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The Occupancy Data Trap: Why 80% Peak and 53% Average Don't Mean What Your Badge System Says
BLUF: CBRE's 2026 benchmark shows average peak office utilization just crossed 80% globally — beating the long-standing >65% target for the first time since the pandemic. But the same dataset puts average utilization at 53%, and sensor vendors measuring actual desk presence report capacity usage as low as 9–11%. Three numbers, three different truths. If you rightsize your portfolio to the average, your peak days break. If you trust your badge system alone, you're flying on a proxy that never sees the desk. Here's how I'd separate signal from noise before signing a stacking plan.
The three numbers every FM is now staring at
The 2026 occupancy picture finally looks healthy on paper. After three years of "the office is dead" headlines, the data turned:
| Metric | 2026 Value | Source | What it actually measures |
|---|---|---|---|
| Average peak utilization (global) | 80% | CBRE 2026 Global Workplace & Occupancy Insights | Busiest day, busiest hour — the design constraint |
| Average utilization (global) | 53% (vs 38% in 2024, 35% in 2023) | CBRE 2026 | Mean across all days/hours — the budget number |
| APAC average utilization (Q2–Q3 2025) | 47% — now #1 region globally | Colliers 2026 Asia Pacific Workplace Insights | Regional mean, first time APAC leads |
| Capacity usage / peak (sensor-measured) | 9–11% avg / 52–60% peak | VergeSense Workplace Index, 9th Edition | Actual bodies at seats, sensor-verified |
| Desks used < 1 hour/day (APAC) | 43% | Colliers 2026 | Assigned-but-idle seats |
The spread between CBRE's 53% and VergeSense's 9–11% is not a contradiction — it's a measurement-method gap. CBRE's headline blends badge swipes, reservation systems, and sensor feeds across a 303-million-sq-ft client portfolio. VergeSense's number is pure sensor "active occupancy" — a person physically detected at a specific seat. Badge data counts a person once when they enter the building; it never knows whether they sat at a desk, parked in a focus room, or spent six hours in conference rooms. That's why 43% of APAC desks see less than an hour of use a day even when the building "feels full."
Why this is a trap, not just a stat
Here's the failure mode I watch for. A workplace lead sees "53% average utilization" and concludes the portfolio is half-empty, so they propose cutting 30% of the floorplate. Then the first all-hands Tuesday hits 80% peak, there are no seats, and the RTO mandate they just signed collapses into a parking-lot fight over desks. The Amazon-scale version of this — planning to average and getting crushed by peak — is the single most expensive occupancy mistake of the hybrid era.
The discipline is simple to state and hard to hold: you rightsize against peak demand, you budget energy and services against average, and you only trust a "cut the floorplate" decision when sensor data confirms the badge story.
The accuracy ladder: what each signal can and can't tell you
CBRE reports that 90% of occupiers still measure utilization via security badging, 52% layer in reservation/booking systems, and 56% plan to add sensor or Wi-Fi analytics in 2026. Each rung up the ladder costs more and tells you something the rung below cannot:
| Signal | What it sees | Blind spot | Typical accuracy |
|---|---|---|---|
| Badge / access control | Building entry counts | Where people go after the turnstile | High for "in building," zero for "at desk" |
| Wi-Fi / device association | Floor- and zone-level presence | Phantom devices, multi-device users, desk-level granularity | Zone-accurate, not seat-accurate |
| Booking / reservation | Intent to use a space | "Ghost bookings" — reserved, never shown | Intent only, not actual use |
| Optical / depth sensors (e.g. VergeSense, Density) | Person count + active vs passive occupancy | Cost, privacy review, install | Up to ~95% (VergeSense Infinity Area Sensor) |
| Thermal sensors (e.g. Butlr, Avuity) | Presence/headcount, camera-free | Lower precision on identity-level detail (by design) | Good for counts, privacy-friendly |
The most useful concept the sensor vendors have added is passive occupancy — a seat claimed by belongings (a bag, a laptop, a jacket) with no person present. VergeSense's Meridian platform unifies sensor, badge, Wi-Fi, and booking signals into one model precisely because no single feed catches both the "ghost booking" and the "ghost desk." Density takes the API-first route, pushing depth- and radar-based desk-level data into the BMS and third-party dashboards.
The APAC privacy guardrail you cannot skip
For Taiwan, Singapore, and Hong Kong deployments, the privacy posture decides which rung of the ladder you can legally climb. The good news: neither Singapore's PDPA nor Hong Kong's Personal Data (Privacy) Ordinance (Cap. 486) prohibits occupancy monitoring. The catch: both require transparency, a legitimate business purpose, and informed notice before you collect. This is exactly why the thermal/anonymous-count vendors (Butlr, Avuity) win APAC pilots — camera-free, headcount-only sensors collect no personal data at all, which sidesteps the heaviest consent obligations. If you're in a PDPA/PDPO jurisdiction, start the privacy review before the sensor RFP, not after.
Here's what I'd do if this were my building
- Separate your two target numbers. Set a rightsizing target against the 80th-percentile peak day (not the headline peak hour), and a separate energy/services budget against the 53% average. Never let one number drive both decisions.
- Run a 6–8 week sensor truth-test before any floorplate cut. Overlay anonymous occupancy sensors on one representative floor and compare against your badge data. If badge says 60% and sensors say 35% active, your "underused" floor is real — but you've just learned your badge baseline runs ~25 points hot. Recalibrate every downstream decision by that gap.
- Kill ghost bookings first — it's free capacity. With 43% of APAC desks used under an hour a day, auto-release booked-but-unoccupied desks and rooms (sensor-triggered, 15-minute no-show). This recovers peak-day capacity without signing a single new lease.
- Wire occupancy into HVAC and cleaning before you wire it into headcount. The fastest, least political ROI on occupancy data is demand-driven HVAC and cleaning — services that respond to real presence instead of a static 7am-to-7pm schedule. Energy savings land in months; the rightsizing debate takes quarters.
- Budget for the data-capability gap, not just the sensors. Only 7% of organizations rate their occupancy data capabilities as "excellent," and 55% cite data quality and lack of expertise as the top barrier. The sensor is the cheap part. Plan for the analyst (or the platform) that turns the feed into a stacking decision.
The bottom line
2026 is the year occupancy crossed from "is anyone coming back?" to "are we measuring the right thing?" Peak hit 80%, average hit 53%, and sensors say the real seat-level number is lower still. The portfolios that win the next lease cycle won't be the ones with the most sensors — they'll be the ones who knew which number to trust for which decision. Fuse your signals, calibrate your badge baseline, and rightsize to peak.
For more on the sensor-accuracy and privacy trade-offs behind these deployments, see our companion analysis in the AISB Library, and explore how multi-signal fusion feeds demand-driven building control across our coverage.
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