Insights are a powerful tool to use in order to make informed decisions for your office. Here is a guide to help you navigate through the data gathered.

Please note that whenever you change the filters you must select "Update" for the report to refresh.

Trend graphs will present differently based on if you’ve chosen to filter by a whole year (the graph will show all 12 months at an appropriate level) vs if you've filtered by a week (whereby it may spread the data out and show you each individual day).

Most chart types can be hovered over to see extra information on the data.

On charts where there are multiple layers of data labeled, for example, "floors", you can click on each label to turn it on or off, showing only the data you are interested in for that occasion.

Desk and Utilisation overview

Desk Cancellation overview

Check in overview

Released Spaces overview

Utilisation takes into account the time your desk is available for, and what percentage of that time it has been booked for. For example, if a desk is available 8 hours in a day, and has been booked for 4, it is 50% utilised.

Comparison to previous period

This metric provides insight into the percentage in which the utilisation has grown or declined. For example, if it was 10% last month and its 15% this month, it has grown by 50% vs previous period (not 5%)

The total amount of bookings which have been made during your selected period.

On average, in a day, how many desk bookings are made?

This metric provides you with an average number of desks which are bookable.

What is the highest usage of desks registered? In this example, at its peak, 16% of the total desks available were used.

This metric tells you what percentage of your overall desk availability has been used in ANY capacity, not taking "time booked" into account. For example, if you have 10 desks, and 3 have been booked all day, and 2 have been booked half days, that is still 50% overall desk usage.

This chart lists all your employees, the number of bookings they have made during the selected period as well as the number of desk bookings that have been cancelled. Using those two statistics, the reports give you a cancellation rate percentage (%).

This chart is similar to the Employee Booking Stats chart but provides you with stats by groups ( and not employees).

This graph provides you with information about the busiest days of the week. In this example we can see Wednesday is the busiest day.

This graph displays the busiest days for your desks. In this example, Wednesday is the busiest day followed by Tuesday.

This graph helps you understand when are your users booking desks.

This graph displays the top 10 of your most popular desks (most bookings).

In this graph, each one of your floors has been attributed a colour. The most utilised floors will have the highest peaks.

Just like the previous graph, you will see the most utilised zones (highest peaks).

The cancellation rate takes into account the total amount of bookings made which have been cancelled.

This number gives you the number of bookings that have been cancelled.

This number gives you an average of the number of cancellations per day.

How many of the bookings which get cancelled go on to be re-utilised by the business? How much of an impact are cancellations therefore having on your utilisation, and is it a key problem to solve for you? For example, if this % is low, it means that people are cancelling with enough time, or that your spaces are in demand enough for them to go on to be utilised anyway.

In this graph, you can easily see when the bookings are cancelled.

What is the reason behind the cancellation of the booking? In this example, we can see that all the bookings that have been cancelled have been cancelled by the user.

In this graph, you can see the cancellation rate trend. Are there periods when more cancellations happen?

Are some desks more often cancelled than others? This graph will help you answer this question.

This percentage represents the average count of desk bookings that have been checked in.

This number represents the total count of desk bookings that have been checked in.

On average how many desks are being checked in per day? This metric answers this question.

The percentage was calculated by taking the total count of bookings that have been checked in divided by the total count of desk bookings.

This graph shows you how users checked into their desks. In this case, we can see most of them checked using the web app.

When did users check into their desks? This graph shows you whether users have checked in before or after the booking start time.

This graph enables a simple visualisation of the checked-in rate compared to the total count of bookings.

This graph shows you simply whether users are checking into their desks or not.

Count of desk bookings that have been released (the user didn't need the booking anymore and removed it).

How many hours have been freed thanks to the early release.

This metric provides you with the average count of released bookings per day. In this example, there are on average 4 bookings released per day.

This percentage gives you an indication of the reusability of the freed time. In this case, none of the bookings that have been released have been re-used.

This percentage of bookings released took into account all the bookings and the ones which have been released. In this case, the percentage is low which means very few bookings have been released.

This graph compares the average released hours with the released space count. In this example, Wednesday had 84 released spaces which freed on average 8 hours.

This graph provides you with a quick view of the spaces' released trends. You can observe if some periods have more bookings released.

This large table of data provides all the key areas you might want to know on a per booking basis. This provides the option for you to download this data into CSV format by hovering over the tile, using the three dots and selecting "download data".