New Features đ
Sales copy
Highly awaited feature goes live!
Any sale can be duplicated. Users save time if sales with the same content are repeated more often. The reservations are moved to the new dates automatically, and warnings of duplicate bookings (room or resource) appear. When all the reservations are in the right places, the sale in the draft state must be accepted as an open sale.
In the copying phase, you can define what content you want to copy for the new sale. For example, copying the list of participants or room reservations is often not necessary, so you can leave them out of the copy at the beginning.
Duplicating an enrolment brings the copy under the same event.
Packet meal listing
Allergy information on the package meal list can be grouped by sales, which makes it easier to read the allergy information of the group.
The grouping of the meals section has been corrected to work according to the name. So, for example, all different lunches appear in the same group if they are named the same.
A new function is a simplified summary view for planning work shifts and food orders.
The view is limited to max 5 weeks at time to simplify navigation and prevent massive lists of data.
Sales participant list print
A new grouping function has been added to the sales participant list printout. The list can therefore be printed grouped by the participant group in addition to the previous room and participant options.
Bug Fixes đ
Editing the number of participants in a room reservation
The number of participants in the room reservation can be modified again directly from the sales office. Previously entered information was not saved in the system if the change was made by sales in the Accommodation view.
Sales resource reservations
The view has been corrected to scale nicely even on a smaller screen. Previously, the page had to be scrolled sideways if the screen size was small, e.g. 13 inches.
Technological Improvements đ
The Cloud environment has been reconfigured to better tolerate higher load times. From the history we saw that at certain hours the system got more load and then the configuration of the database connection started to slow down the performance. We adjusted the parameters so that the system better handles the peak load as well.
As a part of our continuous improvement, we have also optimised some parts of our internals to respond faster and scale to larger amounts of data.