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Erlang Calculators

Erlang calculators are used to translate predicted workload into required staffing levels. They are an essential component of workforce scheduling and capacity planning. Next to the standard Erlang C method CCmath offers the more accurate Erlang X method and also calculators for blending, chat and skill-based routing. You can try them below or use our add-ins for Excel, Python or R.

Choosing a calculator
Erlang C
Erlang X
Erlang Blending
Erlang Chat
Multi-Skill Simulator

Which calculator should I use?

Choose the calculator that best fits your type of customer contact.

Erlang C ▼

Where customers stay in the queue until helped.

Erlang C is the standard calculator for call center staffing.

Use this if:

  • You handle incoming phone calls
  • Customers wait in the queue until helped
  • You do not have clear data on customers who hang up
Erlang X ▼

Customers have a certain patience. If they wait too long, they will abandon the call.

Erlang X is useful if people hang up when the queue is taking too long. This more accurately reflects real customer behaviour.

Use this if:

  • Customers might have patience which runs out and abandon the call
  • You have data about customers leaving the queue
  • You want a more realistic staffing result
Erlang Blending ▼

Agents are able to send out emails or make outbound calls while also taking incoming calls.

Erlang Blending enables you to plan accordingly if agents can handle incoming calls while answering outbound chats or emails.

Use this if:

  • Agents can stop answering an email to pick up a phone call
  • You want to balance service level and productivity
Erlang Chat ▼

For chat and messaging. Agents can help more than one customer at the same time.

Using our Erlang Chat model, you can decide how many chats an agent can handle in parallel.

Use this if:

  • You plan staffing for chat or messaging
  • Agents are able to handle multiple chats at once
  • You want to include chat concurrency in your planning

Erlang C

Erlang C – User Manual

The standard model for inbound call center staffing. Customers stay in the queue until an agent becomes available.

Use Erlang C when you want to calculate staffing or performance for inbound calls.

  • You handle inbound phone contacts.
  • Customers wait in the queue until they are served.
  • You want to calculate required agents, service level, ASA, or occupancy.
  • You want a clear baseline calculation for call center staffing.

Forecast
The expected number of incoming calls in the selected time period.

Average handling time
The average time needed to handle one call.

Number of agents
The number of agents available to answer calls.

Acceptable waiting time
The waiting time used for the service level calculation. For example, 80% answered within 20 seconds.

Average speed of answer
The average time customers wait before their call is answered.

Service level
The percentage of calls answered within the acceptable waiting time.

Scenario 1 – Performance based on agents
Use this when you know how many agents are available and want to calculate the expected service level, ASA, and occupancy.

Scenario 2 – Agents based on ASA
Use this when you have a target average speed of answer and want to know how many agents are needed.

Scenario 3 – Agents based on service level
Use this when you have a service level target and want to calculate the required number of agents.

Scenario 1

Know your staffing → see service level, ASA, and occupancy.

Scenario 2

Have an ASA target → find the required agents and corresponding performance measures.

Scenario 3

Have a service level target → find the required agents and corresponding performance measures.

Results

Erlang X

Erlang X – User Manual

Erlang X extends Erlang C by modelling customer patience. Customers may abandon the queue if they wait too long, so the model gives a more realistic picture of staffing needs and the resulting abandonment rate.

Use Erlang X when you handle inbound contacts and customers may abandon while waiting.

  • You have data (or a reasonable estimate) of customer patience.
  • You want a more realistic staffing result than Erlang C, which assumes infinite patience.
  • You want to compute the resulting abandonment rate – or use it as a target.

Forecast
The expected number of incoming contacts in the selected time period.

Average handling time
The average time needed to handle one contact.

Average patience
The average time a customer is willing to wait before abandoning the queue.

Redials
Percentage of customers who, after abandoning, retry later.

Number of agents
The number of agents available to answer contacts.

Acceptable waiting time
The waiting time used for the service level calculation (e.g. 80% answered within 20 seconds).

Average speed of answer / Service level / Abandonment rate
Performance metrics that can be used as either outputs (Scenario 1) or targets (Scenarios 2–4).

Scenario 1 – Performance based on agents
Know your staffing? See the resulting service level, ASA, occupancy, and abandonments.

Scenario 2 – Agents based on ASA
Set a target average speed of answer to find the required staffing and resulting performance.

Scenario 3 – Agents based on service level
Set a target service level to find the required staffing and resulting performance.

Scenario 4 – Agents based on abandonment rate
Set a target abandonment rate to find the required staffing and resulting performance.

Scenario 1

Know your staffing → see service level, ASA, occupancy, and abandonments.

Scenario 2

Have an ASA target → find the required agents and corresponding performance measures.

Scenario 3

Have a service level target → find the required agents and corresponding performance measures.

Scenario 4

Have an abandonment target → find the required agents and corresponding performance measures.

Results

Erlang Blending

Erlang Blending – User Manual

Erlang Blending models a blended environment where agents handle both inbound calls and outbound work like emails or callbacks. A configurable threshold protects inbound accessibility by reserving capacity for incoming calls.

Use Erlang Blending when agents do more than just answer inbound calls.

  • Agents can also handle outbound work (emails, outbound calls, back-office).
  • You want to balance inbound service level against outbound productivity.
  • You need to model how many agents are kept ready for inbound (the threshold).

Forecast
The expected number of inbound calls in the selected time period.

AHT inbound / AHT outbound
Average handling time for inbound contacts and outbound work, respectively.

Average patience
How long inbound customers are willing to wait before abandoning the queue.

Threshold
The number of agents kept available for inbound work. A threshold of 1 means 1 agent is always reserved to answer the next inbound call – protecting inbound accessibility while the rest of the team works on outbound.

Outbound
The outbound workload (per time period) used when finding required staffing.

Acceptable waiting time
The waiting time used for the service level calculation.

Service level / ASA / Abandonment rate / Occupancy
Performance metrics that can be either outputs (Scenario 1) or targets (Scenarios 2–5).

Scenario 1 – Performance based on agents
Know your staffing? See the resulting service level, ASA, occupancy, abandonments, and outbound capacity.

Scenario 2 – Agents based on service level
Set a target service level to find the required agents and corresponding performance.

Scenario 3 – Agents based on ASA
Set a target average speed of answer to find the required agents and corresponding performance.

Scenario 4 – Agents based on abandonment rate
Set a target abandonment rate to find the required agents and corresponding performance.

Scenario 5 – Agents based on occupancy
Set a target occupancy level to find the required agents and corresponding performance.

Scenario 1

Know your staffing → see service level, ASA, occupancy, abandonments, and outbound.

Scenario 2

Have a service level target → find the required agents and corresponding performance measures.

Scenario 3

Have an ASA target → find the required agents and corresponding performance measures.

Scenario 4

Have an abandonment target → find the required agents and corresponding performance measures.

Scenario 5

Have an occupancy target → find the required agents and corresponding performance measures.

Results

 

Erlang Chat

Erlang Chat – User Manual

Erlang Chat is for digital channels – chat and messaging – where agents handle multiple conversations in parallel. It builds chat concurrency into the staffing calculation alongside customer patience and abandonment.

Use Erlang Chat for live chat, messaging and similar digital channels.

  • Agents can handle more than one chat at the same time (concurrency).
  • You want to factor that concurrency into your staffing.
  • Customers may abandon if they wait too long.

Forecast
The expected number of incoming chats in the selected time period.

AHT
The average handling time per chat.

Parallel
The number of chats an agent can handle simultaneously. A value of 1 means one chat at a time; 2 means two in parallel; the higher the value, the fewer agents are needed for the same workload.

Average patience
How long customers are willing to wait before abandoning the chat.

Acceptable waiting time
The waiting time used for the service level calculation.

Service level / ASA / Abandonment rate / Occupancy
Performance metrics that can be either outputs (Scenario 1) or targets (Scenarios 2–5).

Scenario 1 – Performance based on agents
Know your staffing? See the resulting service level, ASA, occupancy, and abandonments.

Scenario 2 – Agents based on service level
Set a target service level to find the required agents and corresponding performance.

Scenario 3 – Agents based on ASA
Set a target average speed of answer to find the required agents and corresponding performance.

Scenario 4 – Agents based on abandonment rate
Set a target abandonment rate to find the required agents and corresponding performance.

Scenario 5 – Agents based on occupancy
Set a target occupancy level to find the required agents and corresponding performance.

Scenario 1

Know your staffing → see service level, ASA, occupancy, and abandonments.

Scenario 2

Have a service level target → find the required agents and corresponding performance measures.

Scenario 3

Have an ASA target → find the required agents and corresponding performance measures.

Scenario 4

Have an abandonment target → find the required agents and corresponding performance measures.

Scenario 5

Have an occupancy target → find the required agents and corresponding performance measures.

Results

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