Difficulty: novice

Reservation Insights dashboard provides insight in the historical reservation data. The question it tries to answer is: “Based on data of reservations that are not cancelled, how can we optimize usage and learn from usage patterns?”Pattern dashboard reports on all reservations, including cancelled reservations and no-shows (available when sensor data is tracked).

The dashboard does not contain detailed timelines, but shows monthly trends on historical data.

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).

“Summary” page

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title Expand for more information on Summary page
Gain insight into how spaces are  being booked & identify under-performances and take action Image Removed

Get a quick summary insights on how people book and cancel their reservations, to learn from booking patterns to increase awareness and encourage best-practices Image Added

“Cancellations” page

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.

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View how many cancellations were made Per month Per building Per organization Image Added Info Cancelling in advance = good behavior

“No Shows” 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 Removed

“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 Removed

“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 Removed

‪See what are the “no show” patterns where the reserved space is not cancelled in advance, in order to take appropriate actions to reduce the “no shows” Image Added Info (automatic) cancellations after the meeting starts = bad behavior

“Reservations Patterns” 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

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Fixed color coding:

“Data” page

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title Expand for more information on Data Distribution page
‪Details ‪of the raw data ‪per reservation ‪‪and how they are ‪calculated per hour Image Removed

“Scope” page

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‪Presents correlations between ‪Organization ‪Building ‪Type ‪Category Status Image Removed ‪Get a quick summary insights on how people book and cancel their reservations, in order to learn from booking patterns to increase awareness and encourage best-practices

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)

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