Track user additions, removals, and license modifications across all managed tenants in the last 30 days.
Track user additions, removals, and license modifications across all managed tenants in the last 30 days.
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
Track user additions, removals, and license modifications across all managed tenants in the last 30 days.
EVALUATE
ROW(
"UsersAdded", CALCULATE(COUNTROWS(BI_Microsoft_UserChanges), BI_Microsoft_UserChanges[change_type] = "Added"),
"UsersRemoved", CALCULATE(COUNTROWS(BI_Microsoft_UserChanges), BI_Microsoft_UserChanges[change_type] = "Removed"),
"NetChange", CALCULATE(COUNTROWS(BI_Microsoft_UserChanges), BI_Microsoft_UserChanges[change_type] = "Added") - CALCULATE(COUNTROWS(BI_Microsoft_UserChanges), BI_Microsoft_UserChanges[change_type] = "Removed")
)Tenants that added the most users in the last 30 days.
| Tenant | Users Added | Users Removed | Net Change | Current Total | Growth % |
|---|---|---|---|---|---|
| Contoso Ltd | 68 | 12 | +56 | 542 | +11.5% |
| Adventure Works | 52 | 8 | +44 | 318 | +16.1% |
| Fabrikam Inc | 44 | 15 | +29 | 284 | +11.4% |
| Woodgrove Bank | 38 | 5 | +33 | 196 | +20.2% |
| Litware Inc | 31 | 3 | +28 | 158 | +21.5% |
| Tailspin Toys | 27 | 22 | +5 | 213 | +2.4% |
Contoso Ltd leads in absolute additions with 68 new users, but Litware Inc and Woodgrove Bank show the strongest relative growth at 21.5% and 20.2% respectively. Tailspin Toys added 27 users but also removed 22, resulting in just 2.4% net growth. This high churn pattern at Tailspin deserves a check-in call.
EVALUATE
SUMMARIZECOLUMNS(
BI_Microsoft_UserChanges[tenant_name],
"UsersAdded", CALCULATE(COUNTROWS(BI_Microsoft_UserChanges), BI_Microsoft_UserChanges[change_type] = "Added"),
"UsersRemoved", CALCULATE(COUNTROWS(BI_Microsoft_UserChanges), BI_Microsoft_UserChanges[change_type] = "Removed")
)
ORDER BY [UsersAdded] DESCTenants with the most user removals that may signal churn risk.
| Tenant | Users Removed | Removal Rate | Reason (Top) | Risk Level |
|---|---|---|---|---|
| Datum Corp | 28 | 14.2% | Departmental restructure | High |
| Tailspin Toys | 22 | 10.3% | Contract renegotiation | Medium |
| Northwind Traders | 18 | 8.7% | Seasonal workforce | Low |
| Proseware Inc | 15 | 6.9% | Unknown | High |
| Fabrikam Inc | 15 | 5.3% | Office closure | Medium |
Datum Corp removed 28 users (14.2% of their base), the highest removal rate across the portfolio. While some removals at Northwind Traders are seasonal and expected, the 15 unexplained removals at Proseware Inc should be flagged for immediate follow-up. Account managers should verify whether these represent genuine downsizing or a migration to another provider.
EVALUATE
SUMMARIZECOLUMNS(
BI_Microsoft_UserChanges[tenant_name],
FILTER(BI_Microsoft_UserChanges, BI_Microsoft_UserChanges[change_type] = "Removed"),
"UsersRemoved", COUNTROWS(BI_Microsoft_UserChanges),
"RemovalRate", DIVIDE(COUNTROWS(BI_Microsoft_UserChanges), RELATED(BI_Microsoft_Tenants[total_users]))
)
ORDER BY [UsersRemoved] DESCThe 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.
Any addition or removal of a licensed user within a tenant. License SKU changes (e.g., upgrading from E3 to E5) are tracked separately.
User changes sync within 24 hours of the actual change in the Microsoft 365 tenant.
Not necessarily. Some industries have predictable seasonal patterns. Flag tenants with unexpected removal spikes for follow-up.
Compare additions against removals. If a tenant adds 20 and removes 18, they are likely optimizing rather than growing.
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