Woolworths – Predicting and Preventing Refrigeration Ice-Ups with 95% Accuracy
Woolworths Group operates one of Australia’s largest grocery networks, with more than 1,200 stores relying on round-the-clock refrigeration to maintain food quality and reduce waste. One of the most disruptive challenges in-store operations faced was ice build-up in refrigerated display cases—often triggering after-hours emergency callouts, risking stock loss, and overloading technician rosters.
Through its long-standing partnership with Bueno, Woolworths shifted from reactive fixes to predictive prevention—applying near real-time data and machine learning to forecast and resolve ice-ups before they became a problem.
The Challenge – The costly and disruptive nature of refrigeration ice-ups
Ice-ups silently impair system performance, degrade food safety, and increase the risk of high-temperature alarms. At Woolworths, these events were historically treated as Priority 1 or 2 callouts—requiring immediate response, typically after hours. Every event drove up costs, added strain to the workforce, and jeopardised stock.
Across a network of 1,200 stores, the goal was clear: identify and eliminate the issue before it ever triggered a fault or alarm.
The Journey Begins – Detecting ice-ups before they happen
To tackle this, Bueno deployed predictive analytics models across Woolworths’ entire connected fleet. Drawing data from over 2 million points and analysing conditions every 5 minutes, the system tracks refrigerant flow, case temperatures, and defrost trends to detect early signs of icing.
When Bueno’s AI identifies a likely ice-up event, stores and technicians receive 5–7 days advance notice, enabling teams to schedule proactive service before the situation escalates.
This approach offers:
95% predictive accuracy
Daytime resolution instead of night callouts
Centralised visibility through the Energy Management Centre (EMC)
“Being able to predict critical issues like ice-ups days in advance has fundamentally changed our maintenance strategy. It saves us significant costs and ensures our stores are always running optimally for our customers.” — Woolworths Facilities Management
The Results – 22% fewer callouts and significant operational gains
Woolworths achieved measurable results through the program:
22% reduction in refrigeration ice-up related callouts
Significant cost savings by replacing emergency callouts with planned service
Improved cold chain reliability and reduced product spoilage
Higher technician productivity via pre-dispatch diagnostics and improved first-fix rates
Uptime gains that supported consistent in-store operations
Unlocking new value from refrigeration intelligence
The impact of predictive analytics goes beyond fewer callouts. For Woolworths, it’s now a core part of how refrigeration is managed across the business:
Extended Equipment Lifespan – Systems avoid failure due to proactive maintenance
Enhanced Workforce Planning – Reduced reactive pressure improves technician efficiency
Improved ESG Outcomes – Avoided spoilage and lower emissions from fewer truck rolls
Data-Driven Confidence – Every case is backed by trend data and central reporting
Conclusion / Next Steps – A new benchmark for grocery maintenance strategy
Woolworths’ use of predictive analytics to prevent refrigeration ice-ups has become a model for grocery innovation. What was once a reactive problem is now an opportunity to drive cost savings, reduce disruptions, and improve food safety.
This approach continues to shape Bueno’s refrigeration management solutions and is now being scaled globally. As U.S. retailers respond to new refrigerant regulations and operational pressures under the AIM Act, the lessons from Woolworths provide a clear blueprint for success.
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