How Dawsongroup Prevents Failures Instead of Fixing Them with FreezerData

From Firefighting to Forecasting

"Normally, a compressor starts up five or six times per hour. If that suddenly becomes ten or twelve, something's wrong," says Jan de Waard, Operational Manager at Dawsongroup Benelux. He describes a situation familiar to anyone in refrigeration rental: you only know there's a problem when the customer calls—and by then, it's often too late.

Dawsongroup manages an extensive fleet of cooling and freezing units rented across various industries. For their pharmaceutical clients in particular, downtime is unacceptable—a single failure can destroy thousands of euros' worth of medicine. The traditional, reactive maintenance model was no longer sufficient.

The Search for Smarter Maintenance

When De Waard learned about FreezerData, an algorithm-based monitoring system developed with the expertise of cooling specialist IJskoud, his interest was immediately piqued. "I saw it as a very promising innovation," he says. "The smart sensors continuously measure system performance 24/7. The moment something deviates, I get an alert by email or smartphone."

Henk Komin, founder of FreezerData, explains what makes the system unique: "The AI/ML algorithm analyzes every sensor reading every minute. This allows it to predict when a fault is likely to occur—before it actually happens. For example, if someone leaves a freezer door open, you get an instant notification."

Technicians Who Check Before They Drive

The impact on daily operations has been significant. "Normally, a technician would immediately head out after an alarm," says Komin. "Now, they can first check what's happening on their iPad. That saves a lot of time and unnecessary callouts."

For Dawsongroup, this represents a fundamental shift. De Waard explains: "Thanks to this system, we detect anomalies before our customers even notice them. That allows us to act quickly and prevent product loss."

Real-Time Control Across the Entire Fleet

The first three FreezerData systems were installed as a pilot in what Dawsongroup calls their critical cells—units where failure would have the greatest impact. The result? Complete transparency.

"We have a large rental fleet that we can now monitor 24/7," says De Waard. "Many of our clients are in the pharmaceutical industry, where product quality and reliability are non-negotiable. With this technology, we have real-time insight into their essential equipment, regardless of time or location."

What Does This Deliver in Practice?

De Waard gives a practical example: "If a compressor suddenly starts up ten to twelve times per hour instead of five or six, we immediately know something's wrong. With these alerts, we can respond faster than the user ever could and prevent losses."

Komin adds: "Even simple issues, like someone leaving a freezer door open, are instantly reported. Technicians can check remotely before driving out—saving both time and costs."

A System That Keeps Getting Smarter

What makes FreezerData particularly valuable is its continuous improvement. "We've developed an algorithm based on historical data, so the system keeps learning and becoming smarter," Komin explains. "This gives Dawsongroup deeper insight into how each installation behaves."

In other words, the system doesn't just detect current issues—it also learns from past patterns, improving its predictive accuracy day by day.

From Pilot to Rollout

The pilot has been so successful that expansion seems inevitable. "We've already installed the first fifteen systems, and more are being added every week," says De Waard.

The collaboration between Dawsongroup and FreezerData demonstrates how data and digitalization are transforming refrigeration technology—from reacting to breakdowns to preventing them with smart algorithms. For businesses where cooling is mission-critical—whether for medicines, food, or other temperature-sensitive products—this can mean the difference between a satisfied customer and a costly disaster.

Lessons Learned

Dawsongroup's experience shows that successful predictive maintenance implementation starts with:

• Starting small: Begin with a pilot on your most critical installations.
• Building trust: Let the system prove its value before scaling up.
• Choosing the right partner: Work with experts who understand both the technology and your industry.
• Investing in the future: Accept that the technology will keep evolving and becoming more valuable over time.

"For me, it's clear," concludes De Waard. "This technology gives us the predictive capability we need to serve our customers optimally."