Why does production data exist but flow nowhere?
Every shift, every batch, every stoppage leaves a trail. That trail simply dead-ends in a PLC, a historian, or a local file on a production planner's laptop. The ERP system receives a manual entry at the end of the day. The planner works on assumptions. The quality manager exports a report and pastes it into a presentation. Meanwhile, the actual production data sits somewhere else entirely. According to UWV research (Industrie in beeld, February 2026), more than 80% of industrial companies are experiencing greater economic uncertainty, while a shortage of personnel is simultaneously one of the biggest bottlenecks. That makes re-keying and manual synchronisation particularly costly: the people transferring data are the same people you need for the actual work.
Why does standard MES software not resolve the data disconnect?
Most MES packages are built for a generic factory, not for your specific combination of machines, raw materials, customer specifications, and planning logic. Implementations take a long time, configurations become compromises, and after two years the system no longer fits the way the operation has evolved. The real problem: the MES still does not communicate properly with the ERP, the quality registration system, or the purchasing department. So integrations get built, scripts get run, and Excel files are maintained as a fallback. ABN AMRO expects the Dutch manufacturing industry to grow by around 3% in 2026, driven by high-value manufacturing sectors. Those are precisely the companies where production data is most complex, and exactly where a generic package delivers the least return.
Which processes break down most often?
In practice, it is always the same pain points. Work order processing: the order comes out of the ERP, gets printed, filled in on the shop floor, and then manually re-entered. Quality registration: measurement values are noted on paper or in a spreadsheet, only entered into the quality system later. Production reporting: shift handover notes are passed on verbally or via an app that is not connected to the planning system. In each case, people are acting as the integration layer between systems that should be handling that themselves. A production manager who only sees the next morning that a batch fell outside tolerances last night has no use for that information when it comes to the decision that needed to be made the night before.
When is an AI layer the right choice, and when is it not?
An AI layer on top of existing systems helps when the core processes are already recorded digitally but the information does not flow through. AI Workers can read documents, route work orders, flag deviations, and generate notifications without a person touching every step. This works well for companies that do not want to replace their ERP or MES but do want to eliminate the manual connecting work. It does not work when the underlying data is structurally absent or when the core system itself is so outdated that there is no reliable foundation to build on. In that case, rebuilding the core system is the more honest choice: a system built AI-native with production logic at its centre gives the operation a foundation that scales with it. The choice between these two routes depends on the state of the current systems, the complexity of the operation, and whether the existing architecture is scalable at all.
What does it deliver when production data actually flows?
When work orders are routed automatically, quality data is available in real time, and the planner works from current capacity data, the operation changes in a meaningful way. Not because a magic solution has been deployed, but because information arrives at the right place at the right time. Adjustments can be made within the same shift. Deviations are caught before they render a batch unusable. The production planner spends time on planning, not on synchronising systems. In a sector where a tight labour market is a structural reality, that is not a luxury. It is the most efficient way to get the most out of the people you have.