Erlang C is the queueing formula most contact centers use to work out how many agents a queue needs. Given the work arriving and the handle time, it gives the probability a caller waits, and from that the service level and the average wait for any number of agents.
A. K. Erlang, a Danish engineer at the Copenhagen Telephone Company, published the model in 1917 to size telephone exchanges.
Contacts per interval × AHT in seconds ÷ (interval minutes × 60)In Erlangs: the agents busy every moment if contacts arrived evenly.As published in the Staffing Requirement Calculator method, version 1.2.Erlang B by recurrence, B(n) = A × B(n−1) ÷ (n + A × B(n−1)); then C = B ÷ (1 − (A ÷ n) × (1 − B))The probability a contact waits. The recurrence stays finite at any size.As published in the Staffing Requirement Calculator method, version 1.2.1 − C × e^(−(agents − load) × threshold seconds ÷ AHT)The share answered within the threshold.As published in the Staffing Requirement Calculator method, version 1.2.C × AHT ÷ (agents − load)The average wait across all calls.As published in the Schedule Adherence Impact Calculator method, version 1.1.A load of 10 Erlangs, for example 200 calls an hour at 180 seconds each, with a target of answering within 20 seconds. Each row adds one agent. Computed by the same engine the Schedule Adherence tool runs.
| Agents | Chance a caller waits | Answered in 20 s | Average wait | Occupancy |
|---|---|---|---|---|
| 11 | 0.6821 | 39.0% | 122.8 s | 90.9% |
| 12 | 0.4494 | 64.0% | 40.4 s | 83.3% |
| 13 | 0.2853 | 79.6% | 17.1 s | 76.9% |
| 14 | 0.1741 | 88.8% | 7.8 s | 71.4% |
| 15 | 0.1020 | 94.1% | 3.7 s | 66.7% |
| 16 | 0.0573 | 97.1% | 1.7 s | 62.5% |
Adding agents brings the wait down fast at first and then slowly, while occupancy falls with every agent added. That trade is the staffing decision.
Our test suite computes each case with the shipped engine and fails if any answer differs.