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The data for this Dashboard comes from the occupancy Sensors. We only analyse only presence-occupancy data on selected working days between the selected working hours (Can These can be changed in the building details). Data outside this period is currently not taken into account. We calculate the usage of a workspace per day, if the sensor have has times without occupation which are less than 15', we calculate it as occupied for the whole period. (Exe.g. usage occupancy 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')

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As a workspace manager, you are looking for patterns, outliers and key differentiators between the workspaces. When comparing them, the hours of utilization seem may 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 has an average utilization occupancy of 2 hours. But as you can see, there is a clear difference. While the desk 1 has been well utilized used on Monday, it was not utilized occupied during 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 following. You are able to click on ever bar and the report will change and shows one below. Clicking on the various bars prompts the report to change, showing you only the selected data:

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1. A short overview about of the workspaces in the this 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 see how the different the workspace workspaces are used during the week. (The data for each day of the week is aggregated for all day's in the selected periodover the weeks or months selected,)

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

3. In the The monthly profile you are able to see how the usage is shows the occupancy over the months. (if If you have selected more than one year, the date data will be aggregated for the months, in the example above, we have two years’ of data aggregated for Jan, Feb and Marc an aggregation of two years dataMarch)

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

   1. In the buildings, you can compare the selected buildings or floors

   if you open a building

   1. by opening the data with the +.It

5. This is an easy way to see how the spaces

   could be

   are used differently in various buildings, or on

   the

   different

   buildings or

   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:

Floor view

If On the top bar, if you change on top the view to Floor, some parts details of the report are will change: 

1. On most utilized you see the 3 most and less the 3 least used workspaces.

2. If you have more than one floor in the selection, you are able to switch the floor with using 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 the different workspaces are and how they are used.