LeanFM analyzes existing HVAC trend data to find the hidden faults your BAS alarms aren’t catching — and ranks them so your team knows exactly what to fix first.
Trusted by a Pittsburgh-area cultural institution. See the case study →
Prioritized diagnostic finding
Cooling and reheat appear active during occupied periods, creating avoidable energy use and comfort instability.
Energy waste
Comfort risk
Equipment wear
Evidence reviewed
Recommended action
Review sequence logic and occupied schedule behavior.
Up to 30% of energy spend wasted
Hidden HVAC faults that BAS alarms miss can quietly drain up to 30% of building energy spend.
3–5x ROI in energy savings
Backed by our money-back guarantee.
Developed at Carnegie Mellon
LeanFM’s methodology was developed from research at Carnegie Mellon University.
$101,383 saved in year two
Documented at a local museum where LeanFM identified BAS logic faults hiding in existing data.
BAS alarms flag obvious failures or out-of-range conditions. Many costly HVAC issues do not look like alarms. They show up as patterns over time.
LeanFM does not start with new hardware. It starts with the system data your building already produces.
Runtime · Setpoints · Schedules · Sensors
Waste · Drift · Conflicts · Logic Faults
Prioritize · Assign · Resolve
LeanFM delivers findings through OnPoint, our software platform, powered by the Prescriptiv analytics engine developed from research at Carnegie Mellon University. Your team reviews prioritized issues in plain English — no new hardware, no dashboards to decipher.
What we are
Developed at Carnegie Mellon. Tested in real institutional buildings. Backed by a money-back ROI guarantee.
What we are not
The issues are technical underneath, but the operating impact is easy to recognize: waste, comfort risk, wear, and unclear priorities.
What it looks like
Blue cooling and orange heating behavior overlap during occupied periods.
Why it gets missed
Each loop may appear normal while the combined behavior wastes energy.
What it can cost
Energy waste, comfort instability, and unnecessary equipment wear.
What LeanFM surfaces
LeanFM highlights the zones and times where the conflict appears in trend data.
What it looks like
Actual runtime extends beyond the occupied schedule or expected building use.
Why it gets missed
Overrides and schedules can drift without creating an alarm condition.
What it can cost
Higher utility costs, avoidable runtime, and premature wear.
What LeanFM surfaces
LeanFM compares runtime patterns against schedules and building context.
What it looks like
Reported sensor values drift away from actual operating conditions.
Why it gets missed
A sensor can be wrong enough to affect control without crossing a threshold.
What it can cost
Bad control decisions, comfort complaints, and misdiagnosed problems.
What LeanFM surfaces
LeanFM flags sensor behavior that may be driving the wrong response.
What it looks like
The BAS follows a sequence that no longer matches building operation.
Why it gets missed
The system may be doing exactly what it was configured to do, even when the logic is wrong.
What it can cost
Recurring issues, hidden waste, and unstable operation.
What LeanFM surfaces
LeanFM identifies control patterns worth review by facilities or controls teams.
Featured Case Study
A local museum had already installed a new BAS. LeanFM found logic faults hiding in the data, and the case study shows documented savings after those faults were corrected.
$56,386
reported first-year savings
$101,383
reported second-year savings
$100K+
ongoing annual savings shown in the case study
Actual outcomes depend on building conditions, available data, and corrective actions taken.
LeanFM is built for teams managing real facilities, complex schedules, comfort expectations, and operating budgets.
Find hidden HVAC issues driving complaints, budget pressure, and maintenance strain across district buildings.
Protect sensitive environments by finding subtle system drift and hidden control issues.
Bring clarity to complex campus systems, schedules, and building portfolios.
Identify hidden HVAC waste affecting operating costs, tenant comfort, and asset performance.
Request a Sample Analysis and LeanFM will help determine whether your existing building data contains hidden issues worth attention.
Prioritized diagnostic finding
Existing BAS trends can point to issues worth reviewing before they become larger operating problems.
Energy waste
Comfort risk
Equipment wear
Evidence reviewed
Recommended action
Review sequence logic and occupied schedule behavior.