For years, MSPs have relied on simple staffing shortcuts like “one technician per 70–100 users.” It’s easy to remember, easy to explain, and completely disconnected from how help desks actually work.
User count feels like a clean metric. The problem is - it tells you almost nothing about workload.
Two MSPs with the same number of users can experience wildly different ticket volumes, issue complexity, and resolution times. One team stays ahead. The other is constantly underwater. The difference isn’t effort or talent—it’s how staffing decisions were made.
User count ignores the realities that actually consume technician time:
How many tickets arrive each week
How long those tickets take to resolve
How much work happens outside of tickets (projects, documentation, automation, training)
When staffing is tied to users instead of workload, understaffing creeps in quietly. Tickets start aging. Senior engineers get pulled into Tier 1 work. Projects slow down. SLAs stretch. Eventually, the whole desk feels reactive and chaotic.
Most MSPs chalk this up to “just how IT is.” It’s not. It’s a math problem.
The strongest predictor of staffing need is simple: incoming work multiplied by time to resolve it.
Ticket volume and resolution time reflect the real demand placed on your team. They account for client behavior, environment complexity, and internal maturity in a way user count never can.
This is why many MSPs feel permanently understaffed—even when their headcount looks “reasonable” on paper. The ratio never told the full story.
When staffing decisions are based on shortcuts:
Tier 3 engineers spend time on low-value issues
Projects slip and margins erode
Burnout increases and turnover becomes a risk
Growth stalls because the service desk can’t absorb it
These problems don’t show up all at once. They accumulate slowly -until the desk hits a breaking point.
If you want to stop guessing and calculate exactly how many Tier 1, Tier 2, and Tier 3 technicians your MSP actually needs, download our Right-Size Your MSP Help Desk guide. It walks you through a workload-based formula using real ticket data—not outdated ratios.