Currently we have a backlog (ssshhh.. its not that bad)… the problem we have is, we have no idea of the amount of hours worth of resource time it is to get rid of the backlog, just the quantity. E.g. 100 tickets could mean 100 minutes work, or 1000000 minutes. Two very different approaches to clear!
End goal here is to fully understand the full workstack by how much time it would take to clear.
Idea is two fold:
- Manual - Have an estimated effort field for tickets, so that once triaged, this can be completed and therefore you have a rough idea of how long is required to complete that task.
- Freddy AI - for the more mature deployments… utilising Freddy (or similar AI functionality) to be able to scan the ticket on entry and best determine the approx effort for completion using previous ticket data and/or knowledge articles.
Once all tickets in a queue (using either option) have been updated in the same way, you should also now be able to report on this field, showing a Total Resource Effort of all live tickets in the queue. Would also be handy to be able to split it per agent/assignee.
Future look on this would be that you could also see the trends of efficiencies of these tickets when implementing new processes or solutions for that particular workflow/subject, making feedback or ROI slightly easier with statistics.
