Australia’s Largest Supermarket Chain Partners With Sutherland for Advanced Predictive Maintenance Through Intelligent Asset Management

Client Overview

As the largest supermarket chain in Australia and New Zealand, the client operates more than 1,450 stores and depends on a vast network of refrigeration units to maintain the freshness and safety of perishable goods. Given the scale and complexity of its infrastructure, efficient and reliable refrigeration management is mission-critical – not only for product integrity and operational continuity, but also for customer trust and satisfaction.

The Challenge

High Alert Volumes, Disconnected Systems, and Soaring Maintenance Costs

Managing refrigeration systems at enterprise scale had become increasingly unsustainable for Australia’s largest grocery chain. With over 1,450 retail locations and tens of thousands of refrigeration assets operating across Australia and New Zealand, the organization was overwhelmed by the volume of system-generated alerts – averaging 7,000 alarms daily. While the majority of these alarms were non-critical, the absence of intelligent filtering mechanisms meant that every alert was treated with equal urgency.

This environment of constant noise led to significant operational inefficiencies. A manual, labor-intensive three-tier triage process was required just to sift through alerts, draining support team resources without consistently identifying the true root causes. Work orders – roughly 350 per day – were being generated manually, often without adequate diagnostic context. This resulted in excessive technician dispatches, repeat site visits, and suboptimal first-time fix rates.

Further compounding the challenge was a fragmented systems landscape. Alarm systems were not integrated with the Computerized Maintenance Management System (CMMS), leading to data inconsistencies and a lack of traceability across issue detection, resolution, and asset history. The result was a reactive, siloed, and costly maintenance operation – one that was consuming an estimated AUD $64 million annually and eroding both operational agility and customer satisfaction.

Sutherland Solution

A Smart, Connected Framework for Predictive Refrigeration Management

To address these entrenched inefficiencies, the grocery chain engaged Sutherland to design and implement a modern, Intelligent Asset Management (IAM) framework. The goal was to transition from reactive maintenance to a predictive, insight-led model – one that would reduce unnecessary alarms, improve technician efficiency, and enable better strategic planning across asset lifecycles. Sutherland initiated the transformation with a pilot across 10 stores to test and refine the new operating model before full-scale deployment. The solution centered on advanced automation, intelligent filtering, and data orchestration, with key innovations including:

• Smart Alarm Filtering Engine: Applied AI-driven logic to suppress noise and surface only high-priority issues requiring action.
• Real-Time Sensor Validation: Automatically validated whether incoming alarms correlated with actual operational faults – reducing false positives.
• Alarm Deduplication Protocols: Prevented redundant notifications by clustering recurring or duplicate alerts.
• Unified Analytics Dashboard: Delivered near real-time insights into refrigeration performance, failure patterns, and alert trends – empowering both frontline and strategic decision-making.

By connecting previously siloed data sources and embedding AI into the maintenance workflow, Sutherland created a single source of operational truth, allowing the client to detect issues faster, allocate field resources more effectively, and eliminate inefficiencies that had long gone unaddressed.

The Outcome

Building a Future-Ready, Predictive Maintenance Ecosystem through Intelligent Asset Management

Sutherland’s implementation of Intelligent Asset Management has established a robust digital foundation and a seamlessly connected ecosystem, positioning the client to unlock next-level operational capability and industry-leading efficiencies.

By integrating diverse datasets, including enhanced sensor telemetry, trade logistics, weather patterns, spare parts registries, and service vehicle tracking, the solution is rapidly evolving in maturity. This connected intelligence is driving further reduction of false alarms and unnecessary work orders, while surfacing previously undetectable faults months in advance. The result: one of the most advanced predictive maintenance deployments in the industry, significantly minimizing unplanned downtime and maintenance costs.

Sutherland’s human-centric transformation approach ensures that engineering teams operate in a calm, controlled, and well-orchestrated environment, supported by real-time insights and operational foresight. As the ecosystem evolves, the integration of Digital Twin technologies offers the potential to further elevate situational awareness, planning accuracy, and overall ease of operations.
Together, these advancements are redefining operational excellence across the asset lifecycle.