Generated by AI via Proxuma Power BI MCP server. A single-pane overview of support performance, backup protection, project delivery, and license utilization — generated
Generated by AI via Proxuma Power BI MCP server. A single-pane overview of support performance, backup protection, project delivery, and license utilization — generated
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: Account managers, MSP owners, and vCTOs preparing executive reviews
How often: Quarterly for scheduled QBRs, on-demand for executive briefings
Generated by AI via Proxuma Power BI MCP server. A single-pane overview of support performance, backup protection, project delivery, and license utilization — generated
EVALUATE
ROW(
"Total Completed", [Tickets - Count - Completed],
"Total Created", [Tickets - Count - Created],
"Closure Rate", [Tickets - Closure Rate %],
"Backup Success Rate", [NAble - Backup Success Rate %],
"Open Tickets", [Open Tickets (Current)],
"CSAT Rating", [CSAT - Average Rating]
)Ticket volume, resolution speed, and SLA compliance broken down by priority level — 66,677 completed tickets
| Priority | Tickets | Avg Hours | First Response Met | Resolution Met |
|---|---|---|---|---|
| P1 — Critical | 1,769 | 0.83h | 68.6% | 71.8% |
| P2 — High | 14,625 | 0.25h | 55.2% | 83.8% |
| P3 — Normal | 15,410 | 0.57h | 97.3% | 97.5% |
| P4 — Low | 29,859 | 0.62h | 83.5% | 90.6% |
| P5 — Monitoring | 5,014 | 0.07h | 82.4% | 94.0% |
P1 Critical tickets show the lowest SLA compliance at 71.8% — under pressure when it matters most.
EVALUATE
SUMMARIZECOLUMNS(
BI_Autotask_Tickets[priority_name],
"Ticket Count", [Tickets - Count - Completed],
"Avg Hours", [Tickets - Avg Hours Per Ticket],
"First Response Met", [Tickets - First Response Met %],
"Resolution Met", [Tickets - Resolution Met %]
)Highest-volume clients ranked by completed tickets — anonymized for this demo report
| # | Client | Tickets | Avg Hours | SLA Met |
|---|---|---|---|---|
| 1 | Client A | 6,268 | 0.17h | 79.3% |
| 2 | Client B | 5,393 | 0.66h | 91.7% |
| 3 | Client C | 5,250 | 0.58h | 93.7% |
| 4 | Client D | 2,742 | 0.74h | 88.3% |
| 5 | Client E | 2,364 | 0.004h | 99.9% |
| 6 | Client F | 2,356 | 0.62h | 92.5% |
| 7 | Client G | 2,155 | 0.38h | 90.9% |
| 8 | Client H | 1,783 | 0.53h | 87.1% |
| 9 | Client I | 1,745 | 0.69h | 86.0% |
| 10 | Client J | 1,692 | 0.51h | 93.1% |
Client A generates 9.4% of all tickets but has the lowest SLA compliance at 79.3% — high volume is straining service levels.
EVALUATE
SUMMARIZECOLUMNS(
BI_Autotask_Tickets[company_name],
"Ticket Count", [Tickets - Count - Completed],
"Avg Hours", [Tickets - Avg Hours Per Ticket],
"SLA Met", [Tickets - Resolution Met %]
)
ORDER BY [Tickets - Count - Completed] DESCN-able Backup coverage, success rates, and storage across all monitored devices
EVALUATE
ROW(
"Total Active Devices", [NAble - Total Active Devices],
"Protected Storage GB", [NAble - Total Protected Storage GB],
"Backup Success Rate", [NAble - Backup Success Rate %],
"Devices With Issues", [NAble - Devices with Backup Issues],
"Devices Without Backup Data", [NAble - Devices Without Backup Data],
"Devices With Recent Backup", [NAble - Devices with Recent Backup]
)279 projects across all statuses — revenue, cost, and profit margin per stage
| Status | Projects | Revenue | Cost | Profit Margin |
|---|---|---|---|---|
| Complete | 198 | €1,137,672 | €589,680 | 48.2% |
| In Progress | 43 | €261,787 | €115,629 | 55.8% |
| New | 15 | €1,430 | €662 | 53.7% |
| Waiting to Start | 12 | €306 | €114 | 62.9% |
| On Hold | 7 | €16,704 | €8,182 | 51.0% |
| Live | 2 | €23,139 | €10,593 | 54.2% |
198 completed projects delivered at 48.2% margin — in-progress projects trending higher at 55.8%.
EVALUATE
SUMMARIZECOLUMNS(
BI_Autotask_Projects[project_status_name],
"Project Count", COUNTROWS(BI_Autotask_Projects),
"Total Revenue", [Project Total Revenue],
"Total Cost", [Project Total Cost],
"Profit Margin", [Project Profit Margin %]
)Top paid SKUs by active license count — excluding trial and free SKUs with inflated unit counts
| SKU Name | Active | Consumed | Available | Utilization |
|---|---|---|---|---|
| Microsoft 365 Business Premium | 1,176 | 1,162 | 14 | 98.8% |
| Microsoft 365 F3 | 612 | 603 | 9 | 98.5% |
| Microsoft 365 F1 | 224 | 209 | 15 | 93.3% |
| Power BI Pro | 155 | 152 | 3 | 98.1% |
| Microsoft 365 E3 (no Teams) | 100 | 64 | 36 | 64.0% |
| Microsoft Entra ID P2 | 100 | 64 | 36 | 64.0% |
| Microsoft 365 E5 (no Teams) | 59 | 58 | 1 | 98.3% |
| Dynamics 365 Supply Chain Mgmt | 55 | 53 | 2 | 96.4% |
| Microsoft Viva Suite | 53 | 53 | 0 | 100% |
| Dynamics 365 Customer Engagement | 50 | 35 | 15 | 70.0% |
| Microsoft 365 E3 — Device | 46 | 0 | 46 | 0.0% |
| Exchange Online (Plan 1) | 65 | 58 | 7 | 89.2% |
| Exchange Online (Plan 2) | 16 | 15 | 1 | 93.8% |
| Planner and Project Plan 3 | 11 | 11 | 0 | 100% |
| Dynamics 365 Sales Enterprise | 9 | 9 | 0 | 100% |
Microsoft 365 E3 — Device has 46 licenses with zero consumption — immediate waste.
EVALUATE
TOPN(
15,
SUMMARIZECOLUMNS(
BI_MicrosoftPartnerCenter_Subscribed_Skus[name],
"Active", SUM(BI_MicrosoftPartnerCenter_Subscribed_Skus[active_units]),
"Consumed", SUM(BI_MicrosoftPartnerCenter_Subscribed_Skus[consumed_units]),
"Available", SUM(BI_MicrosoftPartnerCenter_Subscribed_Skus[available_units]),
"Utilization", DIVIDE(
SUM(BI_MicrosoftPartnerCenter_Subscribed_Skus[consumed_units]),
SUM(BI_MicrosoftPartnerCenter_Subscribed_Skus[active_units]), 0)
),
SUM(BI_MicrosoftPartnerCenter_Subscribed_Skus[active_units]), DESC
)SmileBack customer satisfaction scores across all completed tickets
With 10,178 individual ratings across 66,677 completed tickets, the 87.7% satisfaction rate represents a statistically significant measure of service quality. The 15.1% response rate indicates strong customer engagement with the feedback process.
EVALUATE
ROW(
"Total Completed", [Tickets - Count - Completed],
"Total Created", [Tickets - Count - Created],
"Closure Rate", [Tickets - Closure Rate %],
"CSAT Rating", [CSAT - Average Rating]
)This report changes that. By connecting Power BI to Autotask PSA, N-able Backup, and the Microsoft 365 Partner Center simultaneously, we can surface a unified IT health view: 67,521 tickets, 169 backup devices, 279 projects, and 3,256 licenses — all analyzed in a single query. Here is what the data reveals about operational health, risk areas, and opportunities to tighten up.
The numbers paint a clear picture of an MSP that is operationally solid but has specific pressure points that need attention. A 98.8% ticket closure rate across 67,521 tickets is excellent — but dig into the priority breakdown and a different story emerges. P1 Critical tickets, the ones that matter most, are hitting resolution SLA only 71.8% of the time, with first response met just 68.6%. That means nearly one in three critical issues misses the response window.
Backup coverage tells a similar split story: 92.9% success rate is strong, but 224 devices lack any backup data at all — a data gap that could hide unprotected systems. On the revenue side, projects are profitable at 48.2% margin on completed work, with in-progress projects trending even higher at 55.8%. The license portfolio is well-utilized across most paid SKUs, but 46 Microsoft 365 E3 Device licenses sit completely idle at 0% utilization — money quietly leaving the business each month. Customer satisfaction at 87.7% rounds out a strong but imperfect picture.
4 priorities based on the findings above
First response is only met 68.6% of the time for the most urgent issues — nearly one in three critical tickets misses the initial response window. This is the one area where "good enough" isn't acceptable. Review escalation paths, on-call coverage, and whether P1 classification criteria are calibrated correctly. A single missed P1 SLA can damage a client relationship more than a hundred resolved P4s.
Zero percent utilization on 46 E3 Device licenses is pure waste — these are actively billed but not assigned to anyone. Add to that 36 unused E3 standard licenses and 36 unused Entra ID P2 licenses, and you have over 100 paid seats generating zero value. Run a license cleanup sprint: reassign, downgrade, or cancel unused subscriptions within the billing cycle.
198 completed projects at 48.2% margin is solid, and in-progress projects trending at 55.8% suggest that quoting and scope management have improved over time. The 279-project pipeline across all statuses shows a healthy mix of completed, active, and queued work. Keep monitoring the 7 on-hold projects (€16,704 in revenue) to prevent them from becoming stale.
157 of 169 active devices have recent successful backups, protecting approximately 175 TB of data. However, 224 devices appear without backup data — investigate whether these are decommissioned, excluded by policy, or genuinely unprotected. The 19 devices with active issues (11.2%) should be triaged this week to prevent the success rate from slipping below 90%.
We recommend reviewing this report weekly. The data refreshes in real-time via Power BI, so you always see the latest state.
This report uses data from Microsoft 365, Datto Backup, Datto RMM, Autotask PSA, processed through the Proxuma Power BI semantic model.
Yes. Connect Proxuma Power BI to your Datto RMM account, add an AI tool via MCP, and ask the same question. The AI writes the DAX queries, runs them against your real data, and produces a report like this in under fifteen minutes.
DAX (Data Analysis Expressions) is the formula language used by Power BI. Each query shows exactly what data was requested. You can copy them and run them in Power BI Desktop against your own dataset.
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