Content:
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Basic requirement for the dashboard
Advanced analytics subscription (contact Sales if you wish a demo)
Booking system for the workspaces needing to be analyzed:
Room: customer booking system
Desk: myROOMZ
Parking space: myROOMZ
Where does the data come from
The data for this Dashboard comes from the bookings of the workspace. We analyze only occupancy data on the previously specified working days between the specified working hours (These can be changed in the building details). For Meeting rooms it is your , the data is gathered from the connected booking system, and for Desk / Parking slots spaces it is myROOMZ.
Categorization vs. Number of hours
As a workspace manager, you are looking for patterns, outliers and key differentiators between the workspaces. When comparing them, the hours of utilization seem to be the right metric, but when averaged on several days you a losing an important differentiation criterion.
Let’s have a look to an example:
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Monday[hours]
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Tuesday [hours]
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Wednesday hours]
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Thursday [hours]
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Friday [hours]
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Average Hours
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ROOMZ Category
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Meeting room 1
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11
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0
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0
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0
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0
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2.2
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Rarely
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Meeting room 2
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2
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2.5
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2.5
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2.5
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1.5
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2.2
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Frequently
Here, each desk has an average utilization of 2 hours. But as you can see, there is a clear difference. While the desk 1 has been well utilized on Monday, it was not utilized during the rest of the week.
Based on several years of experiences, ROOMZ, developed a machine learning-based algorithm allowing to categorize the utilization and bookings. The workspace will be in one of the following very rarely, rarely, frequently or very frequently.
Note: unlike the basic analytics, working hours no longer need to be taken into account in this algorithm.What is visible on the Dashboard
from the myROOMZ application.
Organization view
If you have set your Filters, you will be able to see a report like similar to the followingone below. You are able to click on ever every bar and the report will change and shows to show you only the selected data:
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A short overview about the workspaces in the report.
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You can select the base of the daily % usage calculation.
If you would like to analyze desks or parking spaces make sure to take 8h as a base, 8h are the maximum of booking time a desk / parking space can have. If you select 10h as a base, the desks / parking will be reaching max 80%.
In the
weekly profile,you are able to so how different the workspace are booked during the week. (The data is aggregated for all day's in over the selected period, so several weeks or months of data could be aggregated for each day of the week. )In this example, we see clearly that the office is not well-used around towards the end of the week.
In the
monthly profileyou are able to see how,you can view the bookings are over the months. (if If you have selected more than one year, the date data will be aggregated for some of the months, in the example above we have for , Jan, Feb and Marc March are an aggregation of two years of data.)In the
selected time period,you are able to see the data over the selected time period.In the
buildings, you can compare the selected buildings or floors if you open a building by opening the data with the +.It This is an easy way to see how the spaces could be booked differently on the different buildings or are used differently in various buildings, or on different floors.
If you have set tags, you will see the differences on the tags here as welldata relating to them reported here too.
This is a very nice great way to analyse analyze how different teams are use their workspaces.
You are able to open expand every part of the Report separately by open opening the details with a right mouse click (select show as a table):
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Now you have a bigger view and the exact number for every section:
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You will now see a larger view with the exact numbers for each section:
Floor view
If On the top bar, if you change on top the view to Floor, some parts of the report are will change:
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On most booked, you see the 3 most and less the 3 least booked workspaces.
If you have more than one floor in the selection, you are able to switch the floor with the navigation. Also, you can manage the level of zoom.You see now the zoom in/out.
Using this view of the data on the floorfloorspace, you will easily see on one where all the different workspaces are and how they are being booked.
How will be the data calculated
We collect all the booking data for every workspace, every day. The system aggregates the data based on your chosen booking rate and the filters you set. A daily booking of a desk / parking is counted as 8h, and a half day booking is 4h.
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Stichwort hinzufügenFor the Room, we take the actual booking time during the opening hours.
Huddles will be not shown in this Dashboard due to that this workspace is not bookable.