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Data is everywhere in our lives today—and buildings are no different.

Managing Buildings in a Time of Scarce Skilled Technicians and More Technological Complexity

Feb. 23, 2024
Analytics-driven facility management is rising as new and increasing pressures drive technology adoption. Top facilities teams can respond smarter, not harder, to these pressures.

Data is pervasive in our lives today. We all expect to log in to a personal device and access anything we need to know. Our bank accounts, health information, educational records, our home appliances—we expect data about everything around us so that we can make decisions and take action in our daily lives.

Buildings should be no different, although many owners still haven’t tapped their data sources to create the insights facility professionals need to understand building performance and act to make it better on their behalf. But the industry is changing fast, and many new and increasing pressures are driving technology adoption to rise to the challenge. Here are a few of those pressures.

There is a shortage of skilled people in facilities management. Skilled facilities personnel are retiring at a faster rate than new people are entering the industry. It is getting harder to recruit and retain people to maintain and service buildings. 

Buildings are becoming more complex. As exciting and impactful new technologies in building automation, HVAC, energy management and even AI make their way into buildings, it is becoming simultaneously more complex to manage buildings effectively and simpler with the right mix of technology, process and people.  

Decarbonization and electrification initiatives are driving urgency for change. Governments and corporations alike are driving sustainability, carbon reduction and energy management efforts to decarbonize and electrify buildings. For example, as local regulations in cities like New York and Boston take effect with real financial consequences, facilities teams are under pressure to reduce and maintain low carbon emissions. 

The dramatic impact of buildings on our health, productivity and daily life is more evident now than ever before. The pandemic shined a light on the impact of indoor environmental quality on people’s health and productivity. Facilities teams play a critical role in delivering these quality environments. 

Responding to Pressure: Smarter, Not Harder 

With pressures like these, facilities teams need strategies that make it easier to fulfill the goals of their organization with the limited resources they are given. Working smarter, not harder, has never been more relevant in an industry full of hard-working professionals. Automated analytics software provides solutions, and relief, for these challenges.  

Automated building analytics combines building automation systems (BAS) and utility data with metadata about equipment, systems engineering and controls to create new insights for facility teams—including identifying the highest-impact energy and mechanical issues in their buildings. It creates a baseline understanding of how buildings systems are performing, timely enough to do something about it and without relying on the limited availability of engineers who can’t pore over building data all day long.

Through innovative machine learning techniques to streamline the onboarding of buildings and tried and true methods of energy engineering analysis, analytics produce insights that previously could only be done through engineering consulting studies a few buildings at a time. 

Through automated analytics, it is already possible to have portfolio-wide insights about building systems and performance like never before. Across a global portfolio, fault detection and diagnostics (FDD) can pinpoint that one air handler, in one site, on the other side of the world, has the most potential to reduce operational carbon emissions because it is a large, 100% outdoor air unit with a carbon-intensive utility mix and a faulty valve or control.  An experienced technician or engineer can review such diagnostic information condensed and prioritized from millions of data points across thousands of pieces of equipment, normalized to engineering units, currencies, energy and carbon metrics they are familiar with, consistent across all assets, every day.  

While changes to one air handler alone won’t meet the energy, carbon, operating cost, reliability or IEQ goals of an organization, the systematic adoption of these automated analytics into daily facilities management prioritization, escalation, and resolution workflows is what drives massive impact in improving building portfolio performance. Analytics are a force-multiplier, enabling resource-constrained maintenance and service teams to manage more assets at higher performance than traditional maintenance. 

The most advanced organizations have already deployed fault detection and diagnostics, virtual metering and system benchmarking analytics across their portfolios and are incorporating those insights into broader facilities management strategy. This includes streamlining the resolution of issues with work order system integration and adopting condition-based maintenance strategies that reduce the amount of reactive and scheduled maintenance, focusing their resources on critical assets and the most important issues. 

As analytics-driven facilities management continues to mature, expect more organizations to also use analytics information in capital planning, by factoring faulty performance histories and costly repair options into capital planning decisions. At the most cutting edge, it is already possible at a small-scale and will become increasingly possible at large-scale to automatically implement energy and carbon savings measures or fix certain fault detection and diagnostic findings with limited and selective human oversight.

While buildings are becoming more complex and the people available to manage them become fewer, technology is available to work smarter and enable facilities professionals to drive massive positive impact across buildings around the world. 

About the Author

Nick Gayeski

Nick Gayeski is co-CEO of Clockworks Analytics.

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