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Content:

Where does the data come from

The data for this Dashboard comes from the Sensors. We analyse only presence-data on working days between 7:00 until 19:00. Data outside this period is currently not taken into account. We calculate the usage of a workspace per day, if the sensor have times without occupation which are less than 15' we calculate it as occupied for the hole period. (Ex. usage between 8:00 until 9:00 and from 9:10 to 10:00 the usage for this period is 2h / if the break is from 9:00 to 9:20 the usage would be 1h 40')

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:

 

Monday[hours]

Tuesday [hours]

Wednesday hours]

Thursday [hours]

Friday [hours]

Average Hours

ROOMZ Category

Desk 1

11

0

0

0

0

2.2

Rarely

Desk 2

2

2.5

2.5

2.5

1.5

2.2

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

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:

image-20240305-142530.png
  1. A short overview about the workspaces in the report.

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

  2. In the weekly profile you are able to so how different the workspace are used 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 usage is 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 used 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):

image-20240305-143038.png

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

image-20240305-143131.png

Floor view

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

image-20240305-144249.png

  1. On most utilized you see the 3 most and less used 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 desks are and how they are used.

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