vocational training on trusted and sovereign data sharing for the manufacturing sector.
Visit the official LinkedIn page for VET4DATACOOPERATION project updates: https://www.linkedin.com/showcase/vet4datacooperation/posts
