This report provides a detailed breakdown of how are tickets distributed across queues? for managed service providers.
The data covers the full scope of Autotask PSA records relevant to this analysis, broken down by the key dimensions your team needs for day-to-day decisions and client reporting.
Who should use this: Service desk managers, dispatch leads, and operations teams
How often: Daily for queue management, weekly for trend analysis, monthly for capacity planning
EVALUATE
ROW(
"Queues Unique Count", [Queues - Unique Count],
"Queues Avg Resources", [Queues - Avg Resources per Queue],
"Queues Resources Assigned", [Queues - Resources Assigned]
)| Queue | Tickets | % of Total |
|---|---|---|
| L1 Support | 31,378 | 46.5% |
| Centralized Services | 17,082 | 25.3% |
| L2 Support | 7,889 | 11.7% |
| Merged Tickets | 4,999 | 7.4% |
| Technical Alignment | 2,316 | 3.4% |
EVALUATE TOPN(10, SUMMARIZECOLUMNS('BI_Autotask_Tickets'[queue_name], "TicketCount", COUNTROWS('BI_Autotask_Tickets')), [TicketCount], DESC)L1 Support handles nearly half of all tickets. That concentration is expected for a typical MSP, but it also means L1 is the single biggest risk point for SLA breaches when volume spikes. Centralized Services adds another quarter, making those two queues responsible for 72% of all volume.
Technical Alignment and Customer Success deserve immediate attention. Despite having a fraction of L1's volume, they carry a disproportionate open ticket load. A 12-13% open rate suggests tickets are entering those queues without a clear path to resolution — which could indicate missing owners, unclear escalation paths, or scope creep.
L1, by contrast, processes 31,378 tickets with only 107 open — a 0.34% open rate that reflects a well-functioning triage process.
For high-volume queues like L1, anything under 1% is strong. For specialty queues (Technical Alignment, Customer Success), under 5% is a reasonable target. Above 10% in any queue signals a workflow problem worth investigating.
Autotask's built-in reporting shows individual queue views, but it doesn't provide a single-screen breakdown of all queues by volume share and open rate. That cross-queue comparison requires custom reporting — which is exactly what Power BI provides.
Weekly for operational queues (L1, L2), monthly for specialty queues. If you have a live dashboard, set up an alert when any queue's open rate crosses a threshold — say 8% — so you catch problems before they become visible to clients.
Yes. In the interactive Power BI dashboard version of this report, you can filter by resource, date range, priority, and company. The DAX queries in this report are the starting point — add CALCULATETABLE filters to slice further.
Connect Proxuma Power BI to your PSA, RMM, and M365 environment, use an MCP-compatible AI to ask questions, and generate custom reports - in minutes, not days.
See more reports Get started