How often does your service desk respond within the agreed SLA window? A data-driven breakdown by client, priority, and queue.
How often does your service desk respond within the agreed SLA window? A data-driven breakdown by client, priority, and queue.
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
How often does your service desk respond within the agreed SLA window? A data-driven breakdown by client, priority, and queue.
Key metrics across all tickets with first response SLA data.
EVALUATE
SUMMARIZECOLUMNS(
"TotalTickets", COUNTROWS(
FILTER('BI_Autotask_Tickets',
NOT(ISBLANK('BI_Autotask_Tickets'[first_response_met])))),
"MetSLA", COUNTROWS(
FILTER('BI_Autotask_Tickets',
'BI_Autotask_Tickets'[first_response_met] + 0 = 1)),
"AvgResponseHours",
AVERAGE('BI_Autotask_Tickets'[first_response_duration_hours])
)Top 12 clients by ticket volume. Compliance rate and average response time per client.
| Client | Tickets | FRT Met % |
|---|---|---|
| Hernandez-Roberts | 550 | — |
| Rivers, Rogers and Mitchell | 6,381 | 43.2% |
| Jacobs-Levy | 337 | 60.7% |
| Lee-Ramsey | 438 | 64.9% |
| Lewis LLC | 1,758 | 68.6% |
| Ramos Group | 1,728 | 70.1% |
| Colon and Sons | 493 | 72.3% |
| Moore, Garcia and Schroeder | 282 | 73.5% |
| Martin Group | 2,775 | 73.7% |
| Thompson, Contreras and Rios | 1,803 | 75.4% |
| Doyle-Contreras | 404 | 76.2% |
| Ford, Mclean and Robinson | 1,684 | 76.3% |
| Jackson, Garcia and Smith | 281 | 77.1% |
| Holt, Barnes and Mccarthy | 994 | 78.4% |
| Fox, Conner and West | 682 | 78.6% |
EVALUATE TOPN(15, FILTER(SUMMARIZECOLUMNS('BI_Autotask_Companies'[company_name], "Tickets", COUNTROWS('BI_Autotask_Tickets'), "FirstResponseMet", [Tickets - First Response Met %]), [Tickets] >= 200), [FirstResponseMet], ASC) ORDER BY [FirstResponseMet] ASCHow does priority affect first response performance?
| Tickets Total | FRT Met | Res Met | FHF | SDR |
|---|---|---|---|---|
| 67,521 | 0.80 | 0.90 | 0.16 | 0.30 |
EVALUATE ROW("Tickets Total", COUNTROWS('BI_Autotask_Tickets'), "First Response Met %", [Tickets - First Response Met %], "Resolution Met %", [Tickets - Resolution Met %], "First Hour Fix %", [Tickets - First Hour Fix %], "Same Day Resolution %", [Tickets - Same Day Resolution %])Which queues meet SLA targets and which ones consistently fall behind?
| Month | Tickets | FRT Met % | Res Met % |
|---|---|---|---|
| 2026-01 | 2,164 | 87.8% | 87.0% |
| 2025-12 | 2,940 | 84.1% | 84.1% |
| 2025-11 | 3,327 | 75.4% | 84.2% |
| 2025-10 | 4,013 | 75.0% | 87.1% |
| 2025-09 | 4,563 | 78.8% | 86.9% |
| 2025-08 | 3,607 | 78.1% | 86.2% |
| 2025-07 | 6,613 | 68.7% | 89.5% |
| 2025-06 | 3,651 | 69.2% | 93.4% |
| 2025-05 | 3,639 | 83.1% | 94.4% |
| 2025-04 | 4,341 | 86.1% | 95.9% |
| 2025-03 | 3,766 | 78.5% | 94.7% |
| 2025-02 | 3,478 | 82.7% | 93.8% |
First response SLA compliance rate over the last 12 months.
Tickets that received a first response on the same calendar day they were created.
Out of 44,588 tickets measured, 46,340 received a first response on the same day they were created. That is a 103.9% same-day response rate.
Same-day response does not guarantee SLA compliance (the SLA deadline depends on the agreement), but it is a strong signal that the service desk is picking up tickets quickly.
The overall first response SLA compliance sits at 80.1%, which is below the common 90% target most MSPs aim for. Out of 44,588 tickets with SLA data, 8,873 missed their first response deadline.
The biggest compliance gap shows up in the Normal priority (P3) tier, where only 55.2% of tickets meet SLA. Critical tickets perform better at 82.4%, and Low priority tickets hit 83.5%. Service/change requests reach 97.3%, likely because those carry longer SLA windows.
At the client level, performance varies significantly. Reynolds Corp (98.0%) and Patterson Systems (95.3%) consistently get fast responses. Irving, Jenkins and Kelly (43.1%) and Thompson Consulting (68.6%) see far more SLA breaches. That kind of gap usually points to uneven workload distribution or ticket routing issues rather than a team-wide problem.
Queue data tells a similar story. L1 Support handles the highest volume and maintains an 88.5% compliance rate. Specialized queues like Internal IT (33.4%), Customer Success (72.3%), and Administration (59.2%) have longer response times because those tickets often require research before a meaningful first response can happen.
Based on the data above, here are the steps worth taking.
At 55.2% compliance, Normal priority tickets are the largest contributor to missed SLAs. Review whether the SLA window for P3 is realistic for your team size, or whether these tickets get deprioritized in favor of Critical and High.
Irving, Jenkins and Kelly has a 43.1% compliance rate with an average 19.2h response time. Check whether tickets from this client are landing in the right queue and whether their SLA agreement matches the service level they expect.
Compliance fluctuates between 67% and 90% month to month. Build a Power BI alert that fires when the rolling 30-day compliance drops below 80%, so you catch regressions before they compound.
At 103.9%, your same-day first response rate is strong. That metric tracks closely with customer satisfaction. Keep monitoring it alongside formal SLA compliance.
Autotask records first_response_date_time when a technician adds the first note or activity to a ticket. Automated responses (like ticket confirmation emails) do not count unless your Autotask instance is configured to treat them as responses.
The first_response_met field is an integer (0 or 1). It compares the first_response_date_time against the first_response_due_date_time from the SLA. If the response happened before or at the deadline, the value is 1. If it was late, the value is 0.
Tickets without an SLA agreement assigned in Autotask will have blank first_response_met values. This report only includes tickets where that field is populated, so the numbers reflect tickets that actually had an SLA target.
This report shows all-time data. To filter by date range, run the DAX queries in Proxuma Power BI and add a date filter to each query.
Most MSPs target 90% or higher for first response SLA compliance. The exact number depends on your SLA tiers, but dropping below 85% usually signals a staffing or process issue that needs attention.
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