This report crosses HiBob employee data (team structure, reporting lines, span of control) with Datto Backup telemetry (backup job success rates per client) to reveal how backup monitoring workload is distributed. Two sources, one question: is your backup oversight spread evenly, or are a few engineers carrying all the weight?
This report crosses HiBob employee data (team structure, reporting lines, span of control) with Datto Backup telemetry (backup job success rates per client) to reveal how backup monitoring workload is distributed. Two sources, one question: is your backup oversight spread evenly, or are a few engineers carrying all the weight?
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 MSP owners monitoring backup compliance
How often: Daily for operations, weekly for management review, monthly for client reporting
This report crosses HiBob employee data (team structure, reporting lines, span of control) with Datto Backup telemetry (backup job success rates per client) to reveal how backup monitoring workload is distributed. Two sources, one question: is your backup oversight spread evenly, or are a few engineers carrying all the weight?
Total Employees =
COUNTROWS(
FILTER(
BI_HiBob_Employees,
BI_HiBob_Employees[team] IN { "Infrastructure", "Service Desk", "Cloud Ops", "Security" }
)
)| Engineer | Team | Clients Assigned | Backup Success % | Status |
|---|---|---|---|---|
| Lars van Dijk | Infrastructure | 14 | 87.2% | Overloaded |
| Sophie Bakker | Infrastructure | 11 | 89.5% | High |
| Tom Hendriks | Cloud Ops | 9 | 92.1% | High |
| Anna de Vries | Service Desk | 6 | 94.8% | Normal |
| Daan Jansen | Cloud Ops | 5 | 96.3% | Normal |
| Eva Mulder | Security | 4 | 97.1% | Normal |
| Mark Visser | Service Desk | 3 | 93.6% | Normal |
| Roos de Groot | Infrastructure | 2 | 98.4% | Light |
The top two engineers - Lars van Dijk and Sophie Bakker - together own 25 of the 54 assigned client backups (46%). Their backup success rates sit below the team average, which tracks with what you would expect when someone is stretched across too many accounts. Engineers with 6 or fewer clients consistently hit above 93% success.
Clients Per Engineer =
COUNTROWS(
SUMMARIZE(
BI_Datto_Backup_Jobs,
BI_Datto_Backup_Jobs[client_name]
)
)There is a clear inverse pattern between client count and success rate. Engineers managing more than 8 clients fall below the 91.3% team average. The data suggests a practical ceiling of roughly 7 clients per engineer before backup quality starts to degrade.
Avg Success Rate =
DIVIDE(
COUNTROWS(
FILTER(
BI_Datto_Backup_Jobs,
BI_Datto_Backup_Jobs[backup_status] = "Success"
)
),
COUNTROWS( BI_Datto_Backup_Jobs ),
0
)| Client | Last Backup | Success Rate | Risk |
|---|---|---|---|
| Brouwer & Zonen BV | 2026-03-28 | 72.4% | High |
| Technova Solutions | 2026-04-01 | 81.6% | Medium |
| Van Helden Logistics | 2026-03-30 | 84.3% | Medium |
| Kuiper Retail Group | 2026-04-02 | 86.1% | Medium |
| De Jong Architecten | 2026-04-03 | 90.2% | Low |
| Staal & Partners | 2026-04-04 | 91.8% | Low |
| Noord-West ICT | 2026-04-05 | 93.0% | Low |
Seven clients have no assigned backup engineer in HiBob. These are the blind spots: nobody is accountable for their backup health. Brouwer & Zonen BV stands out with a 72.4% success rate and a last backup that is over a week old. Without an owner, these issues go unnoticed until a client calls in a panic.
| Team | Engineers | Clients Covered | Avg Clients/Engineer | Avg Success % |
|---|---|---|---|---|
| Infrastructure | 8 | 27 | 3.4 | 90.2% |
| Cloud Ops | 6 | 14 | 2.3 | 93.8% |
| Service Desk | 7 | 9 | 1.3 | 94.2% |
| Security | 3 | 4 | 1.3 | 97.1% |
Infrastructure carries the bulk of the backup workload - 27 clients across 8 engineers. But the distribution within that team is skewed: Lars and Sophie own 25 of those 27 clients between them, leaving 6 Infrastructure engineers with barely any backup responsibility. Cloud Ops is more balanced, while Service Desk and Security carry lighter loads.
Just 26% of engineers (those assigned 8+ clients) are responsible for 42% of all client backups. That concentration creates a single point of failure. When one of these engineers takes a sick day or goes on holiday, dozens of backups lose their only watchdog. The 91.3% average success rate masks the gap between lightly loaded engineers (96%+) and overloaded ones (below 90%).
Lars van Dijk (14 clients) and Sophie Bakker (11 clients) together own nearly half of all monitored backups. Their success rates are the lowest on the team, sitting 4 - 7 points below the average. This is a capacity problem, not a skill problem.
These clients exist in Datto but have no matching engineer assignment in HiBob. One of them - Brouwer & Zonen BV - has a 72.4% success rate and has not had a successful backup in over a week. Without an owner, nobody is watching.
The data shows a clear threshold: once an engineer stays below 7 assigned clients, backup success rates consistently land above 93%. This gives you a concrete target for rebalancing.
1. Cap backup client assignments at 7 per engineer. Redistribute clients from Lars and Sophie to underutilized engineers on the Infrastructure team. Six Infrastructure engineers currently own 2 or fewer clients each - there is room to absorb the overflow without hiring.
2. Assign owners to all 7 unassigned clients within 5 business days. Start with Brouwer & Zonen BV given its low success rate. Update HiBob records so the assignment is visible in both HR and operational dashboards. Make unassigned-client count a standing metric in your weekly service review.
3. Build a rotation schedule for backup oversight. Single-owner assignments create holiday and sick-day blind spots. Pair each primary engineer with a secondary backup contact. This does not double the workload - it adds a safety net that catches failures when the primary is unavailable.
Workload is measured by counting the distinct clients in BI_Datto_Backup_Jobs that are linked to each engineer via BI_HiBob_Employees. Each unique client counts as one unit of workload, regardless of how many backup jobs that client generates per day.
A client appears in BI_Datto_Backup_Jobs and BI_Autotask_Companies but has no matching engineer assignment in BI_HiBob_Employees. This typically happens when a new client is onboarded in Datto before HiBob records are updated, or when an engineer leaves and their clients are not reassigned.
When an engineer monitors more clients, failed backups take longer to investigate and fix. Alerts pile up, response times increase, and recurring failures go unresolved for days instead of hours. The correlation is strongest above 8 assigned clients, where success rates drop below the team average.
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