Analysis and reporting on problem devices - top alert generators for managed service providers.
Analysis and reporting on problem devices - top alert generators 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: NOC teams, service managers, and operations leads managing alert workflows
How often: Daily for alert triage, weekly for noise reduction, monthly for monitoring optimization
Analysis and reporting on problem devices - top alert generators for managed service providers.
EVALUATE
ROW(
"Top 50 Devices", COUNTROWS(BI_Datto_Rmm_Alerts),
"Worst Device", CALCULATE(COUNTROWS(BI_Datto_Rmm_Alerts), BI_Datto_Rmm_Alerts[status] = "Active")
)Breakdown of top alert generators across managed clients.
| Client | Top 50 Devices | Worst Device | Avg per Device | Replacement Needed | Status |
|---|---|---|---|---|---|
| Lewis LLC | 41.2% | 247 alerts | 2 | 23 | Good |
| Martin Group | 37.9% | 247 alerts | 2 | 21 | Good |
| Wall PLC | 34.6% | 247 alerts | 1 | 19 | Warning |
| Ramos Group | 31.3% | 247 alerts | 1 | 17 | Warning |
| Hahn Group | 28.0% | 247 alerts | 1 | 16 | Critical |
| Anderson Group | 24.7% | 247 alerts | 1 | 14 | Good |
Lewis LLC leads across most metrics in this analysis. Hahn Group shows the weakest performance and should be flagged for a dedicated review. The gap between top and bottom performers suggests an opportunity to standardize processes across the portfolio.
EVALUATE
SUMMARIZECOLUMNS(
BI_Datto_Rmm_Alerts[company_name],
"Top 50 Devices", COUNTROWS(BI_Datto_Rmm_Alerts),
"Worst Device", CALCULATE(COUNTROWS(BI_Datto_Rmm_Alerts), BI_Datto_Rmm_Alerts[status] = "Active")
)
ORDER BY [Top 50 Devices] DESCHow top alert generators has evolved over the past three quarters.
| Quarter | Primary Metric | Issues | Coverage | Change |
|---|---|---|---|---|
| Q3 2025 | 81.8% | 412 | 78.4% | Baseline |
| Q4 2025 | 84.2% | 387 | 82.1% | +2.4% |
| Q1 2026 | 87.4% | 342 | 85.7% | +3.2% |
The portfolio shows steady improvement over three quarters, with the primary metric increasing from 81.8% to 87.4%. This 5.6 percentage point gain reflects ongoing optimization efforts. To maintain this trajectory, continue the current remediation cadence and expand coverage to newly onboarded clients.
EVALUATE
SUMMARIZECOLUMNS(
BI_Datto_Rmm_Alerts[snapshot_month],
"Top 50 Devices", COUNTROWS(BI_Datto_Rmm_Alerts),
"Rate", DIVIDE(CALCULATE(COUNTROWS(BI_Datto_Rmm_Alerts), BI_Datto_Rmm_Alerts[is_successful] = TRUE()), COUNTROWS(BI_Datto_Rmm_Alerts))
)
ORDER BY BI_Datto_Rmm_Alerts[snapshot_month] ASCThe risk matrix shows that most entities fall in the low-risk category, but the high-risk group demands immediate attention. The moderate-risk group shows a declining trend that could escalate without intervention.
| Category | Items | Primary | Secondary | Status |
|---|---|---|---|---|
| Category A | 234 | 94.2% | 14 | Healthy |
| Category B | 187 | 89.3% | 20 | Review |
| Category C | 156 | 91.7% | 13 | Healthy |
| Category D | 98 | 86.7% | 13 | Review |
| Category E | 67 | 82.1% | 12 | At Risk |
| Category F | 45 | 95.6% | 2 | Healthy |
The detailed breakdown shows clear performance differences. The bottom two categories require targeted action to improve overall portfolio health.
Overall portfolio health is strong at 92.4%, but the 87.3% coverage rate suggests that roughly 1 in 8 entities is not fully monitored. The 23 open action items represent a manageable backlog if addressed within 2 weeks.
The gap between top and bottom performers is wider than expected. The bottom 20% scores more than 25 percentage points below the portfolio average, indicating structural issues that require targeted intervention.
Entities in the moderate risk category show a declining trend over the past quarter. Without intervention, 3-4 of these entities may shift to the high-risk category within 60 days.
The top 30% of the portfolio maintains stable performance above target, indicating current best practices are effective and can serve as a model for the rest.
1. Conduct a targeted review of all high-risk entities within 2 weeks. Document the root cause for each entity and create a remediation plan with clear deadlines and accountable owners.
2. Implement automated monitoring for the moderate-risk group. Set thresholds that trigger an alert when performance drops 5 percentage points below target, enabling early intervention before entities slip into high risk.
3. Schedule this report monthly as part of the QBR process. Use the trend data to verify that improvement initiatives are delivering measurable results across multiple quarters.
Top 50 Devices tracks the key performance indicator for top alert generators. It is calculated based on data from Datto RMM and refreshed daily.
Data syncs every 24 hours from Datto RMM. The report reflects the most recent complete data set.
Schedule a dedicated review for any client falling below the portfolio average. Create an action plan with specific remediation steps and follow up within 2 weeks.
Yes. This report is designed to be QBR-ready. Export the key metrics and trend data to include in your quarterly business review slide deck.
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