How to Measure Space Utilization on a University Campus

Most US and UK campuses run their academic buildings somewhere between 25 and 45% utilization, and many planners can’t tell you which buildings are pulling down the average. The data exists.

It just lives in 4 places at once: timetabling software, building swipe systems, sensor dashboards, and the memory of the facilities team that walks the corridors at 2pm.

Facilities directors, space planners, and operations VPs need a real number on campus utilization before any big decisions about leases, renovations, or new construction. Here’s how to get one.

What space utilization actually measures

Space utilization (check out this guide) is one number built from two others.

Frequency is the share of available hours a room is used. If a seminar room is open 40 hours a week and gets booked for 24, frequency is 60%.

Occupancy is the share of seats filled when the room is in use. If that seminar room seats 30 and the average session has 18 students in it, occupancy is 60%.

Utilization is frequency multiplied by occupancy. In this case, 60% x 60% = 36%.

That last number is the one that matters. A room booked every hour but half-empty during each session is doing the same work as a room booked half the time but packed when in use.

One caveat. “Available hours” is a definition your team owns. Some institutions count 9am to 5pm Monday to Friday (40 hours). Others count 8am to 9pm Monday to Friday plus Saturday morning (60+ hours).

The benchmark you compare against has to use the same window, or the comparison is meaningless. The SCUP and NACUBO joint resource on data-informed space utilization makes this point repeatedly: agree on definitions internally before you measure anything externally.

Space utilization and workplace analytics are among the must-have features to look for when choosing the best hybrid work solution for your organization.

Why your timetable lies

Guess what – a booking records who reserved a room, not who used it.

Consider a 200-seat lecture hall booked Tuesday at 10am for a survey course. The timetable says: 100% frequency for that hour, 100% occupancy assumed, 100% utilization. The reality on a typical Tuesday in week 7: 62 students physically present.

The same room books at 11am for a lab section that gets cancelled because the instructor is at a conference. No one updates the calendar. The room sits empty. Frequency in the data: 100%. Frequency on the floor: 0%.

Across a 14-week semester, those gaps compound. Booked use and actual use are two different measurements, and most campuses are still confusing the two.

The fix is straightforward: measure both, and treat the gap between them as one of the most useful numbers you have.

3 data sources and where each falls short

1. Booking and scheduling data

What it tells you: who reserved what, when, for how long, and which department owns the booking.

Where it falls short: it counts intent, not presence. A 200-seat hall booked for a 30-person seminar reads as fully booked. A “ghost booking” that no one cancels reads as use. Recurring weekly bookings that haven’t met since week 3 of the semester still register.

The fix: combine booking data with cancellation data, and require check-ins for any booking over a certain size. A room ignored for 15 minutes past the start time gets released. Most modern booking platforms do this automatically.

2. Sensors and people counting

What it tells you: how many people were actually in the room, and when.

Sensor types vary. Passive infrared (PIR) sensors detect motion but don’t count. Wi-Fi probe counting estimates crowd size from device signals. Computer vision cameras count heads. Thermal sensors count without identifying anyone, which matters for GDPR in Europe and student privacy in the US.

Where it falls short: cost, installation friction, and noise. Wi-Fi counting overcounts students who carry 2 devices. PIR misses still classes. Cameras raise privacy reviews that can take 6 months to get through governance. Sensor data also tells you nothing about who used the room or why.

The fix: pick one sensor type per space class. Lecture halls do well with thermal or vision counters. Study rooms and faculty offices do well with PIR plus desk reservation data. Don’t try to instrument every room. Instrument the 15 to 20% that drive the most decisions.

3. Manual audits

What it tells you: ground truth.

The classic method, used by UK and Australian universities for decades, is the room-by-room walk-through. An auditor visits each room at fixed intervals (every 30 or 60 minutes), records whether it’s in use, and counts heads.

Two weeks of audits across a typical week gets you a defensible utilization number for a fraction of the cost of sensors.

Where it falls short: labor. A campus of 800 timetabled rooms needs roughly 200 to 300 hours of auditor time per cycle. The data also goes stale fast. By the time the report is written, the semester has changed.

The fix: use manual audits to calibrate. Run a 4-week audit once, get a true baseline, then use booking and sensor data going forward, with annual audit re-checks for drift.

Benchmarks worth using

The most cited target in the field comes from the UK National Audit Office’s 1996 Good Practice Guide and the Space Management Group’s 2006 follow-up: utilization of 35% or above is good, 25 to 35% is fair, below 25% is poor. Most UK universities still use these bands.

In Australia, TEFMA’s target is higher: 75% frequency multiplied by 75% occupancy gives a 56% utilization goal. In Virginia, the State Council of Higher Education for Virginia targets 60% x 60%, or 36%.

The honest read: these targets are policy decisions about how hard a campus should work its rooms. A 35% target reflects the reality that timetables don’t fill evenly, that students don’t show up at 8am, and that pedagogy needs slack. Pushing the same campus to 56% will produce schedules that work on paper and break in practice.

Two practical rules:

1. Don’t benchmark across countries without adjusting for available-hours definitions. A 35% UK number and a 40% US number may describe the same building.
2. Benchmark against your own historical data first. A campus that moved from 22% to 31% in 3 years is doing better than one that has held flat at 38%.

The Education Advisory Board’s analysis of multiple consulting reports shows how much benchmark choice changes the story. Across reports, actual classroom utilization varied from 18.6 to 29.5 weekly room hours, while the targets used in those same reports ranged from 24 to 40. Some institutions with high actual numbers got told they had problems.

Some with lower numbers got told they were on target. The benchmark drove the conclusion.

A 4-week audit you can run before buying anything

If you’re building the business case for a booking platform or a renovation, run this audit first. It takes 4 weeks, costs roughly $8,000 to $15,000 in auditor time, depending on campus size, and gives you a defensible baseline.

Week 1: scope and definitions.

Pick 30 to 50 representative rooms across building types (lecture halls, seminar rooms, labs, study rooms, faculty offices). Agree on available hours per room class. Pull existing booking data for those rooms for the past 14 weeks. Get a privacy review started if you plan to use any sensor or video data.

Weeks 2 and 3: observation.

Run room-by-room audits at 30-minute intervals during operating hours, 5 days a week. For each visit, record: room ID, time, in-use yes/no, headcount, and apparent activity (class, study, meeting, idle). Two auditors with clipboards and a Google Form is enough. Pair this with whatever booking data your timetabling system already produces.

Week 4: analysis and reporting.

Compute frequency, occupancy, and utilization for each room and each room class. Compare booked frequency to observed frequency.

The gap between them is your no-show rate. Build a simple report with 4 charts: utilization by room class, utilization by time of day, the booked-versus-actual gap, and the 10 most underused rooms by square footage.

Expected findings, based on what most campuses see: peak demand will cluster between 10am and 2pm, off-peak hours will look almost empty, lecture halls will be oversized for the classes assigned to them, and at least 1 building will turn out to be a candidate for repurposing or release.

These findings give you the case for whatever comes next. If new software is part of that case, the questions to put to scheduling vendors get much more specific once you have a real baseline to compare against.

What to do with the data

Once you have a real utilization number, the conversation changes. You stop arguing about whether the campus is overbuilt and start deciding what to do about it.

Common actions, in rough order of how often they get taken:

1. Right-size classroom assignments. Move the 30-person class out of the 200-seat hall. This is the highest-frequency win and the easiest sell to academic departments.
2. Consolidate underused buildings during low-demand periods. Close one wing on Fridays. Run summer programs in 2 buildings instead of 5.
3. Introduce booking and check-in workflows for shared rooms and for shared desk areas used by hybrid faculty and staff. Released no-show bookings recover 8 to 15% of frequency in most studies.
4. Make the case for repurposing or release. A building below 20% utilization for 2 consecutive years is a capital planning conversation.
5. Inform new construction decisions. If existing space sits at 30% utilization, a new building should require either a 50%+ utilization commitment or a documented activity that current space can’t support.

Measuring before deciding matters more than which platform you pick. Universities that ran a clean baseline first tend to choose simpler tools and get more out of them. The right university booking software handles the booking, check-in, and reporting side once the baseline is in place. The audit comes first.

The single most useful exercise for any campus space team in the next academic year is the 4-week audit described above.

The number it produces will be defensible across the provost’s office, the CFO, the deans, and the facilities team. Once that number exists, decisions about renovations, leases, hybrid policies, and new buildings get faster and quieter.

Resources

• SCUP and NACUBO. Data-Informed Space Utilization: Cultivating Partnerships (2022). Definitions, governance, and the case for agreeing on space data before benchmarking. https://www.scup.org/resource/nacubo-data-informed-space-utilization-cultivating-partnerships/
• Education Advisory Board. Why space utilization reports may not be actionable enough for higher ed leaders (2025). Analysis of how benchmark choice changes conclusions across consulting reports, with weekly room hour ranges. https://eab.com/resources/blog/strategy-blog/space-utilization-reports-not-actionable-enough-higher-ed-leaders/
• Ye et al. An Empirical Study on Assessing Classroom Space Utilization Efficiency in Higher Education Institutions. MDPI Buildings (2025). Reference for the UK National Audit Office 1996 thresholds (35%+ good, 25 to 35% moderate, below 25% inefficient). https://www.mdpi.com/2075-5309/16/10/1929
• Abdullah, Mohd. Ali, and Alias. Classroom Management: Measuring Space Usage (2012). Comparative reference for TEFMA’s 56.25% target, SCHEV’s 36% target for Virginia, and the SMG 2006 benchmark bands. https://www.researchgate.net/publication/239938981_Classroom_Management_Measuring_Space_Usage
• Occuspace. Top Platforms for University Space Utilization Reports (2026). Source for the Fall 2025 average campus utilization figure of 45%, down from 53% the year before. https://www.occuspace.com/blog/top-platforms-for-university-space-utilization-reports