Workspace analytics software is often bought on the strength of a demo dashboard and judged six months later on whether anyone trusted the numbers. For desk-sharing offices, trust comes from three things: a clear definition of what counts as attendance, a reliable link between bookings and actual presence, and capacity figures that only include desks people can really use. This guide sets out the questions worth asking any vendor, shows how DeskHybrid answers them, and outlines a short pilot that tests the data before you commit.
Workspace analytics software is often bought on the strength of a demo dashboard and judged six months later on whether anyone trusted the numbers. For desk-sharing offices, trust comes from three things: a clear definition of what counts as attendance, a reliable link between bookings and actual presence, and capacity figures that only include desks people can really use. This guide sets out the questions worth asking any vendor, shows how DeskHybrid answers them, and outlines a short pilot that tests the data before you commit.
DeskHybrid is a desk-sharing specialist, and its analytics follow the booking-to-check-in lifecycle rather than building-wide sensors.
The unit of attendance is a **qualifying office day**. A day counts once per person, only when the person checked in and was checked out (including automatic check-out), and the total checked-in time reaches the minimum duration in the booking policy. Company owners and admins see this per person in a weekly or monthly office-day report, alongside a **No-Show Report** that counts bookings released because no valid check-in happened in time. Each report carries an information panel that states its counting rule, can be stepped through previous periods, and can be sorted highest or lowest first.
The dashboard adds **Active Desks**, which excludes deactivated desks, and **In Office Today**, the number of people holding a live booking for the day. Every person also sees their own office days for the week and month. Days, weeks, and months are calculated in the company's timezone.
Because the office-day count depends on check-in, the check-in experience decides data quality. Employees check in from the desk dialog on the booking map once the check-in window opens, and the mobile apps offer check-in straight after booking when the window is already open. Available on Web, Android, and iOS. Admins can require QR check-in so the person scans the code on the desk, optionally with a proximity check against the floor's location taken only at the moment of scanning.
There is no badge integration, no continuous location tracking, and no screen or activity monitoring. The data is what people create by booking and checking in, which keeps the analytics explainable to employees as well as to leadership.
The booking policy is part of the analytics model. The minimum duration to count a booked day sets how strict the office-day report is. The check-in window and auto-release delay determine when an unclaimed booking becomes a no-show. Maximum days in advance shapes how far ahead demand is visible. Record the date of each change so trend comparisons stay honest.
When a booking passes the auto-release delay without a check-in, DeskHybrid releases the desk, marks the booking as a no-show, and makes the desk bookable again. Recovery is where analytics produces a practical result: a desk that was blocked is back in the pool the same morning.
Keep two lists. Reported directly by DeskHybrid: active desks, people in office today, qualifying office days per person, and no-shows per person, each by week or month. Derived by your team: peak-day bookings against active desks, the share of bookings ending as no-shows, and the gap between booked days and qualifying days. Write down how each derived KPI is calculated so it means the same thing every month.
Recent official data shows why workspace analytics software needs to distinguish between scheduled attendance and verified usage. 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. Many employers are managing variable demand rather than a fixed in-office routine.
Building-capacity oversight points to the same problem. 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. When utilization is that uneven, reservation counts alone say little; the gap between reservation intent and confirmed presence is the figure worth tuning against.
A four-week pilot on one floor tells you more than any demo. In week one, set up the floor, deactivate desks that are not available, print the floor's desk QR codes in one batch, and agree the minimum duration that should count as an office day. In week two, let people book and check in normally and watch check-in adoption. In weeks three and four, read the office-day and No-Show reports with the floor manager and compare them with what the manager saw on the ground. If the numbers and the manager's experience disagree, adjust the check-in setup before scaling.
Analytics degrade quietly when the people list drifts. Where Microsoft Entra ID single sign-on is configured, accounts are created on first sign-in and display names come from the workspace rather than being self-edited, so report rows match the directory. New users default to the company's timezone. Review the active-desk list whenever a floor changes, and treat any policy change as a break in the trend line.
DeskHybrid reports qualifying office days and no-shows per person by week or month, counts capacity against active desks only, and documents each counting rule inside the report.
Start with booking quality, check-in adoption, no-show counts, and the gap between booked days and qualifying office days.
A weekly operational check and monthly policy review is a practical baseline for sustained performance.