A booking tells you what someone intended to do. Office utilization analytics only becomes useful when it separates that intention from what actually happened at the desk. DeskHybrid builds its utilization numbers on that separation: reservations show demand, check-ins confirm presence, and unclaimed bookings are released and counted as no-shows. This page explains what each number in DeskHybrid measures, which policy settings change those numbers, and how operations, HR, and IT teams can run a short weekly review without building a separate reporting stack.
A booking tells you what someone intended to do. Office utilization analytics only becomes useful when it separates that intention from what actually happened at the desk. DeskHybrid builds its utilization numbers on that separation: reservations show demand, check-ins confirm presence, and unclaimed bookings are released and counted as no-shows. This page explains what each number in DeskHybrid measures, which policy settings change those numbers, and how operations, HR, and IT teams can run a short weekly review without building a separate reporting stack.
The dashboard shows four figures. **Active Desks** is the count of desks that can currently be booked; deactivated desks are excluded, so a floor that is partly closed for refurbishment does not inflate your capacity. **In Office Today** is the number of people holding a live booking for today; cancelled bookings and released no-shows drop out. **My Office Days (Week)** and **My Office Days (Month)** show each person their own qualifying office days.
Company owners and admins also get a Reports area with two reports:
Both reports step back and forward one period at a time, sort highest or lowest first, and include a panel stating the counting rule in plain language. Weeks and months are calculated in the company's timezone.
Every qualifying office day depends on a check-in, which makes the check-in flow the most important input to your analytics.
Employees can check in from the desk dialog on the booking floor plan once the check-in window opens, and the Android and iOS apps offer check-in immediately after a booking is made if the window is already open. Available on Web, Android, and iOS. Admins who want a stronger confirmation can require QR check-in, so the person scans the code on the desk itself, and can optionally add a proximity check that compares the phone's position with the floor's location at the moment of scanning. Location is read only for that check-in, which keeps the control proportionate.
Low check-in adoption makes the office-day report under-count real attendance, so fix adoption first.
These booking-policy settings feed directly into the figures, so change them deliberately.
Double-booking is blocked at the database level, even when two people book the same desk at the same moment, so one desk never counts twice.
No-show automation is where analytics turns into recovered capacity. When a booking passes the auto-release delay without a check-in, DeskHybrid releases the desk and marks the booking as a no-show. The desk becomes bookable again, and the event appears in the No-Show Report.
Read the No-Show Report as a pattern detector, not a scoreboard. A sudden rise across many people usually points to a policy problem, such as a release delay that is too short for the commute, rather than to individual behavior.
A thirty-minute weekly review is enough:
Separate the figures DeskHybrid reports directly from the ones you derive.
Reported directly: active desks, people in office today, qualifying office days per person per week or month, and no-shows per person per week or month.
Derived by your team: peak-day demand against active desks, the share of bookings that end as no-shows, and the gap between booked days and qualifying office days. Keep the derivation method written down so the KPI means the same thing every month.
Official labor and workplace-use data supports treating office utilization analytics as an operating discipline rather than a cosmetic reporting layer. The U.S. Bureau of Labor Statistics reported that on an average day in 2024, 34 percent of employed people did some or all of their work at home.
Federal workplace oversight data points in the same direction. The U.S. Government Accountability Office reported in 2024 that 17 of 24 selected federal agencies used 25 percent or less of headquarters building capacity. Low and uneven occupancy is exactly why utilization analytics should rest on confirmed presence and released bookings, not reservation counts alone.
Utilization analytics is only as good as the first month of data. Start by deactivating desks that are not genuinely available, because the active-desk count is your denominator. Next, decide whether check-in will be optional, QR-required, or QR-required with a proximity check, and print the QR codes for each floor in one batch before launch day.
Then agree the minimum duration that should count as an office day. Left at zero, a ten-minute visit counts the same as a full day; set at a full working day, it under-counts people who leave early. Most teams settle in between and write the reason down.
Finally, give owners clear roles. Workplace operations reads the No-Show Report weekly, HR looks at office-day patterns monthly, and IT owns sign-in and device rollout. Where Microsoft Entra ID single sign-on is configured, accounts are created on first sign-in, which keeps the people list, and therefore the reports, aligned with the directory.
DeskHybrid counts an office day only when a person checked in and stayed for the policy minimum, records released bookings as no-shows, and measures capacity against active desks only.
Start with the weekly office-day report, the No-Show Report, and peak-day bookings against active desks, then derive the gap between booked days and qualifying office days.
A weekly operational check and monthly policy review is a practical baseline for sustained performance.