Space management insights #5: Occupancy data only matters if it benefits employees

Shivaun Ryan, Head of Customer Success, XY Sense

Editor’s Note: This article is part of an exclusive series featuring insights from our ebook, The smarter office: Your guide to space management in the hybrid era. Read the full guide for more insights on actionable space intelligence, making the office a destination, AI’s role in space management, and more.

There’s been a lot of hype, and budget, poured into free food and social activities to lure people back to the office. But a pizza lunch and a game of ping pong isn’t going to fix the friction people feel at work.

If I can’t find a desk, can’t concentrate, or can’t easily work with my team, no amount of perks is going to make that experience worthwhile.

Most people don’t hate the idea of coming into the office. They just want to be able to do their job properly while they’re there.

That’s why occupancy data matters. Used well, it helps teams understand where friction is really happening and fix it in ways employees can feel. But used poorly, it becomes another leadership dashboard that never changes the workday.

That’s the real test of workplace data: does it make the office easier for employees to use? If the answer is no, the data is probably too far away from the people it’s supposed to help.

Friction looks different in every workplace

What makes the office worth the commute varies more than you might expect. “Friction” can differ significantly according to company culture and geography.

In some organizations, the biggest barrier is not being able to find a quiet focus room. In others, it’s not knowing where your team is sitting. In large campuses, it might be difficulty finding the right neighborhood, knowing where space is actually available, or understanding where teams are gathering. 

That’s where space teams can get into trouble. If you apply the same standard everywhere, you miss the reality of how each location’s employees actually work. What creates friction in one region may be a non-issue in another. Your execution needs to reflect that.

Good data should move teams closer to the lived employee experience, not further into abstract reporting.

Human perception is shaped by personal experience, not patterns. That is why anecdotal complaints need to be tested against reliable occupancy data before teams decide what to change. A team may feel like there are never enough meeting rooms, but the real issue might be no-shows, room size mismatch, or spaces that are available but not trusted. 

Phantom availability is the crux of friction

One of the most frequent versions of this problem is phantom availability. These are meeting rooms that show as booked but sit empty for hours. Or conference rooms occupied by a single person eating lunch. Or open desks that employees walk past because they have no idea whether they’re actually free. People come in, and they can’t find space.

The issue gets worse when the data only tells part of the story. For example, if meeting rooms are fully booked but you can’t see that 30% of them are no-shows and should be released, you’re falling into a dangerous data gap. Employees feel that gap immediately.

They commute in, check the booking system, walk across the floor, and find out the available space isn’t actually available. Or they assume everything is taken, even though half the rooms are empty. Either way, they stop trusting the system.

Once that trust breaks, people work around it. And when people work around the system, the data gets worse.

This is where occupancy data has to prove its value. It should close the gap between what employees see in a system and what’s actually happening in the space.

Start with the problem you’re trying to solve

The solution isn’t always technology. 

Take a step back. What are the use cases? What’s your company culture? What are you looking to do?

Anonymous occupancy data gives you a baseline. But before executing any new data collection initiative, you need to get specific about what you’re trying to solve. If you start with a clear, defined problem, you’re likely to get more ROI than a team that gathers everything but has no idea what to do with it.

That problem might be no-show meetings. It might be a lack of quiet space. It might be a campus layout that makes people lose time between buildings. It might be a mismatch between what leadership thinks employees need and what the floor is showing every day. The data should help answer a real question.

And the best questions usually come from friction employees already feel.

Show the data live to build trust fast

Leadership trust matters too. When leaders can see occupancy data reflecting real activity in real time, it clicks right away. That’s the moment it moves from concept to credibility.

Before any budget conversation, think back over the last month. List every challenge you faced that better data would have helped you resolve. That list of real problems makes for a compelling pitch. It connects the investment to specific issues your leadership has already witnessed firsthand.

The stronger case is not “we need more data.” It’s “here are the decisions we could have made better if we had the right data at the right time.”

Space design should be behavior-based

Once you understand how employees actually use space, you can design it to support what they really come in for.

For example, our data has found that 82% of meetings involve just one to three people, while 39% have only one person. That kind of insight can change the mix of spaces teams build, shifting investment toward phone booths, smaller collaboration rooms, and tech-enabled spaces that match actual behavior. 

For organizations operating across multiple regions, that means avoiding a single design standard. Space usage behaviors vary significantly by culture and geography. A global framework can help, but the execution needs to be regional.

This is also where occupancy data can help identify demand for spaces that may not be obvious in a traditional floor plan review. Organizations are increasingly using occupancy data to identify the demand for low-stimulation spaces. These might be quieter rooms with better soundproofing and lower light levels, well suited for neurodivergent employees. 

These rooms often become among the most well-used areas in the building. It’s not only for employees who identify as neurodivergent. It’s for anyone who wants a quiet area after a stimulating morning.

Your decisions should account for everyone who’s using the space, rather than only the most visible working group.

Sometimes the right fix is surprisingly practical. In one example, desks with dual monitors were twice as popular as other setups. Employees had grown used to more functional home offices, so returning to a single screen felt like a step backward. The answer was not a major redesign. It was investing in the workstation quality people actually valued. 

That same logic applies to employees. They don’t need to hear that the organization has better analytics. They need to see that the office works better because of it.

The experience starts before employees arrive

The most mature organizations are extending their thinking beyond the building itself. In reality, the in-office experience starts the minute employees are leaving home.

The decision to commute depends on confidence. Employees need to know whether their team will be there, whether the right space is available, and whether the office will support the work they came in to do. Friction starts before an employee reaches reception. 

If employees don’t know whether their team is in, whether the right space is free, or whether they’ll spend the first 20 minutes searching for a room, the office has already become a harder choice.

The workplace experience needs to account for that full decision process, from leaving home to finding the right place to work once they arrive.

That’s what makes the data useful. It helps space teams see the needs that don’t always show up in the loudest feedback channels.

Occupancy data becomes more valuable when it helps employees make that decision with confidence.

Data becomes more valuable when employees can use it

Occupancy data tends to be positioned as a tool for leadership: space utilization reports, real estate decisions, cost analysis.

All of that is valuable.

But the organizations getting the most out of their data are the ones surfacing it directly to employees.

It’s not about tracking people. It’s about how this data helps me, as a colleague, in a workplace.

When you turn data into a utility, it goes from living in dashboards to solving daily friction.

Imagine a team wants to move their conversation into a meeting space down the hall. If booking data only updates every few minutes, the room might show as empty, but it actually became occupied by another one-to-one two minutes ago.

Because the team doesn’t have up-to-date visibility, they waste the time walking there and back.

That certainty is what makes the difference between an employee who finds a space in under a minute and one who gives up and takes a call from the corridor.

This is the point where workplace data starts to earn trust. It gives people time back, removes guesswork, and makes the office feel more reliable.

Make the purpose of data visible

Employees can be skeptical about occupancy data.

The best way to address it is through demonstration.

When employees start seeing the output – new spaces that match their actual needs, meetings proactively rescheduled when rooms go unused – the purpose of the data becomes self-evident.

You know all those extra phone booths that went in on level 12? That’s because the data said you had so many single-occupant meetings.

That is the kind of explanation employees can understand.

When you roll out any new data collection capability, plan its employee-facing application at the same time. Show employees what data is being collected, how it’s anonymized, and what changed because of it.

The privacy foundation matters. The data should be private by design: no images, no video, no personally identifiable information, and no individual tracking. The value comes from population-level patterns over time, not from knowing what one person did at one desk. 

Occupancy data earns trust when it gives something back.

The more visible that value becomes, the less the data feels like surveillance and the more it feels like support.

The workplace should respond before friction shows up

The next step is moving from reactive to proactive to predictive.

Rather than running heating, cooling, and air quality management on a fixed schedule, you can connect occupancy data directly to building infrastructure.

If we can pick up that 10 people are about to be in a room before the CO2 goes high, then you’re actually being predictive before it gets to that threshold.

For instance, a room booked for 10 people at 2 p.m. can trigger pre-emptive airflow adjustments, so the group walks into a comfortable space at meeting time.

That’s where the value of occupancy data becomes very practical.

It helps leadership make better real estate decisions. It helps facilities teams see what’s really happening. And, most importantly, it helps employees have a better day at work.

Because the real test of workplace data is whether it helps people find space, feel comfortable, and do the work they came in to do.

Get more expert insights in our ebook, The smarter office: Your guide to space management in the hybrid era.