Feature availability
The Advanced Analytics is not available by default. An additional subscription is needed. Once activated, it can take up to 24 hours for being visible on the ROOMZ Portal (https://portal.roomz.io ). Please contact sales@roomz.io for a trial.
Once activated, it can be found under the following menu:
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Overview
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Handle of the data
Data is always computed during the night, so data from today is available tomorrow. The working days come from the building settings, if you change the opening day’s for a building the future (from today on) will include these days. (If you would like to include the weekend in the report, you have to change it in the building settings. From the date of change on the Ad. Analytics will calculate also the new days on, data in the past will be not calculated)
For dashboards use sensor data we only take valid sensor data, if a workspace have no valid data for one day or more we handle this workspace like he would not exist (all calculations are done without this workspace). A sensor could have invalid date if something of the following issues were detected:
There is a physical shock on the device (for instance a knee bumping on the desk sensor)
There is an electrical static discharge
The USB is plugged/unplugged
If a sensor is not able to communicate with the server, he will buffer the usage data up to 10 days or more (depends on the usage). As soon as the sensor is able to communicate again, he will send the data to the server and these data are visible in the following day.
All data in the Analytics are anonymous and will be stored for max. 2 years. After 2 years, we delete the analytics data.
Layout for all dashboards
The layout of the is composed of 3 parts: the navigation, the filters and the report:
Context
The context represents what kind of information you would like to analyze. At the moment, the following contexts are available:
Utilization
Bookings
Utilization %
No-show
Point of view
Depending on the context, you can then select a point of view in order to do comparison. The Organization point of view will allow you to compare buildings and floors, whereas Floor will allow you to compare the workspaces on the same floor.
Help
It will bring you to this documentation.
Monday
Tuesday
Wednesday
Thursday
Friday
Average
Desk 1
10
0
0
0
0
2
Desk 2
2
2
2
2
2
2
At ROOMZ, we developed an algorithm allowing to categorize the utilization or bookings of a workspace. Per day, a workspace will be in one of the following categories: very rarely, rarely, frequently or very frequently. It will take also into consideration the aggregation on several days.
Based on its several years of experiences, ROOMZ’s algorithm is able to categorize
UtilizationThe utilization represents the reality of the occupancy of the workspaces.
Per Organization
Per Floor
BookingsFilters
Date
It allows to specify the start and end date of the period to analyze. Depending on your history, up to 2 years of data can be selected. You can also select or unselect specific days (e.g. only Monday and Tuesday).
Workspace type
The list of workspace types you can select will depends on your ROOMZ integration. The following types can be selected: Room, Desk, Huddle and Parking space. Depending on the context, some type could not be present (e.g. Huddle spaces are not bookable, so it will not be displayed on the Booking Report).
Workspaces
This is where you select specific buildings or floors, depending on the report and point of view. If the Organization’s point of view is selected, you can choose one or many buildings and floors. When you select Floor as point of view, you can select only one floor at a time. A search is available should you have a lot of buildings.
Tags
Tags are a free way to group workspaces together. It can be typically used for defining some equipment (e.g. wide-screen displays for desk, beamer for meeting room), zone (marketing, hr, …) or projects (e.g. project 1, project 2, …). A search is also available should you have a lot of tags
Reports
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:
TODO
Subordinate pages
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