Dashboard: Bookings

Content:

Basic requirement for the dashboard

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

• Booking system for the workspaces need to be analysed:

  • Room: customer booking system

  • Desk: myROOMZ

  • Parking slot: myROOMZ

Where does the data come from

The data for this Dashboard comes from the bookings of the workspace. We analyse only presence-data on working days between the working hours (Can be changed in the building details). For Meeting rooms it is your connected booking system and for Desk / Parking slots 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:

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

Organization view

If you have set your Filters, you will be able to see a report like the following. You are able to click on ever bar and the report will change and shows you only the selected data:

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 the selected period)

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

3. In the monthly profile you are able to see how the bookings are over the months. (if you have selected more than one year the date will be aggregated for the months, in the example above we have for Jan, Feb and Marc 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 with the +.

   1. It is an easy way to see how the spaces could be booked differently on the different buildings or floors.

6. If you have set tags you will see the differences on the tags here as well.

   1. This is a very nice way to analyse how different teams are use their workspaces.

You are able to open every part of the Report separately by open the details with a right mouse click (select show as a table):

Now you have a bigger view and the exact number for every section:

Floor view

If you change on top the view to Floor some parts of the report are change:

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

3. You see now the view of the data on the floor, you see on one where the different workspaces are and how they are booked.

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