This report provides a detailed breakdown of sla performance by ticket origin — rmm vs manual 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 delivery managers, operations leads, and MSP owners tracking service quality
How often: Weekly for operational adjustments, monthly for client reporting, quarterly for contract reviews
| Metric | Value |
|---|---|
| Resolution Met | 90.2% |
| First Hour Fix | 16.1% |
| Same-Day | 30.0% |
| Closure | 98.8% |
EVALUATE ROW("ResolutionMet", [Tickets - Resolution Met %], "FirstHourFix", [Tickets - First Hour Fix %], "SameDayRes", [Tickets - Same Day Resolution %], "ClosureRate", [Tickets - Closure Rate %], "TotalTickets", [Tickets - Count - Created])When Datto creates a ticket, it includes the device name, alert type, severity, and often a suggested priority — automatically. This means the ticket routes correctly without a triage step. Engineers pick it up knowing exactly what they're dealing with. Manual tickets often arrive as unstructured email or phone summaries that require interpretation before routing, adding time before the SLA clock is acknowledged.
RMM alerts not only get acknowledged faster, they get resolved faster. This likely reflects the nature of the work: hardware or software conditions that triggered an alert are often addressable with a specific action (patch, reboot, disk cleanup). The resolution path is more predictable than for manually reported issues, which can range from vague connectivity complaints to complex multi-system problems.
With 54,142 manual tickets at 79.4% first-response SLA, the majority of your SLA exposure sits in the manual ticket category. Even a 3-point improvement in manual first-response SLA (from 79% to 82%) would lift the overall service desk average by ~2 percentage points. The queue-level and priority-level SLA reports identify where the manual ticket weakness is concentrated.
If the SLA gap were a capacity issue, RMM tickets wouldn't necessarily outperform manual ones — they'd all be equally delayed. The fact that RMM tickets consistently hit SLA better suggests the bottleneck is routing and acknowledgement, not engineer availability. Auto-routing rules that assign manual tickets to a specific queue or resource on creation — mimicking how RMM integrations work — could close a meaningful portion of this gap.
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