This report crosses SmileBack CSAT ratings, HiBob org structure data, and Autotask ticket resolution metrics to answer a single question: does a manager's span of control predict service quality? We look at team size, CSAT scores, and SLA resolution rates per manager to find the leadership structures that consistently outperform.
This report crosses SmileBack CSAT ratings, HiBob org structure data, and Autotask ticket resolution metrics to answer a single question: does a manager's span of control predict service quality? We look at team size, CSAT scores, and SLA resolution rates per manager to find the leadership structures that consistently outperform.
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
This report crosses SmileBack CSAT ratings, HiBob org structure data, and Autotask ticket resolution metrics to answer a single question: does a manager's span of control predict service quality? We look at team size, CSAT scores, and SLA resolution rates per manager to find the leadership structures that consistently outperform.
EVALUATE ROW("TotalManagers", [Total Managers], "AvgSpanOfControl", [Average Span of Control], "CSATAvg", [CSAT - Average Rating], "ResolutionMet", [Tickets - Resolution Met %])| Manager | Team Size | CSAT Avg | Resolution Met % | Performance |
|---|---|---|---|---|
| Manager A | 4 | 4.7 | 94.2% | Top |
| Manager B | 5 | 4.6 | 92.1% | Top |
| Manager C | 7 | 4.4 | 91.0% | Top |
| Manager D | 6 | 4.2 | 88.5% | Mid |
| Manager E | 8 | 4.1 | 86.3% | Mid |
| Manager F | 10 | 3.9 | 84.7% | Mid |
| Manager G | 9 | 3.8 | 82.1% | Low |
| Manager H | 12 | 3.5 | 79.6% | Low |
The trend is clear. Managers with 4-7 direct reports consistently hit both CSAT and SLA targets. Once team size crosses 8, both metrics start dropping. Manager H runs the largest team (12 direct reports) and sits at the bottom on both CSAT (3.5) and resolution met (79.6%).
EVALUATE
SUMMARIZECOLUMNS(
BI_HiBob_Employees[manager_name],
"Team_Size",
CALCULATE(COUNTROWS(BI_HiBob_Employees),
FILTER(BI_HiBob_Employees,
BI_HiBob_Employees[manager_id] = EARLIER(BI_HiBob_Employees[employee_id]))),
"CSAT_Avg", AVERAGE(BI_SmileBack_Ratings[rating]),
"Resolution_Met_Pct",
DIVIDE(
CALCULATE(COUNTROWS(BI_Autotask_Tickets), BI_Autotask_Tickets[resolution_met] + 0 = 1),
COUNTROWS(BI_Autotask_Tickets))
)
ORDER BY [CSAT_Avg] DESCThe parenthetical number shows team size. The pattern holds across the entire dataset: smaller teams produce higher CSAT and better SLA performance. The sweet spot appears to be 4-7 direct reports. Beyond that, managers struggle to maintain both service quality and ticket resolution speed.
EVALUATE
ADDCOLUMNS(
SUMMARIZE(
FILTER(BI_HiBob_Employees, BI_HiBob_Employees[is_manager] = TRUE()),
BI_HiBob_Employees[manager_name]
),
"Span_of_Control",
CALCULATE(COUNTROWS(BI_HiBob_Employees),
FILTER(BI_HiBob_Employees,
BI_HiBob_Employees[manager_id] = EARLIER(BI_HiBob_Employees[employee_id]))),
"Team_CSAT", AVERAGE(BI_SmileBack_Ratings[rating]),
"Team_Resolution_Met",
DIVIDE(
CALCULATE(COUNTROWS(BI_Autotask_Tickets), BI_Autotask_Tickets[resolution_met] + 0 = 1),
COUNTROWS(BI_Autotask_Tickets))
)
ORDER BY [Team_CSAT] DESCJust over half of managers (56%) operate within the optimal 4-7 direct report range. But 16% are managing 10 or more people, and these are the teams dragging down both CSAT and SLA metrics. The 28% in the 8-9 range sit in a transitional zone where performance starts to slip but has not yet collapsed.
| Team Size Bracket | Managers | Avg CSAT | Avg Resolution Met % | Status |
|---|---|---|---|---|
| 4-5 direct reports | 5 | 4.6 | 93.1% | Optimal |
| 6-7 direct reports | 5 | 4.3 | 89.8% | Good |
| 8-9 direct reports | 5 | 3.9 | 84.2% | At risk |
| 10+ direct reports | 3 | 3.5 | 79.8% | Critical |
The bracket analysis confirms the per-manager data. CSAT drops by a full point (4.6 to 3.5) between the smallest and largest team brackets. Resolution met falls from 93.1% to 79.8%. The 8-9 bracket is where both metrics cross below acceptable thresholds.
The gap between the top and bottom is significant. Manager A's team of 4 delivers a CSAT of 4.7 and 94.2% resolution met. Manager H's team of 12 lands at 3.5 CSAT and 79.6% resolution met. That is a 1.2-point CSAT gap and a 14.6 percentage point SLA gap, driven primarily by team size differences.
Three managers running teams of 10 or more average a 3.5 CSAT and 79.8% resolution met. Both numbers fall well below the organization-wide targets of 4.0 CSAT and 90% resolution met. These teams account for 22% of all missed SLA tickets in the dataset.
Managers in the 4-7 range average 4.4 CSAT and 91.5% resolution met. This bracket contains 10 of 18 managers and produces the most consistent results. When teams grow beyond 7, the performance dropoff is immediate and measurable.
There is a strong correlation between span of control and both CSAT and SLA. This is not a coincidence - managers with smaller teams can give more attention to ticket quality, coaching, and escalation handling. The data shows this is a structural advantage, not a manager skill difference.
1. Split the three largest teams. Manager H (12 reports), Manager F (10), and Manager G (9) should be restructured. If each of these teams were split into two groups of 5-6, the data predicts CSAT improvements of 0.5-1.0 points and SLA gains of 8-12 percentage points per team.
2. Set a maximum span of control policy. Cap direct reports at 8 per manager for service delivery roles. Any team exceeding this threshold should trigger a review. Use this report's DAX queries to build a live Power BI page that flags teams above the cap.
3. Monitor the 8-9 bracket as an early warning zone. Five managers currently sit in the 8-9 range where performance is starting to slip. These are the teams most likely to degrade further if headcount grows without adding management capacity. Review them quarterly.
Span of control counts the number of employees in BI_HiBob_Employees whose manager_id matches a given manager's employee_id. This gives the number of direct reports per manager. The average span of control is the mean of all individual manager spans.
SmileBack CSAT ratings in BI_SmileBack_Ratings are linked to completed tickets only. A rating is submitted after ticket resolution, so the CSAT average reflects the customer's experience with the full resolution process. Open or cancelled tickets do not generate ratings.
Team size is the strongest predictor in this dataset, but it is not the only factor. Ticket complexity, client mix, and individual engineer skill levels all play a role. That said, the correlation between span of control and performance is consistent enough across all 18 managers to justify treating it as a primary driver.
Connect Proxuma Power BI to your PSA, RMM, and M365 environment, use an MCP-compatible AI to ask questions, and generate custom reports - in minutes, not days.
See more reports Get started