The future of maintenance is data-driven

Data-Driven Maintenance

Harness the transformative power of analytics to align your maintenance with industry best-practice. Deliver maintenance efforts that are targeted and efficient, enabling more focused schedules, optimised resource use, reduced downtime and increased equipment lifecycle.
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Why the current approach falls short

Contracts based purely around Planned Preventive Maintenance (PPM) or Unplanned Maintenance (UPM), are common but highly inefficient. PPM contracts revolve around rigidly scheduled checks that all too often equate to time and resources spent on inspecting equipment that is working just fine. UPM, or the “absence of an ongoing maintenance strategy”, occurs purely on a random or reactive basis resulting in highly uncertain budget allocation.

These traditional methods of maintenance are becoming increasingly misaligned with the contemporary needs and challenges of asset management. This results in two significant pitfalls:

Missed Issues

While a contractor may be occupied inspecting functional equipment, other items in need of attention could remain unaddressed for months. This oversight not only compromises system efficiency but can also escalate to more severe problems or tenant impact if not promptly addressed.

Misaligned objectives

These traditional maintenance routines don't necessarily align with the primary objectives of today’s Asset Managers, which prioritise tenants, sustainability, and cost management. This misalignment can jeopardise the tenant experience, compromise an asset’s sustainability, or trigger unplanned capex.
To truly grasp DDM, let’s unravel its key components:

A new era of maintenance

Data-Driven Maintenance (DDM) is the integration of advanced analytics into the realm of property maintenance. Unlike traditional strategies, which rely heavily on preset schedules or reactionary measures, DDM employs continuous data collection and analysis to guide maintenance decisions. DA19 summarises the workflow of this smarter form of maintenance as: “analytics pulled from big data, relayed by wireless sensor networks, analysed by cloud-based algorithms and visualised on mobile computing devices” which is effectively “changing maintenance, disrupting traditional practices and creating new value opportunities.”

Real-time data monitoring

DDM is grounded in the principle of continuously monitoring the billions of data points produced by operational plant and equipment. Real-time in nature, as data is gathered, it's simultaneously normalised and analysed. This ongoing monitoring allows for an ever-updated operational snapshot of a building, allowing for issues or dips in performance to be flagged as soon as they arise.

Integration of advanced analytics

At the heart of DDM lies sophisticated data analysis. This isn't just about collecting numbers but about understanding them. Advanced algorithm-based rules process this continuous stream of data, deciphering patterns, spotting anomalies, and making sense of the vast amount of information flowing in.

Predictive plus reactive

Instead of a broad preventive stance, where checks are made based on set intervals, DDM utilises the analysed data to predict when and where maintenance might be needed next. It's a shift from 'time-based' to 'condition-based' checks. Further, While DDM is largely proactive, it doesn't discard reactive measures. Instead, these reactive actions are informed by data-backed alerts rather than tenant complaints or anecdotal feedback.

Adaptability & flexibility

DDM is inherently adaptive. As data flows in and is analysed, the derived insights might prompt changes to maintenance schedules or resource allocations. This adaptability ensures that the maintenance approach is always in tune with the building's current needs and critical issues are prioritised based on impact.

The role of technology

It's crucial to note that DDM isn't just about data. It's also about the technological ecosystem that facilitates this data-driven approach. From the sensors that gather data to the cloud infrastructures that store it, and the analytics software that analyse it – each plays a pivotal role in bringing DDM to life.

Phases of implementation

A transition to data-driven maintenance unfolds over three stages: from initial integration, through contract evolution, to mastery and refinement.
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1. Initial integration

Recognising the extensive costs associated with traditional planned preventive maintenance.

Initial integration of analytics and optimisation tools, which may add to initial expenses but set the foundation for future savings.
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2. Contract evolution

Maintenance contracts undergo a transformative revision to integrate the principles of DDM.

The previously separate costs for analytics and optimisation now become part of the core contract, with the added benefit of reduced routine maintenance expenses.
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3. Mastery and refinement

DDM becomes the backbone of a building’s maintenance strategy. Any existing backlogs or inefficiencies are addressed and cleared.

The system operates at peak efficiency, leading to further reductions in costs, heightened equipment lifespan, and increased tenant satisfaction.

The benefits of data-driven maintenance

Optimised maintenance contracts

The advent of data-driven maintenance can have a profound impact on the negotiation of maintenance contract costs. Fewer reactive callouts and a closer focus on the real issues facilitates a more optimised strategy and in many cases, reduced contract costs by more than 20%. Beyond just cost savings, this data-centric approach offers 24/7 smart monitoring - almost like having a virtual engineer on standby at all times. This supplements the financial savings with improved overall efficiency of operations

Reduced equipment downtime

A data-driven approach directly reduces equipment downtime, with owners reporting a drop of up to 45 percent. Constant monitoring complemented by automated fault detection and diagnosis (AFDD) ensures issues are picked up before they impact building users. For tenants, this equates to fewer disruptions and a consistently superior indoor environment across all zones, elevating their overall experience and satisfaction and productivity.

Extension of equipment life cycle

Adopting a data-driven approach goes beyond immediate operational benefits; it plays a pivotal role in extending the life cycle of equipment. Through continuous monitoring and timely interventions, wear and tear are mitigated, allowing plant and equipment to function optimally for longer periods. For end users, this means a more reliable system in place, minimising the inconvenience of frequent upgrades or repairs. The overarching advantage? A long-term solution that also promotes sustainability by reducing waste.

Improved sustainability

Data-driven maintenance primes operations teams to maximise efficiency in the utilisation of electricity, gas, and water. This not only curbs a portfolio's carbon footprint but also facilitates elevated sustainability ratings. This has positive implications for meeting Net Zero targets, assisting tenants with their Scope 3 responsibilities, and meeting green lease commitments. The cherry on top? Enhanced eligibility and access to Green finance, making sustainability both an environmental and financial win.

Contractor accountability

Data-driven maintenance also reshapes the dynamics of contractor management. By enabling a more transparent evaluation of contractor performance against predetermined KPIs ensures they adhere to set standards. It provides full oversight over tasks assigned, allowing for real-time tracking of their progress and status. The result is a heightened level of contractor accountability, ensuring optimal performance, timely deliverables, and adherence to quality standards.

Team productivity

By minimising onsite maintenance hours, enabling contractors to directly address the root causes of issues, and facilitating centralised issue resolution, the workflow of the on-site operations team is made more efficient. This newfound efficiency affords the team more time to other priorities, like meaningful engagement with tenants. Further, a digital history ensures the seamless transfer of intelligence between team members, creating a continuous cycle of knowledge-sharing.

In our client’s own words

In an era where data is the cornerstone of informed decision-making, the leading players in the property industry recognise its transformative influence on facilities management. Dive in and hear directly from some of our esteemed clients who are already reaping the benefits of data-driven maintenance through CIM’s PEAK Platform.
“Scheduled maintenance checks and servicing is now a thing of the past as the data helps us determine precisely when and where maintenance is needed. We can now actively anticipate and prevent equipment breakdowns which means equipment is more likely to last its specified lifespan and we don’t have to resort to costly fixes or replacements.”
Damien Stacey
National Capital & Planning Manager, QICGRE
“We want maintenance time to be better spent in a more productive fashion. It's impossible to check every sensor and every actuator every month. We want our BMS and Mech to investigate real alerts. We want time for them to look into the things our FMs care about. That's where analytics like CIM have helped. It finds what's broken and guides better maintenance man-hours.”
Executive Manager
Building Services and Operations for an Australian University
“The platform goes one step further than simply delivering data and analytics; it supplies the insights and central intelligence required to manage our portfolio sustainably and efficiently. This elevates the resilience and long-term viability of our assets, accelerating our approach to addressing climate change and unlocking environmental value.”
Andrew Cole
Group Head ESG at Charter Hall
“Brisbane Airport Corporation was pleased to engage CIM to assist with delivering energy savings, optimising building performance and improving our operations through data-driven decisions.”
Ken Hughes
Head of Airport Facilities, Brisbane Airport Corporation

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