Difficulty: novice

Parking monitor Reservation Insights dashboard provides insight in the historical data that is gathered by Parking devices that send data to Workplace platformreservation data. The question it tries to answer is: “Which insight/trend is communicated through the data“Based on data of reservations that are not cancelled, how can we optimize usage and learn from usage patterns?”

Historical data means that the visualized data in the dashboard was gathered until yesterday. The current Reservations Insights will load data from 01/07/2022 (hard coded date).

“Parking analysis” page

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As soon as location filtering is set to floor level, floor plan will show up.

If Workplace is receiving data that is relevant for this dashboard, the location will be colored. The darker the color, the more this locations is occupied. For the selected period, brighter colored locations are less occupied than darker colored locations.

More information

Check out Bosch Parking Sensor to better understand how data is captured by the Spacewell parking sensor and subsequently visualized on Workplace touch points.

Metric definitions

• ‪# Reservations: number of reservations that are NOT cancelled

• ‪Reservation rate: Hours reserved / (Hours available x Nr of reservable items) -> calculated per hour

• Avg duration: Avg (Hours reserved / Nr of Reservations)

• Avg leadtime: Avg (Start date – Creation date)

“Summary” page

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Gain insight into how spaces are  being booked & identify under-performances and take action Image Added

“Metrics per Building” page

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Drill down the reservation data per building or select several buildings to identify trends. Example: I want to select all my buildings in the Netherlands to see reservation trends happening in the Dutch workplace. ‪Reports on Rooms Workplaces Parking spots Equipment Available metrics # of reservations Avg duration (h) Avg / peak reservation rate Avg lead time (d) Image Added

“Reservation Patterns” page

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title Expand for more information on Reservation Patterns page
‪Gives insight in most popular booking patterns: When and where are people making most reservations? And for how long? Image Added

“Reservable items” page

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title Expand for more information on Reservable Items page
‪Shows the full list of Reservable items and gives overall simple statistics for every reservable item: #reservations per category #reservations per room size → Check all the reservable items and see how many times each item was reserved Image Added

“Distribution” page

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title Expand for more information on Distribution page
‪Gives insight in most popular booking patterns: When and where are people making most reservations? And for how long? Do we book mainly large meeting rooms or small ones? How does this evolve over time? Image Added

“Calendar” page

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title Expand for more information on Calendar page
‪Check the full list of ‪reservable items and the hours reserved per day The Clear & visual calendar view with legends shows for how many hours that item was reserved per day so you can identify under-performances. the columns show the reservable items the rows present the calendar days the cells indicate how many hours the item was reserved per day. The color coding helps quickly identify popular or under-performing reservable items Image Added Fixed color coding: 0h reserved on a day: white < 2h reserved on a day: red 2-4h reserved on a day: orange 4-12h reserved on a day: green reserved up to 24h on a day: blue

“Data” page

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‪Details ‪of the raw data ‪per reservation ‪‪and how they are ‪calculated per hour Image Added

“Scope” page

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title Expand for more information on Scope page
‪Presents correlations between ‪Organization ‪Building ‪Type ‪Category Status Image Added

Metric definitions

• ‪# Reservations: number of reservations that are NOT cancelled

• ‪Reservation rate: Hours reserved / (Hours available x Nr of reservable items) -> calculated per hour

• Avg duration: Avg (Hours reserved / Nr of Reservations)

• Avg leadtime: Avg (Start date – Creation date)

More information

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