This report provides a detailed breakdown of zombie ticket report: 844 open tickets with no end in sight 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(
"Zombie Tickets", CALCULATE(
COUNTROWS('BI_Autotask_Tickets'),
ISBLANK('BI_Autotask_Tickets'[complete_datetime]) &&
'BI_Autotask_Tickets'[ticket_age_days] >= 14
),
"P1 Zombies", CALCULATE(
COUNTROWS('BI_Autotask_Tickets'),
ISBLANK('BI_Autotask_Tickets'[complete_datetime]) &&
'BI_Autotask_Tickets'[ticket_age_days] >= 14 &&
'BI_Autotask_Tickets'[priority_name] = "P1 - Kritisch"
)
)EVALUATE SUMMARIZECOLUMNS('BI_Autotask_Tickets'[status_name], "Count", COUNTROWS('BI_Autotask_Tickets'))| Priority | Zombie Count | % of Total | Risk Level |
|---|---|---|---|
| P1 — Critical | 5 | 0.6% | Immediate action |
| P2 — High | 19 | 2.3% | This week |
| P3 — Medium | 90 | 10.7% | Review sprint |
| P4 — Low | 556 | 65.9% | Triage & close |
| Service / Change | 174 | 20.6% | Batch review |
EVALUATE
SUMMARIZECOLUMNS(
'BI_Autotask_Tickets'[priority_name],
FILTER(
ALL('BI_Autotask_Tickets'),
ISBLANK('BI_Autotask_Tickets'[complete_datetime]) &&
'BI_Autotask_Tickets'[ticket_age_days] >= 14
),
"Count", COUNTROWS('BI_Autotask_Tickets')
)
ORDER BY [Count] DESCThese are your highest-priority incidents and they’re sitting in the zombie pile. Whether they’re genuinely stuck or just not closed out, each one represents a broken commitment to a customer. Pull them out of the queue this week for an immediate status review.
The customer replied — and then nothing happened. These tickets are the most damaging to customer relationships because the customer did their part. Set up an automation rule or SLA alert to trigger when a ticket stays in “Customer Responded” status for more than 24 hours.
A “New” ticket that has been sitting for a month was never triaged. These are prime candidates for bulk closure or reclassification. Run a triage session to determine which ones are still valid versus which should be closed as stale.
Planned tickets with no movement for 30+ days are a scheduling problem. Either the work was planned but resources were never assigned, or the plan was never revisited after the initial triage. Review your “Planned” backlog as a weekly recurring action item.
A zombie ticket is any open ticket that hasn’t been resolved for 14+ days — it may or may not have a due date. An overdue ticket is one that has passed its specific due date or SLA deadline. A ticket can be both: a zombie that is also past its due date. The zombie concept focuses on stagnation; overdue focuses on deadline breach.
14 days is a common MSP benchmark for identifying stale work. It’s long enough to exclude intentionally slow-moving service items or change requests, but short enough to catch tickets that have genuinely fallen through the cracks. You can adjust this threshold in the DAX filter to match your team’s SLA policy.
Autotask’s native workflow rules can trigger notifications based on ticket age, but building a dynamic “zombie dashboard” with priority heat maps and status breakdowns requires Power BI. The DAX queries in this report can be embedded in a live Power BI dashboard that refreshes every 15 minutes, giving your service manager a real-time view of aging tickets.
Start with P1 and P2 tickets first, as they represent the highest business risk. Then dedicate one hour per week to bulk-triaging “New” status zombies — many can be closed as resolved or irrelevant. For the “Customer Responded” bucket, set an automated follow-up rule so no response sits unanswered for more than 4 hours. Systematic weekly triage sessions typically reduce zombie counts by 30-50% within a month.
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