Page Comparison

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• Advanced analytics subscription (contact Sales if you wish a demo)

• Booking system for the workspaces need needing to be analysed:

  • Room: customer booking system

  • Desk: myROOMZ

  • Parking slotspace: myROOMZ

Where does the data come from

The data for this Dashboard comes from the bookings of the workspace. We analyse only presence-occupancy data on the previously specified working days between the specified working hours (Can 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 from the myROOMZ application.

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 would appear to be the right metric, but when averaged on over several days you a losing an , important differentiation criterioncan be lost.

Let’s have take a look to an example:

Here, each desk meeting room has an average utilization occupancy of 2 hours. But as you can see, there is a clear difference. While the desk meeting room 1 has been well utilized on occupied for all of Monday, it was not utilized during used for the rest of the week.

Based on several years of experiencesexperience, ROOMZ , has developed a machine learning-based algorithm, allowing to categorize the utilization the simple categorisation of occupancy and bookings. The workspace will be in show as one of the following very rarely, rarely, frequently or very frequently; Very Rarely, Rarely, Frequently or Very Frequently.

Note: unlike the basic analytics, working hours no-longer need needs to be taken into account in consideration for this algorithm.What is visible on the Dashboard

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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1. A short overview about the workspaces in the report.

   1. In this report we see a lot of rarely booked workspaces, this could be improved.

2. 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. )

   1. In this example, we see clearly that the office is not well-used around towards the end of the week.

3. In the monthly profile you are able to see how 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 data.)

4. In the selected time period you are able to see the data over the selected time period.

5. In the buildings, you can compare the selected buildings or floors if you open a building by opening the data with the +.

   1. 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.

6. If you have set tags, you will see the differences on the tags here as welldata relating to them reported here too.

   1. This is a very nice great way to analyse 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 You will now see a larger view with the exact numbers for each section:

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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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1. On most booked, you see the 3 most and less the 3 least booked workspaces.

2. 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.

3. 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 bookedbeing used.

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