Results — Found money, on the record

Case · K-12 schools

The budget line item nobody knew existed.

School220,000 sq ftexisting BAS · no new hardware

$0

in annual savings opportunities identified from existing trend data.

What we found

Heating and cooling running simultaneously across multiple units — comfort held, so nobody saw it
Equipment schedules that didn't match how the building is actually occupied, including weekend and early-morning runtime
Economizer and control-sequence faults quietly shifting load onto mechanical cooling and reheat

Why it matters for schools

A six-figure finding in a single building is a teacher's-aide-sized line item recovered without a bond, a retrofit, or a single new sensor.

Most of the identified fixes are schedule and setpoint changes — work an existing controls contractor can complete in normal maintenance windows.

Case · Museums & cultural

Precision climate, lower cost.

The Andy Warhol MuseumCarnegie Museums of Pittsburgh88,000 sq ft · seven floorsconservation-grade climate

$0

reported first-year savings (2023), growing to $101,383 in year two (2024) — with ongoing annual benefit and the environment never relaxed.

The hard part

A museum can't trade comfort for savings: in this seven-floor mixed-use building, temperature and humidity protect the collection around the clock while keeping visitors and staff comfortable. Every change has to be defensible to conservators, not just accountants.

That made it the right proving ground — the savings had to come entirely from BAS logic faults hiding in existing data, never from relaxing the environment. The analysis (2022) ran on the building's own trend data, with no new hardware.

Why the savings grew

Findings reduced chilled-water and steam usage over time. Year one caught the large, obvious-in-hindsight faults; year two compounded as smaller patterns surfaced and year-one fixes stopped re-breaking silently — $56,386 to $101,383.

This is the pattern we see in long-running deployments — analysis keeps paying because buildings keep drifting.

Research · Higher education

Where the research began.

Carnegie Mellon Universitywhere the Prescriptiv engine began

Born from Carnegie Mellon research

LeanFM's analytics grew out of Carnegie Mellon research — the Prescriptiv engine was developed there. It's the same approach we bring to any campus: read every building's data the same way, where equipment diversity makes manual review impractical.

Campus detail is published as our partners approve it. If you're evaluating for a campus, we're glad to discuss specifics directly.

What campuses use it for

Ranking buildings by opportunity, so limited staff goes where the dollars are
Catching faults in buildings nobody has time to watch
Giving leadership a defensible number for capital and budget planning

Found money, on the record.