One agent has 90 open tickets. The agent next to them has 12. Both are in the same group, handling the same category. The imbalance isn’t intentional — it’s what happens when ticket assignment is round-robin by default and one agent is faster at closing tickets, so the system keeps feeding them more.
GLPI’s assignment rules can distribute work more evenly, but only if you configure them beyond the defaults.
How GLPI assigns tickets
By default, GLPI assigns tickets to a group, not a specific agent. The ticket appears in the group’s queue and whoever picks it up first handles it. This "pull" model works for small teams but creates problems at scale — fast agents cherry-pick easy tickets, difficult tickets sit unclaimed, and workload data becomes meaningless.
The alternative is "push" assignment — GLPI assigns each ticket to a specific technician automatically. This can be configured through business rules, with several distribution strategies.
Distribution strategies
Round-robin
Each new ticket goes to the next agent in rotation. Agent A, then B, then C, then back to A. Simple and fair in theory, but doesn’t account for ticket complexity — Agent A might get three P1 incidents while Agent B gets three password resets.
Least-busy
Assign to the agent with the fewest open tickets. This naturally balances load because agents who resolve tickets faster get freed up for the next one. GLPI doesn’t have a built-in "least busy" function, but you can achieve it with a periodic script that queries open ticket counts per agent and sets a user custom field that the assignment rule reads.
Skill-based
Different agents handle different categories. Network tickets always go to the network specialist, SAP tickets to the SAP team. This is the most common approach in practice — it’s really just category-based assignment with one agent per category instead of a group. The trade-off is that if the specialist is on vacation, their tickets queue up.
Hybrid
Route by category to a group, then within the group use a dispatcher — either a team lead who manually assigns, or a scheduled script that distributes evenly. This gives you skill-based routing at the group level and load balancing within the group.
Monitoring workload
Distribution only works if you monitor it. Build a dashboard or report that shows:
- Open tickets per agent — identifies overload before it causes burnout or SLA breaches
- Tickets resolved per agent per week — identifies capacity differences (not for ranking — for understanding where complexity concentrates)
- Average age of open tickets per agent — an agent with 30 tickets averaging 2 days is fine; 30 tickets averaging 15 days is a backlog problem
When uneven distribution is correct
Not all imbalance is a problem. A senior agent handling 20 complex P2 incidents carries more load than a junior agent handling 60 password resets. The metric that matters is effort, not count. If your team has mixed skill levels, expect and accept different ticket volumes — just make sure the effort is roughly balanced.
The goal is not equal ticket counts. It’s sustainable workload with predictable SLA delivery. GLPI gives you the data to measure both — the assignment strategy is the lever you pull to adjust.