Who still needs dashboards?

Dashboards are like maps. They show us the way, but only in a static moment. Anyone who has ever traveled with an old road map knows how quickly reality moves on: Roadworks, detour, new roads. Today we rely on GPS, which provides us with up-to-date, dynamic information at all times. Why should we work any differently in production?

The limits of classic evaluations

This is the reality in many manufacturing companies today: Data is exported from machines, ERP or MES systems. It then ends up in Excel spreadsheets or in PowerBI. This creates dashboards that transform current figures into colorful graphics. That sounds good, but it has crucial weaknesses.

The dashboards have to be maintained manually. Every new question means new work. If you suddenly want to look at delivery reliability instead of productivity, you have to reprocess the data. If you want to make historical comparisons, you quickly reach your limits. And above all: these dashboards are only ever as up-to-date as the last export. They are a snapshot, frozen in time.

This is particularly unsatisfactory for managing directors or division managers who want to manage their company. Decisions often depend on how up-to-date and complete the figures are. If the answer to a critical question is only available days later, valuable time is lost.

AI co-pilots change the game

AI co-pilots fundamentally change this pattern. Instead of thinking in terms of predefined reports, users will in future be able to ask directly what they want to know. Examples:

"What is the current capacity utilization of my machines?"

"Which orders are currently behind schedule?"

"Show me the OEE development over the last three months."

"Which customer orders are at risk of exceeding their delivery date?"

The answer comes immediately. In the form of a clear figure, a dynamic graphic or an interactive dashboard that adapts as soon as a new question is asked.

The key is flexibility. A managing director no longer has to wait for someone from Controlling to build a special dashboard. A production manager no longer has to export raw data in order to run an analysis. Instead, a simple question in natural language is sufficient.

Advantages for decision-makers and employees

For managing directors, this means a new quality of corporate management. Decisions are no longer based on old or filtered figures, but on the actual state of production. Strategic control becomes faster, more precise and closer to reality.

Managers in production, planning or quality also benefit. Anyone who needs an overview of capacity utilization, downtimes or deviations receives the answer in seconds. There is no need for the often time-consuming preparation of reports, which ultimately only provide a limited perspective.

The benefits are also clearly noticeable for employees in day-to-day business. Instead of creating recurring evaluations, a brief dialog with the co-pilot will suffice in future. This leaves more time for the essentials: Improving processes, solving problems, advancing production.

From the map to the GPS

The analogy with maps and GPS illustrates this change. Dashboards are like maps. They are valuable, but static. If you are looking for a new road, you need a new map. AI co-pilots are the GPS of production. They provide the current route at all times, show detours and adapt immediately if the situation changes.

This is exactly what decision-makers need today: a tool that is always up-to-date, always flexible and always close to reality.

Context data: the next step

The real strength of Copilots becomes apparent when contextual data is included. After all, a figure is only as meaningful as the context in which it is placed.

Examples:

A BWA can be uploaded and automatically linked to the production data. This makes it possible to see directly how machine utilization and the order situation influence the key financial figures.

Energy data can be set in relation to machine utilization. This makes it possible to see which orders are particularly energy-intensive and where there is potential for savings.

Sensor values from production can be linked to quality data. This enables the co-pilot to recognize anomalies and provide information on possible causes.

Delivery dates and customer orders from the ERP can be evaluated together with current capacity data. This makes it immediately clear where there are risks of late deliveries.

This combination of contextual information opens up a completely new dimension. Instead of looking at isolated key figures, answers are created that take the entire company into account.

Why EVOMECS is the pioneer here

However, there is one important prerequisite: such co-pilot queries only work if the basis is right. A comprehensive and clean data set is required. This is precisely where EVOMECS has a unique advantage.

EVOMECS is the only platform that really links production data consistently. Tools, NC programs, orders, machine statuses, quality data - everything flows into an integrated system. This creates the data depth and data quality required to answer AI queries reliably and precisely.

While other systems remain isolated solutions, EVOMECS makes it possible to display the entire production process as a digital image. On this basis, the co-pilot can answer questions that were previously unthinkable. And it can do this in real time, without having to laboriously merge data first.

Where the journey is going

We are at the beginning of a new type of corporate management. Away from rigid dashboards and towards a dynamic, dialog-based approach to data. Anyone who has ever experienced how ChatGPT creates complex texts on demand can easily imagine what this means for key production figures: transparency at the touch of a button.

The question is no longer whether we will be working with AI co-pilots in the future. The only question is when.
And at EVOMECS, the answer is: very soon.