For a well-managed Class A office building, the obvious problems have usually been solved. The lights are energy-efficient LEDs, the major equipment is on a schedule, and the on-site team is quick to respond to critical alarms. But what about the problems you can’t see?
In our experience, the most significant sources of energy and operational waste are not the catastrophic failures that set off alarms. They are the silent, “invisible” faults that bleed money, day after day, completely undetected by a traditional Building Management System (BMS).
This is the story of one of those faults—and how a data-driven, operational excellence approach turned a hidden problem into a five-figure financial win.
The Challenge: An “Invisible” Problem
The building in question was a modern, well-run office tower. The on-site team was excellent, and the BMS showed no critical alarms. By all traditional measures, the building was operating efficiently. However, our automated building analytics platform, which was continuously analyzing thousands of data points from the building’s systems, flagged a persistent, high-cost anomaly in Air Handling Unit 5 (AHU-5).
The problem was simultaneous heating and cooling. The system’s data showed that the cooling coil valve was open and actively trying to cool the air, while at the same time, the heating coil valve was also open, reheating the same air before it was delivered to the space. The two systems were locked in a constant, invisible, and incredibly expensive battle.
This type of fault is almost impossible for an on-site team to spot. It doesn’t generate a critical alarm because, from the BMS’s perspective, the equipment is “running.” The tenants may not even complain, as the system might be able to maintain the temperature setpoint—it’s just spending a fortune in wasted energy to do so.
The “Operational Excellence Playbook” in Action
This is where a modern, data-driven approach changes the game.
- Detection & Quantification: The automated analytics platform didn’t just flag an anomaly; its Fault Detection and Diagnostics (FDD) engine identified the specific root cause. More importantly, it instantly quantified the financial impact. The platform calculated that this single fault was costing the building over $60 every single day in wasted thermal energy.
- Prioritization & Action: This wasn’t a low-priority alarm in a sea of a thousand others. It was a single, high-cost insight delivered directly to the operations team. The insight was not, “There’s a problem with AHU-5.” It was, “AHU-5 is wasting an estimated $60/day due to a leaking heating coil valve. This is your #1 priority.” Armed with this specific, data-backed directive, the on-site team was able to investigate with confidence. They quickly confirmed the analytics’ findings: the heating coil valve was physically stuck in a partially open position.
- Resolution & Verification: A work order was issued, and a technician performed a simple, low-cost repair on the valve. The problem was solved within hours of the initial investigation.
Crucially, the job wasn’t done. Using a Measurement & Verification (M&V) model, the analytics platform continued to track the performance of AHU-5 post-repair. The M&V report provided definitive proof of the savings, confirming that the simple repair had eliminated the waste and put the building on track for over $22,000 in annualized savings.
This is the power of a value-driven approach. It’s not about having the most data. It’s about having a system that can automatically find the single, actionable insight that delivers the most value, and then proving the financial impact of that action.