Resetting ticket merges

Problem description / use case

In daily ticket processing, agents sometimes merge incorrect tickets by mistake or due to a misunderstanding. These errors can currently only be corrected in a limited way.

Current workaround and its disadvantages

To repair an incorrect merge, the current process consists of manually splitting off the mismerged message into a new ticket.

This workaround has disadvantages:

  • Message remains in the original ticket: the split-off message remains visible in the original ticket. This makes a confusing ticket history. The recommended workaround of setting the article to “internal” does not solve the problem of clarity for the agents.
  • Tme-consuming and error-prone: The process of switching to “internal” and then splitting off is time-consuming and carries the risk of further errors being made.

Proposed solution / feature request

I would request the implementation of a function that can be used to easily and directly undo the merging of tickets.

This could be implemented using one of the following options, for example:

  • Option 1 (Preferred): An “Undo merge” button that is available for a certain time directly after a merge or can be found in the ticket menu. This action would cleanly separate the merged tickets back to their original form.
  • Option 2: An extended “split off” function. When splitting off a message, a checkbox could be added, such as “Remove message from original ticket”. If this is activated, the article is not only copied, but also completely moved to the new ticket.

Added value and benefits

Implementing this function would lead to the following improvements:

  • Time saving: agents can correct merge errors quickly and with one click.
  • Error reduction: The complexity of the current workaround is eliminated, reducing the risk of follow-up errors.
  • Clean ticket history: Ticket histories remain clear, which increases the quality of documentation and the efficiency of processing.
  • Improved user experience: The workflow for agents becomes more logical and intuitive.
3 Likes