Are Facility Teams Facing the Same Challenges After Ten Years?
I recently found myself reviewing an article published on AutomatedBuildings.com in November of 2015 (more than ten years ago). At the time, the piece set out to predict what facility managers would need over the next decade…. which would bring us to today.
https://www.automatedbuildings.com/news/nov15/articles/hydro/151016123606hydro.html
Reading it today raises an unavoidable question:
How did things actually pan out? Did we achieve what we thought we needed?
The original article outlined a clear need for data, analytics, and increased intelligence within buildings. Seems very similar to the needs of our modern building operations. The way those needs show up today looks very different though with AI in play. Do we still need these things or have our needs changed?
The 2015 Vision: What We Needed Then
Visualization and Reporting
Visualization and reporting were positioned as the foundation to building analytics. There was a need for tools focused on transforming raw utility, submeter, and sensor data into charts and dashboards that humans could interpret.
The assumption was that awareness would drive change. If people see how energy was being used, they would make better decisions.
Fault Detection and Diagnostics (FDD)
Fault Detection and Diagnostics represented a meaningful step forward. Instead of waiting for equipment to fail, FDD aimed to identify anomalies early and therefore detect faults before they happened.
A classic example was monitoring the electrical current of an air handling unit’s blower motor. Deviations from expected behavior could indicate an impending failure, allowing teams to intervene before occupants felt the impact.
The critical assumption for this is detection is only valuable if someone is watching and acting.
Predictive Maintenance and Continuous Improvement
In conjunction with FDD, predictive maintenance would be triggered by actual equipment conditions and performance trends and deliver communications to the facility manager for needed repairs.
The promise was compelling:
- Fewer emergency repairs
- Longer asset life
- Better alignment between operations and real-world usage
The subtle shift from reactive to predictive maintenance is leaning heavily on the assumption that facilities management was becoming a data-driven discipline, not just a mechanical one.
Optimization
Optimization represented the most advanced capability 10 years ago. By using real-time conditions to adjust setpoints, schedules, and control strategies, buildings could continuously fine-tune themselves.
But optimization also introduced risk. Relinquishing control to a computer required trust in data quality, system integration, and logic correctness.
In 2015, this was still the frontier.
The 2026 Review: Do We Still Need the Same Things?
Everything in this original article was correct.
In fact, most facility teams still want these basic requirements:
- Integrated data
- Clear visibility
- Early fault detection
- Predictive maintenance
- Ongoing optimization
So the question isn’t whether these needs still exist. They do.
The real question is:
As we satisfy these needs, how does AI fit in?
Enter AI: Changing How We Solve Our Needs
Artificial intelligence didn’t eliminate these needs. Rather it reframes them.
Where earlier systems focused on presenting information, modern systems focus on acting on information. Where specialized humans once served as the primary interpreters of analytics, AI systems can now recognize patterns, compare outcomes, and adjust behavior continuously.
This leads to new, uncomfortable questions for facility teams:
- If software can detect faults, predict failures, and optimize performance faster than humans, what should people focus on?
- At what point does AI’s “decision support” become “decision making”?
- How much autonomy are we willing to give our buildings?
- And perhaps most importantly: How must facility teams adjust?
So What Do Facility Teams Need Now?
In order to have visualization and reporting, fault detection and diagnostics, predictive maintenance, and optimization, what do facility teams need different than what was needed a decade ago?
The answer comes down to relationships:
- The relationship between humans and artificial intelligence (AI)
- The relationship between data and decisions
- The relationship between automation and human oversight
Facilities teams today don’t just need better dashboards or more alerts.
They need solutions that:
- Reduce cognitive load, while improving overall team performance
- Take autonomous action, and explain why
- Learn continuously, and elevate our collective human knowledge about controls
And more than anything, our industry needs leaders who are willing to ask:
As our buildings become fully automated, what is our role as the guardians of our built spaces?
This question may define the next decade of facilities management more than any technology ever could.
As our buildings become fully automated, what is our role as the guardians of our built spaces?
