To gain a comprehensive understanding of your workplace, it's crucial to analyze not just workspace trends but also meeting room occupancy. This report delves into meeting room usage, providing insights into room occupancy rates. Like desk occupancy, meeting room sensors detect occupancy and, depending on the sensor type, can provide additional information such as people count.
🚨 Please note that desk occupancy is only available for desks with associated sensors. If your subscription doesn't include a sensor integration, you won't be able to access this page. Please get in touch with your Customer Success Manager for more information.
Available Filters
You can apply various filters to tailor the report to your needs:
Filter | Selection Type | Description |
Building | Multi-select | Filter by specific or multiple buildings for more focused insights. |
Floor | Multi-select | Filter Data by floor level. If a building is selected, the filter will apply to that floor. |
Meeting Room | Multi-select | Filter by specific meeting rooms within your buildings. |
Size | Multi-select | Select the meeting room sizes you want the data to include |
Period | Single-select | Determine the period for data evaluation, ranging from the beginning of the year to as far back as 2021. |
Date customisation | Multi-select | With this filter, you can filter out specific days from your data. For example I want to see the data of 2024 excluding Christmas. |
Week length | Single-select | Choose to let the data include a five or seven day workweek. |
Weekday | Multi-select | Only show data on the selected day(s). For example if you only want to see data for Mondays and Fridays. |
Key Numbers
These key numbers offer a quick overview of your meeting rooms' occupancy levels:
Key Number | Description |
Meeting rooms with sensors installed | The total number of installed sensors sending data to Mapiq. |
Number of Meeting rooms used less than 10% of the time | The count of meeting rooms utilized less than 10% of the time within your selected filter settings (hours, week length, and period). |
The percentage of time occupancy is higher than 75% | The rate of time occupancy exceeded 75% within your selected filter settings. |
The lowest percentage of meeting room occupancy | The lowest occupancy level within your specified time range. |
The average percentage of meeting room occupancy | The average occupancy percentage is calculated by dividing the sum of the average per hour total occupied rooms by the total number of sensors, then by the total hours in the selected time range. |
Peak percentage of meeting room occupancy | The highest occupancy level within your selected time range. |
Reports
Where is it busy?
How popular are your rooms and how effectively are they occupied?
The Occupancy per Location graph shows the average percentage of time a meeting room is occupied compared to the total time available. The occupancy data is calculated by averaging the occupancy for a room per hour, then averaging it over the hours of the workday and the set period (depending on the Week Length filter, Saturdays and Sundays may be included or excluded).
Use the compare buttons to analyze data at different levels (building, floor, area, or meeting room). The graph is always sorted by average in descending order. When selecting the Floor view, the chart displays the average occupancy of all meeting rooms on all floors based on your selected filters. You can also view Building and Meeting Room levels.
💡If you've selected the Meeting Room view in the graph, it displays all meeting rooms across all buildings. Using filters can help you visualize the graph more effectively. The blue bar shows the average percentage of meeting room occupancy, and you can hover over the red line to view the maximum occupancy percentage.
What type of rooms are busy?
How popular are your meeting rooms and how effectively are they occupied?
This graph visualizes occupancy per room capacity. For instance, if you have multiple rooms with a total of six seats, you'll see the average occupancy of all these rooms in the bar labeled "6."
Note: it's challenging to determine which rooms fall into which capacity bucket, as the report only shows the capacity set in your meeting room configuration. Using active filters (building or meeting room) will limit the number of meeting rooms used in the graph, helping you identify the most and least popular room sizes. If people count sensors are available, you can also compare the intended size with the actual size.
When is it busy?
What are your peak days in the selected period?
Considering selected filters, the Occupancy Over Time graph displays the percentage of meeting room occupancy on specific dates. This graph also shows the current week and historical weeks (based on the Period filter) when the meeting rooms were occupied. The Week Length filter determines the week length.
A trend line indicates occupancy based on the selected time frame, helping you determine if it's getting busier or less busy at a glance. The trend line is responsive to active filters.
Occupancy per Day of the Week
You can also view the average occupancy percentage for meeting rooms per day of the week, offering insights into weekly usage patterns. The red line indicates the maximum occupancy of the meeting rooms, and the days shown depend on the Week Length filter.
Occupancy Over the Course of the Day
The final graph in this section displays meeting room occupancy throughout the day. For example, if a meeting room was occupied between 1:00 PM - 2:00 PM on a given day but empty the rest of the time, the graph will show a maximum of 100% based on the occupancy between 1:00 PM and 2:00 PM at 1:00 PM. The rest of the day will show as 0% occupied. If filters include multiple meeting rooms, the occupancy over the day will be shown as the average of all selected meeting rooms.
How effectively are room bookings being used?
Effective usage of room bookings per location
Using this report, you can quickly check the effectiveness of your meeting room usage. We break down the data into three key components: the time the room is efficiently booked and used, the percentage of time it remains unused (no-shows), and the ad-hoc usage pattern with booked meetings. These insights are derived from both meeting room booking data and occupancy data collected from sensors, with the selected "Hours" filter influencing the displayed results.
Effective usage per day of the week & Effective usage over the course of the day
The same data is also analyzed for the week and at different times of the day, providing organizations with valuable insights into how meeting rooms are utilized throughout the week and daily schedules.
Each of these graphs includes three primary categories or legends:
Effective Booking: This shows how often the meeting room is both booked and actually used.
Ad Hoc Usage: Here, we see how much the room is used on the fly, even if it wasn't formally booked.
No shows: This part covers instances where the room was booked but left empty because someone didn't show up.
Note: These reports currently do not include actual no-shows, as we don't directly match meeting room bookings with attendance. Instead, we focus on the percentage of time meeting rooms were booked during the day and actively utilized. Consequently, Mapiq refers to "unused bookings" rather than labeling them as no-shows.
How often do room bookings turn into a no show?
Time lost on no-shows & Impact of recurring meetings on no-show
The first graph show the time lost on no-shows. Of all bookings how many turn into a no show, how many are being released and how many meeting room bookings are utilized normally.
The second graph shows what the probabilities are that a meeting turns in to a no show. There are two columns, one for one time meetings and the second column for recurring events.
Impact on no shows due the meetings booked in advance
This graph shows the average amount of bookings that have turned into a no show per days booked in advance. Often the further a booking is made in the future, the more likely that they are to become a no show. This graph shows the relation between the effectiveness of the booking and the number of days the booking is made in advance.
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