Help Desk Staffing Calculator

Calculate the number of help desk agents required to meet your service level targets using the industry-standard Erlang C formula. Enter your call volume, average handle time, and desired service level to get staffing recommendations.

Total inbound calls expected per hour
Average talk + hold + wrap-up time per call
Percentage of calls to answer within the target time
Calls should be answered within this many seconds
Time agents are unavailable (breaks, training, meetings)
Number of hours the help desk operates per day

Formulas Used

1. Traffic Intensity (Erlangs):

A = (Calls per Hour × Average Handle Time in Hours)

2. Erlang C — Probability a Call Waits P(W):

P(W) = [Aᴺ/N! × N/(N−A)] / [Σₖ₌₀ᴺ⁻¹(Aᵏ/k!) + Aᴺ/N! × N/(N−A)]

Where N = number of agents, A = traffic intensity in Erlangs. The system is only stable when N > A.

3. Service Level:

SL = 1 − P(W) × e^[−(N−A) × (Target Time / AHT)]

4. Average Speed of Answer (ASA):

ASA = P(W) × AHT / (N − A)

5. Agent Occupancy:

Occupancy = A / N × 100%

6. Staffed Agents (with Shrinkage):

Staffed Agents = ⌈Raw Agents / (1 − Shrinkage%)⌉

Assumptions & References

  • The Erlang C model assumes calls arrive following a Poisson process and service times follow an exponential distribution (M/M/N queue).
  • All callers wait indefinitely (no abandonment). For abandonment modeling, Erlang A (ERTA) would be more accurate.
  • Shrinkage accounts for time agents are scheduled but unavailable: breaks, training, meetings, coaching, and unplanned absence. Industry standard is 25–35%.
  • Occupancy above 85–90% is generally unsustainable and leads to agent burnout and degraded service quality.
  • The 80/20 rule (80% of calls answered within 20 seconds) is the most common industry service level benchmark (ICMI, HDI).
  • Log-space arithmetic is used internally to prevent numerical overflow for large call volumes or agent counts.
  • References: Erlang (1917); ICMI Call Center Management Handbook; HDI Technical Support Practices & Salary Report; Koole & Mandelbaum (2002) Queueing Models of Call Centers.

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