Plan requirement
| Subscription | Suite Professional or higher, Explore Professional or higher |
| Access | Agent |
Whether unsolved work is growing. Needs the updates dataset, and it is the number that predicts trouble earliest.
Build it
- Ticket updates dataset, because this is about history rather than current state.
- Metric: unsolved tickets at the end of each period.
- Attribute: by week.
- Filter: the last six months.
Created against solved is the simpler version
Two lines on one chart: tickets created per week and tickets solved per week. Where created runs above solved, the backlog is growing, and the gap is how fast.
Easier to build and easier for an audience to read than a backlog count.
It is the earliest warning you get
Response times stay acceptable for a while as a backlog builds, then deteriorate quickly. The backlog turns upward weeks before customers notice.
Split by age
A backlog of recent tickets is a queue. A backlog of tickets older than a month is a different problem, and the totals look identical.
Watch pending separately
Tickets waiting on customers are not your backlog, and including them makes it look worse than it is. Separating them also reveals the ones waiting on a reply that never came.
A falling backlog is not automatically good
It can mean tickets are being closed without resolution. Read it next to reopens and satisfaction before celebrating.
Report it weekly
This is the number to put in front of whoever decides on staffing. It is a trend anybody can read, and it makes the case earlier than response times do.
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