GACS explained: building data and energy management

Buildings generate more and more data. Energy flows, climate data and equipment status are often already available. Yet in practice, we see that this data does not always lead to greater control or better performance. This is where GACS comes in.

GACS (Building Automation and Control Systems) is a European requirement for large non-residential buildings. Its aim is to monitor energy use more effectively, control building systems more intelligently and identify energy losses sooner. But GACS is not just about measurement. Above all, it is about having demonstrable insight into how a building functions. And that is precisely where many organisations face a challenge. Plenty of data is available, but without analysis, that information goes unused.

GACS therefore shifts the focus from collecting data to understanding and using it. Not as an additional administrative burden, but as an opportunity to gain lasting control over energy use and building systems.

When data provides no direction

Many buildings have been collecting data for years. Yet important questions often remain unanswered.

Why do spikes in energy consumption occur?
Which systems cause these spikes?
And when does behaviour differ from what is normal for this particular building?

Without context, data is difficult to interpret. Values appear to fluctuate, but there is no frame of reference.

What is normal use?
What can be attributed to the building, the equipment or its usage profile?

Analysis therefore starts not with optimisation, but with understanding what you see.

Analysis as the foundation for control and compliance

For GACS, Data Science Lab focuses on analysing and interpreting building data. By structuring data, revealing patterns and putting anomalies in context, we generate insights that go beyond individual measurements or dashboards. This provides the basis for demonstrating compliance and taking informed action.

That analysis does not stand alone.

Together with Montreal Solutions, we ensure that the building’s technical systems are accurately documented and monitored.

Montreal Solutions maps energy systems and equipment reliably and in detail — system by system and component by component. Data Science Lab can then identify relationships, compare behaviour and detect declines in performance.

One example is identifying peak demand. This means not only showing that a peak occurs, but also making it clear which systems contribute to it and under what conditions.

Another example is identifying systems that consistently perform differently from expected, even when this is not immediately apparent in overall energy consumption.

Insights without assumptions

GACS requires evidence. That means insights must be traceable and explainable.

They must be based not on assumptions, but on consistent analysis over time. This analysis establishes a point of reference: what is normal behaviour, what deviates from it and where is action needed?

That makes it possible to justify decisions and take targeted action, rather than reacting to incidents.

It gives managers, owners and regulators clarity and peace of mind.

GACS as an opportunity to improve how you manage buildings

GACS is therefore not just a technical or legal obligation. It is also a practical framework for gaining control over building performance. By putting analysis at the centre, insights become the starting point for better decisions, ongoing monitoring and continuous improvement. This makes GACS more than a checklist: it becomes a tool for keeping energy use and building systems demonstrably under control.

Get in touch

Do you have building data, but still lack a clear picture of energy use and building systems?

If so, analysis is often the missing step. Call Sebastiaan on +31642987624. We’ll show you how the right analysis can help you gain control over building performance while meeting your GACS obligations.