Skedda's Insights feature is a rich, compelling and fast analytics and reporting solution designed to empower the decision-makers at your organization. This feature is part of our Pro plan and above.
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Insights at a glance
Here's how the Insights dashboard looks at a high level. It includes filtering and reporting controls, key performance indicators, charts and tables:
The Insights dashboard includes a number of filtering controls to help you discover knowledge from your data. We discuss each of these below.
The date range filter controls the time period on which the displayed information is based. There are a number of preset ranges ("Last week", "Last month", "Last 3 months", ...) as well as a "Custom range" option (note that custom ranges are limited to spanning up to 3 months at this time).
Note on the comparison with the "previous period": For a chosen date range, the percentage values used for the trend indicators (i.e. the little green and red arrows) are computed by comparing the main date range with its equivalent previous period. For example, if you choose "Last week" as the main date range, then the week before it used as the comparison. For custom date ranges, the previous period is the equivalent count of days directly preceding it (e.g. if your custom main range is 8–10 November, than the previous period used for comparison is 5–7 November).
Here you can filter by one of the views, locations or areas that you have set up across your spaces. Perhaps you want to ignore your desks and focus on just your rooms, for example. If you don't have any such views set up and you have permission, you can conveniently create one directly from the Insights page if (just note that the view is then available account-wide as if it were created on the scheduler).
Here you can filter the insights dashboard to only consider those bookings matching a user tags filter. For example, you might want to focus only on bookings made by those users in Marketing or Sales, or perhaps those users that have neither of those tags. Again you can manage user tags directly from the Insights page if you wish.
Key concept: "Utilization"
Utilization percentage — an important metric expressed in various Insights elements — is intuitively understood as: The fraction of a space’s available time which was actually used for something valuable.
Skedda is a sophisticated and powerful scheduling platform with many policy-based features, so it's useful to elaborate on what we exactly mean by a space’s “available time” and its “valuable usage”. The relevant concepts in Skedda that are involved are:
And, of course, regular "user"-type bookings
To figure out when a given space was actually available for booking on a given day, Skedda does the following:
Start with the times of the day that the space was "open", as defined by the Hours of availability for the space.
From these, subtract:
Any times explicitly/directly booked using an "unavailable" type booking.
Explanation: We don’t count “unavailable” bookings for a space towards its availability, because such bookings are used to indicate that the space is “out of action” for those times. This might result from a public holiday, repair work or similar. As such, times marked as directly unavailable are treated just like “closed” times that are outside of your Hours of availability (i.e. they’re ignored in the computation of utilization metrics).
Any times implicitly made "unavailable" as a result of space-sharing rules.
Explanation: If a booking for one space makes one or more other spaces unavailable due to space-sharing rules, then this is likewise placing those other spaces “out of action”. We hence ignore those times on those other spaces when computing their utilization metrics.
Any unavailable times caused by buffer-time rules
If a booking for one space makes neighboring times for that space unavailable (“buffer” times), then this is likewise placing the space “out of action” for those times. We hence ignore such buffer times when computing utilization metrics for the space.
The result is a set of times on the day for which the space was actually “available” to be booked for a valuable purpose.
Now that we understand what “available” time is for a space, we can turn to understanding what “valuable usage of a space” is. In short, it’s just those available times that are taken up by regular user-type bookings and internal-type bookings.
The ratio of a space’s "valuable usage" time to its “available” time is what we define as “utilization”. We always express this fraction as a percentage, and it’s always between 0% and 100%.
If there are no available times from which to compute a utilization metric, then the relevant dashboard element will either not be shown or will show an “N/A”. For example, if Saturday has no Hours of availability at all, then Saturday won’t be shown on the “Utilization by weekday” chart.
If a user booking or internal booking is created outside the hours of availability for the space, it’s ignored in utilization calculations. That is, only those bookings that are within the “available” times for a space contribute to utilization. If we were to count bookings outside of your hours of availability, then it’d be possible to have a utilization percentage above 100%, which would be somewhat confusing.
If you’re filtering the Insights dashboard by user tags, then the utilization metrics will normally be lower than when considering “all tags”, because the “valuable usage for a space” computation will only be considering those bookings that match your tags filter. For example, the utilization for bookings held by users tagged “IT team” might be 10%, whereas your overall usage considering all bookings might be 30%.
Detailed description of each dashboard element
Key Performance Indicator: "Utilization"
This number represents the average utilization percentage across all spaces and bookings matching your selected filters. Note that the “trend” indicator here is not showing the number of “percentage points” by which the utilization has changed, but rather the relative amount by which the percentage has changed. For example, if the utilization were 20% in the selected period and 10% in the previous period, then the utilization trend would show a 100% increase because your utilization doubled from one period to the next.
Key Performance Indicator: "Bookings"
This is the total number of user- and internal-type bookings matching your selected filter controls. Notes:
Bookings of the “unavailable” type are not counted in this metric.
If a booking is for multiple spaces, it’s still only counted once.
If a booking is a repeating/recurring booking, it is counted once for each date on which it occurs within the dashboard’s specified date range filter.
A user- or internal-booking is counted for this metric even if it’s created outside the hours of availability. This is in contrast to computing utilization, where such bookings are ignored.
Key Performance Indicator: "Users"
Key Performance Indicator: "Busiest Time"
This is the time of week having the maximum utilization (averaged across all occurrences of that day of week in your date range filter). This corresponds to the “darkest” area on the “Utilization by time of week” chart. If there are multiple times of the week with the same maximum utilization, only one of them will be shown here.
Chart: "Utilization by weekday"
This chart displays your utilization percentage broken down by day of week, considering only the bookings matching your filters. For example, this chart might indicate that you have a "mid-week mountain" of utilization, perhaps motivating you to look into strategies for distributing use to other days. Note that days with an "N/A" utilization will not be shown. Hovering or tapping on a bar shows additional information.
Chart: "Utilization by time of week"
This “matrix” chart shows utilization distributed by weekday and time of day. Darker colors represent higher utilization percentages, so this is a kind of "heat map". This chart can highlight the most-utilized times of the week at a finer level of granularity than the "Utilization by weekday" chart, helping you to understand popular periods of the day and booking trends. Color darkness levels are "normalized" (i.e. the maximum utilization will always be "very dark", even if it represents a small utilization percentage) in order to improve contrast and therefore pronounce differences between maximum and minimum utilization. Hovering or tapping on a cell shows additional information.
Chart: "Utilization timeline"
This chart shows the evolution of utilization across time within your date range filter, at the granularity of days and considering only the bookings/spaces matching the selected filters (note that dates with an "N/A" utilization are not shown). Hovering or tapping on a line point shows additional information. This chart can help you understand how volatile your utilization is, and if it's trending up or down over time. Skedda is a platform designed to make it 100% frictionless for your end users to create bookings, so you should absolutely expect this chart (and hence the utilization of your spaces) to climb after you adopt Skedda!
Chart: "Duration breakdown"
This colorful donut shows the percentages of bookings with certain durations (or duration ranges). Combined with the Spaces filter, you could use this donut to see the duration of bookings for your meeting rooms, for example. Hovering or tapping on a donut segment shows additional information.
Table: "Top users" (sortable)
(Note that this screenshot is showing entirely fake user names)
This table shows aggregate statistics for users that have a booking in either the main date range or the previous date range (the previous date range is used for the "Trend" comparison). Users without a booking in either period are not shown in this table.
The "Hours" value refers to the total duration for which spaces were booked by the user. Specifically note that a two-hour booking for two spaces represents four hours of usage (i.e. usage is the booking duration multiplied by the booking's number of spaces). The "Trend" information compares the "Hours" usage value between the previous and main date ranges. The "Bookings", "Hours" and "Trend" headers can be clicked/tapped to sort the table, however note that the table cannot be "paged" at this time.
Table: "Top spaces" (sortable)
This table shows aggregate statistics on a per-space basis. The "Bookings", "Utilization" and "Trend" headers can be clicked/tapped to sort the table. Using this table, you might choose to identity the spaces with the lowest utilization, for example (perhaps there are practical steps you can take to make them more attractive to book)! You can of course use the spaces filter to focus on just one kind of space (e.g. only rooms, or only desks). The "Trend" information compares the "Utilization" between the previous and main date ranges.
Generate a report
You can quickly generate a report of the current state of your dashboard, ready to send to management! Click the "Report" button at the top right (note that this button is not available on mobile devices).
How often is the information updated?
Insights information is recomputed every four hours. The "Last updated" time at the top-right of the dashboard indicates the time at which the information was computed.
Which users have access to the Insights dashboard?
By default, only the Owner has access to the Insights dashboard. If you wish for certain Admins to also be able to access the Insights dashboard, please reach out to Skedda support and we will help you configure this.
Is there a test/demo mode?
Yes! We've built in a demo mode that fills your Insights dashboard with gorgeous synthetic data. Simply append
testmode=1 as a query parameter to your Insights URL. That is, your Insights test/demo mode URL is
Note that this is the mode that you see if you haven't yet upgraded to Skedda Pro or above (i.e. you'll see dummy data if you're not at the right plan level).
Can I save a particular combination of filters?
Yes! Skedda automatically updates the URL in your browser's address bar when you modify your filters, so you can simply bookmark the link and you'll land on the same filter state when you follow the link in future.
We're happy to help! You can reach us via the blue chat widget!