Introduction
This manual gives guidance about using the free online version of CCmath's Erlang calculators to make capacity planning calculations and familiarize yourself with contact center workforce management. You will find the definition of some parameters required and understand the capabilities of Erlang calculators. Do you prefer making calculations in Excel? Please explore our new Erlang Add-in for Office 365. Start your free trial and find out the convenience of this one-of-a-kind tool!
Parameters
The required parameters for online Erlang calculators are briefly explained below. If you want to explore more workforce management terminology, visit our WFM definitions page. Please ensure that you use the correct time units while making your calculations. For any questions, see our FAQ page.
| Parameters | Definition and Requirements |
|---|---|
| Abandonments | The percentage of arbitrary customer that will abandon the queue. (0 < Abandonments < 100) |
| Acceptable Waiting Time (AWT) | The maximum allowed waiting time of customers to be considered to have a good service. The service level is defined as the percentage of customers that are served within this duration. (AWT = 20 seconds by default) |
| Average Handling Time (AHT) | The average time an agent spends on a call. (AHT > 0) |
| Average Patience | The average time a customer is willing to wait in the queue. A simple estimator for the patience is calculated by dividing the total waiting time (including the waiting times of the abandoned customers) by the number of abandonments. It is important to filter out extreme values in advance. (Patience ≥ 0) |
| Average Speed of Answer (ASA) | The average waiting time that an arbitrary customer with infinite patience in the queue. (ASA > 0) |
| Forecast | The average number of arrivals per unit of time. (Forecast ≥ 0) |
| Lines | The total number of trunk lines, consisting of: lines in use by customers in service, and lines in use by customers that wait. (Lines ≥ Agents, integer) |
| Number of Agents | The number of agents available for taking calls. (Number of agents > 0) |
| Occupancy | The percentage of time that agents are handling calls (0 < Occupancy ≤ 100) |
| Outbound Calls | The average number of outbound calls per unit of time. (Outbound calls > 0) |
| Redials | The percentage of customers that once abandon the queue but reconnect than. (0 ≤ Redials ≤ 100) |
| Service Level (SL) | The percentage of customers that waits less than acceptable waiting time. (0 < SL < 100) |
| Service Level Definition | A flag to switch between different modes of calculating the service level in Erlang X: On offered calls, answered calls, or virtual test customer |
| Threshold | The number of agents that are kept idle when there are no inbound calls before taking outbound calls into service. (0 < Threshold ≤ Agents) |
Calculators
| Erlang C | ||
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The Erlang C model is a queuing system where:
The Erlang C model is often used for single-skill call centers with only inbound calls. This model uses the following input parameters from the historical data based on three different scenarios: |
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| Scenario | Example | |
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1) Calculation of ASA, service level, and agent occupancy based on given number of agents See the example. |
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2) Calculation of the minimum number of agents required to answer calls within the given ASA See the example. |
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3) Calculation of the minimum number of agents required to satisfy the given SL See the example. |
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| Erlang X | ||
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The Erlang X model is a queueing system with the following features:
The Erlang X model gives a better estimate than the Erlang C model by involving customer behavior in the queuing system, considering patience, abandonments, and redials. In the free online version, you may use the following input parameters from the historical data based on four different scenarios: |
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| Scenario | Example | |
| Inputs | Outputs | |
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1) Calculation of ASA, SL, customer abandonment, and agent occupancy based on given number of agents See the example. |
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2) Calculation of the minimum number of agents required to answer calls within ASA See the example. |
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3) Calculation of minimum number of agents required to satisfy given SL See the example. |
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4) Calculation of minimum number of agents required to satisfy given abandonment rate See the example. |
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| Erlang Blending | ||
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The Erlang Blending model considers that agents can work on different types of calls: inbound and outbound.
This model uses the following input parameters from the historical data based on two different scenarios: |
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| Scenario | Example | |
| Inputs | Outputs | |
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1) Calculation of SL based on a given threshold See the example. |
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2) Calculation of the threshold value for agents based on SL See the example. |
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| Erlang Chat | ||
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The Erlang Chat model involves the following characteristics:
The Erlang Chat model is suitable for contact centers with agents handling chat interactions. It is essential to consider the impact of multiple parallel chats on average handling time and overall efficiency. This model uses the following input parameters from the historical data based on three different scenarios: |
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| Scenario | Example | |
| Inputs | Outputs | |
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1) Calculation of ASA and SL based on given number of agents See the example. |
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2) Calculation of the minimum number of agents required to handle chats within ASA See the example. |
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3) Calculation of the minimum number of agents required to satisfy given SL See the example. |
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| Multiple Skills | ||
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The Multiple Skills simulator can be considered as an extension of Erlang X with multiple skills-requiring calls but runs with a simulation.
Let us compare two scenarios to see that the same service level and occupancy can be achieved with fewer agents when they are multi-skilled. |
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| Scenarios | Parameters | Result of calculation |
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1) Calculation of ASA, SL, customer abandonment, and agent occupancy, when there are two types of agents: all of them are single-skilled See the example. |
Type 1 Calls:
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Type 1 Calls:
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Type 2 Calls:
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Type 2 Calls:
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2) Calculation of ASA, SL, customer abandonment, and agent occupancy, when there are two types of agents: some of them are multi-skilled See the example. |
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