Use Cases That Deliver Results

^{Fault detection and diagnostics. Identify equipment issues before they cause comfort complaints or failures. A faulty economiser damper, a stuck valve, a sensor drift—analytics can detect these automatically and prioritise them by impact.}

^{Data-driven maintenance. Move from reactive to predictive. Monitor supply air temperatures, valve positions, fan speeds, and filter pressures to identify units requiring attention—before occupants complain or energy waste accumulates.}

^{Chiller plant optimisation. Central plants are the most energy-intensive systems in commercial buildings. Machine learning can identify optimal staging sequences and setpoints—often delivering 10–20% energy savings without capital expenditure.}

^{NABERS performance improvement. Analytics platforms can model the relationship between operational settings and energy consumption, enabling targeted tuning to close the gap between current and target ratings.}

^{Indoor air quality. Track CO₂, particulates, temperature, and humidity in real time. Correlate IAQ data with ventilation rates and occupancy to support NABERS Indoor Environment and WELL certification.}

^{Demand-driven cleaning. Smart bathroom sensors and floor-level people counters enable cleaning schedules driven by actual usage rather than fixed rosters. High-traffic areas receive more attention; low-traffic areas receive less—improving service levels while reducing labour costs.}

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^{Occupancy-based HVAC scheduling. People counting sensors can feed occupancy data to the BMS, enabling demand-based conditioning. Floors with low occupancy receive reduced airflow and adjusted setpoints—reducing energy while maintaining comfort where people are working.}

The Foundation: Data Quality and Network Infrastructure

^{Analytics is only as good as the data feeding it—and the infrastructure that delivers it.}

^{Naming conventions. If every building uses different naming conventions, portfolio-wide analytics becomes impossible. A chilled water supply temperature labelled "CHWS_Temp" in one building, "CW-S-T" in another, and "Chiller_1_Supply" in a third cannot be aggregated or compared. Adopting consistent classification and tagging standards across your portfolio is foundational.}

^{Data completeness and accuracy. Are critical points being trended at appropriate resolution? Are there gaps? A temperature sensor that has drifted 2°C will generate false alarms and misleading insights. Regular validation is essential.}

^{Network architecture. Building OT networks need to support data extraction without compromising stability or security. This requires appropriate segmentation between OT and IT networks, and secure pathways for data to reach analytics platforms.}

^{Secure remote access. Analytics platforms require access to BMS data via secure connections—centralised platforms with multi-factor authentication, time-limited vendor access, and audit logging. Direct internet exposure of building controllers is not acceptable.}

^{Data integration. Multiple systems from different vendors—BMS, lighting, metering, access control—each with different protocols. An integration layer that normalises and aggregates data is often essential for effective analytics.}

^{Governance. Who owns the data? Who maintains naming conventions and ensures quality? Without clear governance, data quality degrades as different contractors make changes without coordination.}

Getting Started

^{Audit your data and network. Understand what data you have, where it lives, how reliable it is, and whether your infrastructure can support secure data extraction.}

^{Standardise naming conventions. Adopt portfolio-wide standards. Retrofit existing buildings progressively—starting with critical assets.}

^{Start with high-impact use cases. Chiller plant optimisation, AHU fault detection, and after-hours energy monitoring typically deliver the fastest payback.}

^{Integrate with workflows. Ensure alerts integrate with CMMS, facilities management, and contractor processes.}

^{Measure and verify. Automated M&V provides confidence that optimisation is delivering real results.}

The Competitive Advantage

^{Buildings with mature analytics capabilities operate more efficiently, maintain equipment more effectively, and achieve better sustainability ratings.
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^{For landlords, this means lower operating costs, higher NABERS ratings, and stronger tenant retention. For tenants, it means better comfort, better air quality, and confidence the building is being operated professionally.}

How Datafied Helps

^{We help building owners develop data strategies, specify analytics platforms, and implement the governance frameworks that make analytics effective. Our experience spans data standards, BMS audits, network reviews, platform selection, and NABERS performance programs.}

^{Ready to unlock the value in your building data?}