What it means
An office has 200 desks but only 90 are occupied on an average measured workday, so its desk utilisation is 45% under that definition, though the result does not tell whether the office runs out of desks on Tuesdays. JLL recommends a deliberate plan for measuring building space use, with resources and sampling window matched to the decision, since a meeting room, desk and entire floor are not interchangeable units.
CBRE discusses hybrid-workplace capacity and peak demand, noting that design decisions must account for variation, not just averages, because a small average can coexist with a high peak. A fictional software firm measures desk occupancy by hour across several weeks and finds low Monday and Friday use but a busy midweek, so it avoids cutting desks from the weekly average alone.
Utilisation differs from occupancy and allocation in some workplace systems, since a desk assigned to an employee may sit empty most days and a booked meeting room may be unused despite its reservation. A fictional bank has 120 assigned desks and 80 occupied on an average day, but it also needs secure rooms for certain work, so it cannot replace every desk with open seating based only on the 80 count.
Sensors, booking logs and manual walks provide different evidence: booking data show intention, while sensors and observation show presence, each with its own limitations, so choose a method appropriate to privacy and accuracy needs. JLL's workplace utilisation guidance highlights patterns across time and space types, so a useful report might show average and peak room use by hour and also record spaces out of service.
A fictional consultancy books ten rooms daily but sees only six actually used, and it changes cancellation reminders before building more rooms, because the booking metric had exaggerated demand. A simple desk ratio divides occupied desks by usable desks at each observation, then summarises over the relevant period, and if the denominator excludes closed desks, document why, since changing capacity silently distorts trends.
Floor-area utilisation may use a different method, such as regularly occupied area versus available area, and should not be directly compared with desk occupancy, so define the measure in the chart title. Averages can hide poor distribution, because one floor may be crowded while another is almost empty, and access rules, team needs and equipment can prevent simple redistribution.
A fictional design studio sees low total utilisation but high demand for large project tables, so it changes the space mix rather than reducing its footprint immediately, showing that the type of space matters. Space use has cost implications, since rent, utilities and service costs continue when rooms are empty, but moving or redesigning can require capital spending and disruption.
Ask employees why certain spaces are avoided, because noise, accessibility, equipment or temperature may explain apparently spare capacity and a lower utilisation figure can be a symptom of poor design, as when a fictional office's quiet rooms rarely show in booking data because workers use them informally for focused calls, and manual observation prevents them from being wrongly removed. Privacy matters in monitoring, so aggregate use for planning and follow applicable workplace rules, without tracking identifiable movement unless there is an appropriate basis and safeguards.
Seasonality and special events change use, so measure enough weeks to represent normal work and report holidays or construction closures, because a snapshot during a conference is not a steady-state baseline, and compare utilisation with service outcomes since overcrowding, meeting delays and employee experience may worsen if capacity is cut too far. A manager can test an adjustment before signing a smaller lease by shifting booking policies or reconfiguring a floor and measuring peaks again while keeping flexibility for future growth, and space utilisation is credible when the unit, data source and peak patterns are explicit, used with employee needs and not instead of them, since efficient space is not necessarily maximum occupancy.
In practice
Real-world examples.
Example
An office measures occupied desks across a normal workweek.
Example
A team compares meeting-room bookings with actual use.
Example
A company checks midweek peaks before reducing capacity.
Formula
Calculation
Illustrative desk utilisation = observed occupied usable desks / total usable desks x 100% for the same time point. Summarise the series with average and peak.
Worked example: a fictional media firm has 100 usable desks and counts occupied desks at midday on five days: 30, 85, 70, 60 and 30. The daily utilisation figures are 30%, 85%, 70%, 60% and 30%. The average is (30 + 85 + 70 + 60 + 30) / 5 = 275 / 5 = 55%, and the peak is 85%. A lease-cut target based on the 55% average would leave only 55 desks, which is 30 short on the busiest day, so the peak plus a buffer is the safer planning basis.Case study
Seen in the real world.
In this fictional case, Alder Media has 100 usable desks. An eight-week study finds an average of 55 occupied but peaks above 85 on certain days. The company keeps enough capacity for peaks and changes how rooms are booked. It does not use the 55 percent average as a direct lease-cut target.
Watch out
Common mistakes.
- Treating assigned desks as proof of actual use.
- Cutting space from an average while ignoring peak days.
- Comparing room bookings with occupied-desk counts.
Questions
People also ask.
Is space utilisation the same as occupancy?
Definitions vary; specify the resource and measurement method.
Why measure peaks?
An average can hide times when capacity is insufficient.
Can booking logs prove usage?
Not alone. Reserved space may be empty, and some use is unbooked.
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