Actual office usage measures how your spaces are concretely used on a daily basis, as opposed to what your contracts and fit-out plans provide for. It is the difference between "we have 80 workstations" (theoretical capacity) and "on average, 48 people work here every day" (reality).
Actual usage is measured across several dimensions: how many people are present (presence rate), which spaces are occupied (utilisation rate by zone), at what times (hourly and weekly profile), and how spaces are used (individual work, meeting, collaboration, calls). It is this complete picture that enables the right real estate decisions to be made.
Historically, sizing an office was simple: 1 employee = 1 workstation = 10-12 sqm. Theoretical capacity matched actual usage, give or take a few days of leave and sick days.
Hybrid work has shattered this equation. Three concrete examples:
The company that "has 100 workstations for 100 people". In reality, with 2 days of remote working on average, daily presence oscillates between 45 (Friday) and 78 (Tuesday). The average actual usage is 58 workstations: 42% of capacity serves no purpose.
The company that "has 6 meeting rooms". In reality, the 2 small rooms (2-4 people) are booked 90% of the time, the 2 medium rooms (6-8 people) run at 50%, and the 2 large rooms (12+ people) are used only once a week. The problem is not the number of rooms: it is their size.
The company that "uses 500 sqm". In reality, the west wing (200 sqm) has been almost deserted since the tech team went full remote. The remaining 300 sqm are correctly occupied. It is concentrated waste in a single zone.
For a complete picture, actual usage is measured across 5 axes:
1. Overall presence rate. Number of people present / total headcount. This is the macro indicator. In hybrid mode, it sits between 55 and 65% on average, with strong day-to-day variability (Tuesday 80%, Friday 40%).
2. Utilisation rate by space type. Workstations, meeting rooms (by size), phone booths, collaborative zones, informal spaces. This is the indicator that reveals imbalances: saturated zones (small rooms, phone booths) and deserted zones (large rooms, oversized open plans).
3. Temporal profile. Hour by hour and day by day. Activity starts at 9am, peak between 10am and 12pm, trough between 12:30pm and 2pm, second peak between 2pm and 5pm, gradual emptying after 5:30pm. This curve determines the hours of services (cleaning, reception, maintenance) and the needs for air conditioning/lighting.
4. Type of activity. Are employees coming to the office for individual work (which could be done remotely), for meetings, for informal collaboration, to see their colleagues? This data determines the optimal mix of spaces. If 70% of people come to collaborate, you need more meeting rooms and informal spaces, not more individual workstations.
5. Instantaneous density. Number of people per sqm at a given moment, by zone. Above 1 person per 6 sqm NUA, the feeling of crowding increases. Below 1 per 15 sqm, the space feels "quiet", a feeling that pushes employees to stay home rather than come to an empty office.
Step 1: Define what you are measuring and why. Before deploying sensors, clarify the objective. The objective determines the methods and the granularity.
Step 2: Choose the appropriate method.
For a quick diagnosis (SME, limited budget): manual observation. A survey 3 times a day (10am, 1pm, 4pm) for 4 to 6 weeks.
For precise and continuous measurement: presence sensors. Under desks (thermal sensor), at ceiling level (infrared) or at room doors (entry counter).
For meeting room analysis: cross-referencing bookings vs actual usage. Requires access to data from your booking tool (Outlook, Google Calendar) and a field check for 2 weeks. Reveals ghost meetings (25 to 35% of bookings).
Step 3: Collect over a sufficient duration. 8 to 12 weeks minimum. Avoid atypical periods (August, bank holiday weeks, seminar weeks) or at least identify them in the data. The goal is to capture a typical week. In reality, several are needed because no week is truly typical.
Step 4: Analyse and visualise. Raw data speaks to no one. Produce: a day×hour heatmap (where are the peaks and troughs), a utilisation rate by zone (which spaces are saturated/deserted), a weekly profile (Tuesday vs Friday), and a cost of under-utilisation in euros (unused surface × cost per sqm). It is this last figure that triggers action from management.
Decision 1: Should we move to flex office? Actual usage gives you the optimal flex ratio.
Decision 2: Should we redesign? If small rooms are saturated and large ones deserted, the answer is often yes.
Decision 3: Should we reduce or add value to the surface area? If your actual usage reveals 200 to 300 sqm chronically unused, two paths are available. Return to the landlord (if the lease timing allows). Or add value via an operator like Sora: after a complete financial analysis of your situation, the operator transforms the excess sqm into operated offices and generates recurring income to cover between 50% and more than 100% of the rent on those surfaces, not through subletting, but via a service contract.
Do you suspect under-utilisation of your offices? Measure, quantify, act. Estimate the potential of your spaces with our savings simulator.
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