Space Utilisation Data: What FM Managers Need to Know Before They Redesign Anything

Maxcene Crowe
Apr 8
6 min read

Modern open plan office workspace - Space Utilisation FM

The Uncomfortable Truth About Most Workplace Redesigns

Most workplace redesigns are not driven by occupancy data. They are driven by opinion — a senior leader who decided the office "feels empty," a lease renewal that forced a conversation, or a post-pandemic hunch that things have changed. They have changed. But not in the way most people assume, and certainly not uniformly.

Before you pull a single desk or knock through a wall, you need to understand what your space is actually doing — and what the data is telling you that your instincts are not.

This post is a practical brief on space utilisation data: what it is, what it tells you, and how to use it to make decisions that hold up under scrutiny.

What Space Utilisation Data Actually Tells You (And What It Doesn't)

Space utilisation data tells you how often spaces are occupied, when they are occupied, and for how long. It gives you a factual baseline against which to test assumptions.

It does not tell you why spaces are or aren't used. A meeting room that sits empty every Friday might be a policy issue, a booking friction problem, a commute pattern, or simply poor location relative to the teams who need it. Data gives you the signal. You still need to interrogate the cause.

It also does not tell you what the future looks like. It captures current behaviour — which, in a hybrid working environment, is itself still evolving. According to the HubStar Hybrid Occupancy Index 2025–2026, global average occupancy is stabilising in the 50–60% range, with vacancy rates of 40–50% on average — but that average masks enormous variation by day, building, city, and sector.

Used correctly, space utilisation data removes the politics from the redesign conversation. Used incorrectly, it becomes a justification for decisions that were already made.

The 3 Types of Occupancy Data

Not all occupancy data is created equal. FM managers need to understand what each type measures — and where it breaks down.

1. Point-in-Time Data

Manual headcounts, periodic surveys, or walkthrough audits. Fast and inexpensive to collect, but inherently limited. A snapshot taken at 10 AM on a Wednesday tells you almost nothing about utilisation at 4 PM on a Monday. Useful as a sanity check; unreliable as a planning foundation.

2. Continuous Sensor Data

IoT-based occupancy sensors — PIR motion detectors, CO₂ monitors, desk-level heat sensors — provide real-time, continuous occupancy readings. Dexterra Group notes that IoT sensors now provide real-time insight into occupancy, environmental conditions, and equipment performance simultaneously. As of 2025, 28% of organisations have embedded AI solutions in their FM operations — many of them starting with sensor-driven occupancy analytics. This is your most accurate data source for understanding true utilisation patterns, but it requires upfront infrastructure investment and data governance to make sense of the output.

3. Booking and Access Data

Room booking systems, desk reservation platforms, and building access records. Cheap to extract because the infrastructure already exists. The problem: bookings are not the same as occupancy. A meeting room booked for 90 minutes may only be occupied for 40. Access card swipes tell you someone entered the building — not which floor they went to or whether they stayed. Use this data as a proxy, not a measure.

In practice, robust space planning combines all three. Sensor data provides the accuracy; booking and access data provides the operational context; point-in-time surveys provide the qualitative layer.

Post-Pandemic Hybrid Working: What the Utilisation Patterns Tell Us

The contrarian statement FM needs to hear: The office is not dying — but it has fundamentally restructured itself around three days a week, and the buildings most organisations occupy were not designed for that.

The data is now clear. JLL's Global Occupancy Planning Benchmark Report 2025 puts global office utilisation at 54%, up from 49% in 2024 — but utilisation targets are set at 79%, meaning most organisations are operating with a structural deficit of roughly 25 percentage points. The UK picture is similar: average weekly occupancy hit 37.8% in March 2025, its highest since the pandemic — but still well below pre-pandemic norms of 60–80%, per Remit Consulting data.

The pattern is consistent everywhere: Tuesdays are the peak day (58.6% global occupancy, 75% in London), while Fridays remain the quietest at 34.5%. The informal three-day office week — Tuesday to Thursday — has become an embedded default, not a transitional arrangement.

This creates a specific FM problem: not too little space overall, but the wrong space in the wrong configuration. Research from Wave Connect shows that 36% of desks are never used at all; only 14% of workstations are used for five hours or more per day. Meanwhile, small meeting rooms (2–3 person capacity) are hitting 90% occupancy on core days — while large boardrooms sit below 12% utilisation. That mismatch is not an accident. It is what peak-day compression looks like when nobody has reconfigured the space to match how people actually work.

How to Build a Defensible Business Case for Space Change

Data becomes a business case when it quantifies the cost of the current situation and the return on the proposed change. FM managers need to frame space decisions in terms that finance and leadership teams can evaluate:

Current cost per workstation vs. actual utilisation rate
Wasted lease liability from consistently underutilised zones
Service delivery cost (cleaning, utilities, heating) relative to occupied vs. unoccupied areas — Intellis highlights that occupancy analytics directly inform cleaning schedules and energy consumption, enabling measurable cost reductions
Projected efficiency gain from reconfiguration (e.g., converting oversized boardrooms to smaller collaboration rooms)
Risk of inaction — the reputational and operational cost of a workspace that frustrates staff on peak days while burning energy on empty space the rest of the week

The IWFM Market Outlook 2025 reports that 42% of FM respondents increased workspace investment in 2025, with budgets higher than in 2024. Investment is flowing. The FM managers who will secure their share of it are the ones who arrive at the table with data, not opinions.

During mobilisation and transition phases in particular, space utilisation data is mission-critical. FM teams transitioning into a new contract or site should establish baseline occupancy data in the first 30–60 days before any service redesign or space consolidation begins. Without that baseline, every recommendation is a guess.

The 5 Mistakes FM Teams Make with Space Data

1. Measuring peak occupancy, not average occupancy.

Peak days look like the space is fully used. Average data tells a completely different story. Always report both.

2. Confusing booking data with actual utilisation.

A booked room is not an occupied room. Ghost bookings can inflate your apparent utilisation rate by 20–30%. Validate with sensor data.

3. Collecting data once and treating it as permanent.

Utilisation patterns change with headcount, hybrid policy updates, and seasonal rhythms. A data snapshot from 18 months ago is not a planning document.

4. Ignoring qualitative data.

Numbers tell you what is happening. Staff surveys, team observations, and service feedback tell you why. A space with low utilisation might need better signage, better booking UX, or simply better coffee nearby. Data without context leads to misdiagnosis.

5. Letting data gathering become a substitute for decision-making.

Some FM teams collect occupancy data for months and then wait for more data before acting. Define in advance what utilisation threshold triggers a decision — and honour it.

The FM Space Utilisation Framework: Save This Before Your Next Redesign

BEFORE YOU REDESIGN: THE 5-STEP DATA FOUNDATION

Step 1 — Baseline First

Establish occupancy data across all space types (desks, meeting rooms, collaboration areas, support spaces)
Collect for a minimum of 8 weeks across a full working pattern
Use at least 2 data types (sensor + booking or access card)

Step 2 — Segment the Data

Split by day of week (identify peak vs. trough days)
Split by space type (individual vs. collaborative vs. support)
Split by floor / zone / department where possible

Step 3 — Identify the Gaps

Which spaces are consistently under 40% utilised?
Which spaces are over 80% utilised on peak days?
Where does supply (space type) mismatch demand (user behaviour)?

Step 4 — Cost the Current State

Calculate cost per workstation vs. actual occupancy
Quantify utility and service costs for low-utilisation zones
Document the demand you cannot currently meet on peak days

Step 5 — Build the Case, Not Just the Plan

Define what success looks like post-redesign (target utilisation %)
Link space changes to measurable FM KPIs
Include a review point (6 months post-change) with new data collection

Take This Further

If you want to embed data-driven decision-making as a core FM competency — not just for space, but across every service line — these two programmes will build that foundation:

MCFM00203.2 Advanced Continuous Improvement and Adaptability — £895 Designed for FM professionals who need to move from reactive to evidence-led operations. Covers performance frameworks, data interpretation, and structured change management.

Mobilisation Mastery: From Chaos to Clarity — Free If you are in a contract transition or site mobilisation, this is where to start. Covers the structured approach to establishing operational baselines — including space data — from day one.