Is Anyone Actually in the Office? A Modern Guide to Occupancy Tracking

You signed the lease, laid out the floor plan, and stocked the kitchen. You invested in the office, and now you genuinely can't say whether anyone is using it.

That gap is what office occupancy tracking is meant to close: turning a vague sense of "it felt quiet this week" into data you can plan around. And it matters, because most teams don't actually know. 62% of decision-makers admit they don't actually know how their space is being used (Facilities Management Advisor).

That's because modern work has changed how people use the office. When everyone came in five days a week, occupancy was a given. Now presence is unpredictable, and the same office can be packed on Tuesday and empty on Friday. Measuring it has become one of the hardest questions workplace, facilities, and HR teams are trying to answer.

This guide breaks down the five methods teams actually use to track occupancy in 2026, the honest trade-offs of each, and how to pick the right combination for your goals.

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Why “Is Anyone in the Office?” Became a Hard Question

The crowding problem and the empty-office problem usually happen in the same building and in the same week.

Teams cluster around midweek. On peak days, desks run short, meeting rooms are booked solid, and the parking lot fills by 9 a.m. Global office utilization on those days sits near 80% (CBRE). Then Monday and Friday arrive, weekly utilization drops to roughly 56%, and the floor goes quiet (JLL).

Each side creates its own kind of waste. On the busy days, you get more people than desks, rooms that show as “booked” but sit empty, and ghost bookings that make you think you need more space than you do. More than 25% of all booked meetings are ghosted in some way, which quietly inflates every capacity decision you make based on that data (Density).

On the quiet days, the waste is financial. You're running HVAC for empty floors, cleaning spaces no one touched, and paying for square footage that goes unused. Employees who did come in find their teammates aren't there, so the commute is wasted on a video call they could have taken from home.

You can't fix either problem until you can see it. And seeing it clearly is where most teams get stuck, because a booking calendar tells you what people intended to do, not what they actually did. Reading real office attendance patterns takes a deliberate measurement method, and often more than one.

Start With the Goal, Not the Gadget

Before you compare sensors and Wi-Fi and badge readers, answer a simpler question: “What are you actually trying to accomplish?” The best method for one goal is may not be the best method for another.

Four goals tend to drive occupancy projects:

• Better workplace experience. If your aim is to make in-office days worth the trip, you care about collaboration, not surveillance. 68% of employees name collaboration as the number one reason to come in, so you want data that helps you cluster teams and protect the days they overlap (CBRE).
• Hybrid-policy compliance. Mandates are easy to write and hard to enforce. Policy requirements have risen about 10% since early 2024, but actual attendance has lagged, climbing less than 2% (WFH Research). If you're measuring against a policy, you need presence data you can trust.
• Space optimization and cost control. Real estate is the second-largest line item after payroll for most organizations, and it isn't getting cheaper (Realcomm). Asking rents are up 2.2% year over year, the fastest pace in six years (CBRE). When every square foot has to earn its keep, you need utilization data granular enough to defend a downsizing or a redesign.
• Killing ghost bookings. If your rooms look full but feel empty, your problem isn't capacity. It's confidence in the data. You need a way to confirm that a booking became a body in a seat.

Match the method to the goal and the rest of the decision gets much easier.

The 5 Ways Teams Track Office Occupancy in 2026

There are five methods in wide use. Here's what each one is good at, and what to watch out for.

Badge swipes and access control

Badge systems are already everywhere. They're deployed by roughly 90% of large enterprises, making them the easiest data source to tap because the infrastructure already exists and someone's already paying for it (JLL). For building-level signals (e.i. did this person enter today?), they work well.

The catch is that a badge tells you someone crossed the threshold, not what they did afterward. Once people are inside, their movement disappears. Around 20% of people aren't captured accurately at all, thanks to tailgating and missed swipes (Occuspace / Nexus Labs). You hold the door for a colleague, three people walk in behind them, and none of them register. Then there's coffee badging, where employees swipe in, grab a coffee, and leave. Nearly 60% of employees admit to it (Owl Labs). The swipe says “present,” but reality says otherwise.

Wi-Fi–based presence

Wi-Fi presence is accurate enough for many teams, landing around 80–85% accuracy, and higher when it's tied to a booking system that connects a device to a named person (PointGrab). Its biggest advantage is that it runs on infrastructure you already own. Every office has Wi-Fi, so the implementation lift and cost are well below those of dedicated sensors, which is why it's gaining ground fast.

The trade-off is precision. Wi-Fi gives you an approximate read on where people are, and because it tracks devices rather than people, one person carrying a laptop, a phone, and a tablet can register as three. It can also mistake a networked printer for a person. Tie it to a booking login and most of that noise clears up, but on its own it's a rough count, not a clean one.

Desk and room booking software

Between 49% and 68% of organizations already use booking software, according to JLL, and it's the method that captures something the others can't: intent. A booking is a deliberate action, so you learn what people planned to do and where they wanted to be.

Paired with check-in and auto-release, it also captures reality. If someone books a room and doesn't check in, the booking releases and the space frees up for someone else, and you learn the booking never became actual use. Because booking is opt-in and involves no cameras or location tracking, it reads as privacy-safe to employees, which matters for adoption.

The honest limits: booking data doesn't capture ad-hoc walk-ins well, and it only works if people actually use the system. That means employee buy-in and custom booking rules clear enough to keep one team from reserving the same room every day for the next five years. Get those right and booking becomes the most practical foundation for occupancy data most teams have.

IoT and dedicated sensors

If raw accuracy is the goal, sensors win. Depending on the type, they hit 95% to nearly 100% accuracy, high enough to trust for redesigns and downsizing decisions (Perra et al., 2021; Milesight).

Two things hold teams back. The first is cost: hardware starts around $149 per unit, and software adds roughly $2.50 to $8 per unit per month (Density.io; Tango Analytics). That adds up fast across a portfolio, which is why 37.5% of organizations cite cost as the barrier to expanding (Tango Analytics). The second is that sensors are anonymous by design. They'll tell you a room held four people and which zones run hottest, but they won't tell you who those people were or which teams are choosing which neighborhoods. If your goal is understanding behavior, not just headcount, sensors need a partner.

Geolocation and GPS

GPS is the outlier, and for most office scenarios it's the wrong tool. Its strength is that it works without any on-site infrastructure, which makes it genuinely useful for field service and distributed workforces where confirming an approximate location is the whole point.

Inside an office, it struggles. GPS reads as surveillance, and employees consistently push back on it. The regulatory picture is murky, too. In the United States, there's no federal ban, but states set their own rules. Globally, you're subject to GDPR. Like Wi-Fi on its own, GPS measures proximity, not space use, so it tells you someone is near the building without telling you what they did inside it.

How the Five Methods Compare

No method scores well on every axis. Here's the honest side-by-side.

*When paired with sensor confirmation or auto-release.

The pattern is hard to miss. The most accurate method (sensors) can't tell you who's there. The method that best captures intent (booking) needs check-in to confirm reality. The signals that already exist for most (badge, Wi-Fi) are the roughest. This is why the real question isn't “which method?” but “which combination?”

See your real utilization, not just your bookings. Skedda's Workplace Intelligence turns booking and check-in data into occupancy insights you can filter by team, space, and day, so you can act on what's actually happening on your floor.

The Occupancy Tracking Maturity Path

You don't need every method on day one. You need the right next step for where you are. Here's the progression we'd recommend.

If you're just starting (running on observation and spreadsheets), add a booking system with Wi-Fi check-in. This is the highest-leverage move available to you. It gives people a way to self-serve a desk or room, and it lets you confirm they actually showed up. That combination closes most of the ghost-booking gap that makes early occupancy data useless.

If you already have booking and check-in, maybe with some badge data alongside it, this is the point to add sensors. Start with your high-stakes zones (meeting rooms and popular neighborhoods) before going portfolio-wide, because the cost is real. Layering sensor accuracy on top of booking's intent and check-in's reality gives you the full picture: how many people, who they are, and which parts of the office they gravitate toward.

If you have sensors, booking, and AI-assisted analysis, congratulations, you have a lot of trustworthy data. Now use it to make decisions: rework a neighborhood, right-size a floor, staff up for peak days without over-provisioning for the quiet ones. When the call is backed by historical data instead of a hunch, you can defend it to finance.

Notice that every stage after the first uses more than one method. That's deliberate. Almost no one is single-source anymore, because each method's blind spot is another method's strength. 68% of firms have already layered two or more methods together (Tango Analytics). Pairing them is how you cover for what any one of them misses.

Booking and Check-In: Your Occupancy Backbone

Most teams don't need to start with the most accurate method. They need to start with the most practical one, and then build up. That's the case for making booking plus check-in your foundation, and it's what Skedda is built to do.

It starts with a booking. People reserve a desk or a meeting room from an interactive office floor plan, on their phone, or through a desk booking system that's genuinely easy to use. That first action captures intent. Then the insights dashboard turns those bookings into utilization data you can read at a glance: overall utilization, total bookings, and active users for any period, with the change versus the period before. You can filter down to just desks, just meeting rooms, or a specific team, and export the whole view as a report.

Bookings alone still carry the ghost-booking risk, though. Someone reserves a room for next Tuesday, never shows, and the data still counts it as used. That's what check-in fixes. You can set a rule that emails people before their booking starts and gives them a window to confirm, either from the email or from their booking calendar of choice. Miss the window, and the booking releases. Now the data reflects reality, not just plans.

The friction with check-in is that people forget to do it. Skedda closes that gap two ways. Add your office's public IP addresses, and anyone who's physically on-site is detected and checked in automatically the moment they connect. Push out the Companion App through your Google or Microsoft admin (no download, one sign-in), and it runs quietly in the background, checking people in when they show up with their laptop. In your booking list, every person seen on-site shows a green check. You get confirmed presence without asking anyone to do anything on the day.

Rooms can work differently from desks. You might auto-check-in a desk booking the moment someone arrives, but require an active check-in for a 1 p.m. meeting so a no-show frees the room. A tablet outside the room handles that: walk up, tap check-in, and you're confirmed on the spot. Walk-ins are covered too, with QR codes on any space that let someone book in seconds from their phone. And because Skedda offers two-way calendar sync with Google and Outlook, a booking made in either place stays consistent across both.

The result is occupancy data you can trust, layered from intent to reality without buying a single sensor. And unlike an anonymous sensor count, it tells you who: which teams are coming in, which spaces they choose, and where your real demand sits.

Measure What Matters, Then Act

The honest answer to “is anyone actually in the office?” is that you can't know until you measure it, and no single method measures it perfectly. Badge swipes miss the tailgaters. Sensors don't know names. GPS reads as surveillance. Booking needs check-in to tell intent from reality.

So start where the leverage is highest. Give people an easy way to book, confirm attendance with automatic check-in, and you'll have trustworthy occupancy data in weeks—not a six-figure sensor rollout. Layer in more methods as your questions get sharper. The goal isn't perfect measurement for its own sake. It's making better decisions about the space you're already paying for, and using space management software that turns those decisions into everyday operations.

Want to see booking and check-in working together on your floor plan? Book a demo with our workplace team.

Frequently Asked Questions

What is office occupancy tracking?

Office occupancy tracking is the practice of measuring how many people are actually using a workspace, and often which spaces they're using and when. It ranges from simple entry counts to detailed, room-level data. The goal is to replace assumptions about how the office is used with evidence you can plan and budget against.

What's the difference between occupancy and utilization?

Occupancy is how many people are present. Utilization is how much of your available space that presence actually uses, measured against capacity over time. A room can be occupied by one person and still be badly underutilized. We cover the distinction in more depth in utilization vs. occupancy, and it matters because the two answer different questions.

What's the most accurate way to track office occupancy?

Dedicated IoT sensors are the most accurate single method, reaching 95% to nearly 100% accuracy depending on the type (Butlr). But accuracy isn't the whole story: sensors are costly and can't identify who's present. For most teams, booking software with automatic check-in delivers highly reliable data at a fraction of the cost, and it tells you who and why, not just how many.

Is occupancy tracking a privacy risk?

It depends on the method. GPS and always-on location tracking read as surveillance and draw consistent employee pushback, and they carry real regulatory weight under GDPR and various state laws. Booking-based tracking sits at the other end: it's opt-in, uses no cameras or location trails, and only records the spaces people choose to reserve, which is why it tends to earn employee trust.

What are ghost bookings, and how do I reduce them?

Ghost bookings are reservations that never turn into actual use—the room shows as booked, but no one shows up. More than 25% of meetings are ghosted in some way, which inflates demand and makes you think you need more space than you do (Density). The fix is check-in with auto-release: if no one confirms, the booking frees up and the data stops counting a no-show as usage.

Do I need sensors to track occupancy?

No. Sensors are the most accurate option, but they're also the most expensive and can't tell you who's in a space. Many teams get trustworthy occupancy data from desk and room booking paired with automatic check-in, then add sensors later in high-stakes zones once the fundamentals are in place. Start with the practical method, not the priciest one.