Healthcare facility example
Hospital buildings with Trane BAS
- 39 biased temperature and pressure sensors
- Overcooling followed by reheat
- CO2 sensors not fully utilized
- Short-term energy reduction reported in the historical case material
Results
How LeanFM helped The Andy Warhol Museum uncover BAS logic faults and reduce utility spend by more than $100K per year.
The issues were already in the building data. LeanFM found the patterns, helped prioritize action, and the corrected faults produced measurable savings.
- Hidden faults surfaced from existing building data
- Clear findings tied to operational impact
- Actionable next steps for facilities teams
Building data to findings
1
Existing data
2
Hidden faults
3
Clear action
Case study signal
Logic fault correctedVisible in data
Reported savingsWarhol case study
Operational impactReduced utility use
Proof That Hidden Issues Are Already in the Data
Many building system problems do not appear as obvious alarms. LeanFM looks for patterns across system data to help teams identify what is wasting energy, affecting comfort, or creating unnecessary system strain.
The goal is not more data. The goal is clearer action.
Featured case study
Featured Case Study: The Andy Warhol Museum
The seven-floor mixed-use museum required stable temperature and humidity control for sensitive artwork, visitor comfort, and staff comfort.
Project Details
Owner
Carnegie Museums of Pittsburgh
Location
Pittsburgh, PA
Size
88,000 sq ft
Duration
2023-ongoing
Challenge
After a new BAS was installed in 2021, the museum still needed to reduce HVAC energy waste, improve comfort, protect artwork, support sustainability, and extend equipment life. LeanFM analysis in 2022 found BAS logic faults that were corrected.
What LeanFM Found
The museum had already invested in a BAS. The opportunity was not more hardware. It was finding the hidden logic faults and operating patterns the system was not surfacing clearly enough.
Case Study Results
$56,386
Reported first-year savings
$101,383
Reported second-year savings
$100K+
Ongoing annual savings shown in the case study
- Reduced chilled water and steam usage over time
- Reported savings based on the provided case study
- Corrected logic faults that were already visible in the data
The important point is not just the savings—it is that correctable logic faults were already visible in the data.
Results are from this specific case study. Actual outcomes depend on building conditions, available data, and corrective actions taken.
Trend-style view
Reduced utility usage over time
Chilled waterBefore correction
Chilled waterFirst year
Chilled waterSecond year
SteamBefore correction
SteamFirst year
SteamSecond year
What This Proves
New systems can still hide problems
The Warhol had a newer BAS, but LeanFM still found logic faults affecting performance.
Existing data can reveal missed issues
The value was already in the building data. LeanFM helped surface what mattered.
Small operational issues can create large impact
Correcting hidden faults helped reduce waste and improve operational performance.
Sensitive environments benefit from early detection
Museums need consistency, not just reactive alarms.
Examples of Issues LeanFM Has Identified
Across complex buildings, LeanFM has identified recurring patterns that traditional alarm workflows can miss.
Additional historical examples from complex facilities include:
Large hospital campus example
1.4M sq ft across 4 buildings with JCI BAS
- Software and hardware faults in AHUs and VAVs
- 9.7-14.4% energy waste identified
- Weekly coordination with facilities and HVAC teams
- Issues reviewed with facility manager, HVAC managers, and technicians
Resort and casino example
270K sq ft hospitality facility with Siemens BAS
- 11 days of BAS data analyzed
- $12,000/month in energy waste diagnosed
- Leaking cooling valves and biased temperature sensors identified
- Manual control logic, economizer settings, and overcooling issues found
Large office building example
550K sq ft office facility with Honeywell BAS
- 13 days of data analyzed
- Incorrectly installed relays identified
- Unused BAS sensors found in control programs
- Frequent VFD resets found
The Same Hidden Problems Show Up Across Building Types
Sensor drift
Simultaneous heating and cooling
Overcooling and reheat
BAS logic faults
Equipment running unnecessarily
Control sequence issues
Underused sensors
Unnecessary equipment strain
Every Building Is Different
LeanFM does not promise a fixed savings percentage because every building is different. Results depend on system configuration, available data, operating conditions, and which corrective actions are taken.
But the pattern is consistent: hidden issues often exist in the data before they are obvious in the building.
Built From Real Building Data
Findings tied to actual system behavior
Prioritized issues facilities teams can review
Evidence-based recommendations, not generic advice
Use the Warhol Case Study as a Starting Point
Request a Sample Analysis to find out whether your existing building data contains hidden issues worth reviewing.
Request a Sample Analysis