Manufacturing companies already face a capability gap in data sharing. The required managerial, technical, legal and operational skills rarely exist in the right combination, and many companies will look to vocational education and training (VET) to build them. Data sharing changes the skills employees need, how roles interact and the kind of training organisations must be able to offer. If VET providers do not adapt, companies will struggle to find learning offers that match how data-driven manufacturing works.
VET providers and trainers therefore need to evolve alongside industry. Learners need to understand how data cooperation works in practice, what responsibilities it creates, and how legal, technical, managerial and operational capabilities fit together.
Data sharing creates new learning needs
Data cooperation in manufacturing cuts across functions. Managers need to understand why data is shared and how it supports business priorities. Technical specialists manage integration, interoperability and reliable exchange. Legal and governance roles must be clear on responsibilities, permitted use and compliance. Operational staff need to know how shared data affects everyday processes.
A single generic course on digitalisation is not enough to cover these various needs. A production employee does not need an integration engineer's technical depth. A manager does not need to configure interfaces, but should understand what data-sharing decisions mean and what is needed to scale them.
VET providers need more role-based learning offers
The answer is more differentiated learning pathways: a common foundation for all participants, followed by role-specific learning where it matters most for each person’s work. Typical pathways may include:
- Management: business objectives, priorities, risks, responsibilities, resource decisions
- Technical roles: data sources, interfaces, interoperability, security, reliable exchange
- Legal and governance roles: permitted use, responsibilities, compliance, escalation
- Operational roles: data quality, process changes, correct handling of shared information
- Coordinating roles: partner requirements, stakeholder communication, ecosystem collaboration
Manufacturing training often brings managers, technicians, production staff, quality experts and VET learners together around the same initiative, each seeing it from a different angle. A layered approach suits these mixed groups. Everyone starts with a common foundation, moves on to role-specific learning, applies it in the workplace and keeps developing from there. The group builds a shared understanding, and only those who need specialist depth go into it. This calls for more flexible course design than a single programme for everyone.
Practical learning becomes more important
Data-sharing skills are hard to develop through theory alone. Learners need to see data cooperation in real situations, such as exchanging quality data with a customer, providing supplier information for traceability, sharing maintenance data across organisations or tracking sustainability data across a value chain. Short modules, case-based exercises, guided reflection and workplace application help connect abstract concepts to real responsibilities.
This practical focus matters most for SMEs, where specialist staff are limited, training time is scarce, and roles are often combined. Therefore, learning needs are immediate and tied to a specific use case. Larger companies with different responsible teams may need more specialised pathways instead.
Trainers also need to be ready
The capability gap relates to trainers too. To teach data cooperation well, they have to explain how governance, skills, organisational readiness and partner collaboration interact, alongside the technical concepts.This calls for:
- up-to-date technical knowledge of current data-sharing approaches;
- a cross-functional perspective linking technical, legal, managerial and operational questions;
- familiarity with realistic manufacturing use cases;
- facilitation skills for mixed groups with different levels of prior knowledge;
- the ability to translate concepts into workplace tasks and decisions.
No trainer has to master all of these. Every trainer needs to know the limits of their own expertise and when to bring in someone else.
Vocational education has to evolve with industry
As manufacturing becomes more data-driven, vocational education has to prepare learners for cross-company cooperation, shared responsibilities, new skill profiles and increasingly connected processes, in addition to training on individual digital tools.
Module 5 of the VET4DATACOOPERATION training programme is being built to address this. Covering the capabilities needed for trusted data sharing, SME vs. large-company differences, the role of VET providers, trainer readiness, and the design of learning pathways for mixed target groups.
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/
