Introduction
Welcome, readers, to our article on the revolutionary Erlang model in the call center industry. Call centers are a critical component of many businesses, providing customer service, technical support, and sales assistance. But, with a high volume of calls and limited resources, call centers can struggle to operate efficiently. This is where the Erlang model comes in. In this article, we will explore the history, benefits, and applications of the Erlang model in call centers, and how it can help improve operations and enhance customer experience.
Before we dive deeper into this topic, let’s take a moment to understand what the Erlang model is all about. The Erlang model is a mathematical equation that helps call centers determine the number of agents required to handle incoming calls efficiently. The model takes into account several factors, including call volume, average handling time, and service level goals, to arrive at the optimal number of agents required to handle calls. With the Erlang model, call centers can optimize their workforce and deliver better results.
Nowadays, most call centers rely on advanced technologies to manage their operations, including intelligent call routing, interactive voice response, and workforce management software. However, the Erlang model remains a cornerstone of call center operations, helping businesses manage their resources and optimize their staffing levels. Let’s explore in detail what the Erlang model is and how it works.
What is the Erlang Model?
The Erlang model is a mathematical formula developed by the Danish mathematician, A.K. Erlang, in the early 1900s. Erlang was working in the Danish Telephone Company at the time, and he developed this model to help determine the number of telephone trunks required to handle incoming calls effectively. Later, this model was adapted for call centers to determine the optimal workforce required to handle incoming calls with a given service level.
The Erlang model is based on the principle of queuing theory, which studies the behavior of waiting lines or queues. It takes into account different parameters, including call volume, average handling time, and service level goals to arrive at the optimal number of agents required to handle calls. The model provides a mathematical representation of how incoming calls are handled in a call center and helps businesses manage their resources more efficiently.
Benefits of the Erlang Model
The Erlang model has several benefits for call centers, including:
- Increased efficiency: By determining the optimal number of agents required to handle calls, call centers can improve their efficiency and reduce wait times for customers.
- Optimized staffing levels: The Erlang model helps call centers manage their staff more effectively, ensuring that they have the right number of agents during peak and off-peak periods.
- Improved customer satisfaction: Shorter wait times and better service levels lead to increased customer satisfaction and loyalty.
- Cost-effective: By optimizing staffing levels, call centers can reduce their costs and operate more efficiently.
How does the Erlang Model Work?
The Erlang model takes into account four primary factors: call volume, average handling time, service level goals, and shrinkage. Let’s explore each of these factors in more detail:
Call Volume
The call volume is the number of incoming calls that a call center receives during a given period, usually measured in calls per hour or day. The Erlang model takes into account the historical data on call volumes to arrive at an estimate for future call volumes.
Average Handling Time
The average handling time is the time taken by an agent to handle a call, including the conversation time, hold time, and wrap-up time. The Erlang model considers the average handling time to determine the time an agent spends handling calls during a given period.
Service Level Goals
The service level goal is the target time within which a call center aims to answer incoming calls. For example, a call center may have a service level goal of answering 80% of calls within 20 seconds. The Erlang model factors in the service level goals to determine the number of agents required to meet these goals.
Shrinkage
Shrinkage is the time that agents are unavailable to handle calls due to reasons like absenteeism, training, meetings, and breaks. The Erlang model considers shrinkage to determine the effective number of agents available to handle incoming calls.
Erlang Model Table
| Parameters | Formula |
|---|---|
| Offered Traffic (A) | Call Volume / Service Level Goal |
| Erlang Traffic (E) | Average Handling Time * Offered Traffic |
| Number of Lines (C) | E / Service Level Goal |
| Agents Required (N) | C * (1 + Shrinkage) |
FAQs
Q1: What is queuing theory, and how does it relate to the Erlang model?
A1: Queuing theory is a branch of mathematics that studies the behavior of waiting lines or queues. The Erlang model is based on queuing theory, and it provides a mathematical representation of how call centers handle incoming calls and manage their resources.
Q2: Can the Erlang model be used for inbound and outbound call centers?
A2: Yes, the Erlang model can be used for both inbound and outbound call centers. For outbound call centers, the model helps determine the number of agents required to meet the desired call volume and service level goals.
Q3: How often should call centers use the Erlang model to optimize their workforce?
A3: Call centers should use the Erlang model regularly to optimize their workforce and ensure that they have the right number of agents at all times. The frequency of use depends on call volume and may vary from daily to weekly or monthly.
Q4: Can the Erlang model be used for non-call center operations?
A4: Yes, the Erlang model can be adapted for other operations that involve queuing or waiting lines, such as healthcare, transportation, and banking.
Q5: How can call centers measure their service level goals?
A5: Call centers can measure their service level goals by calculating the percentage of calls answered within a specified time frame. For example, a service level goal of 80% within 20 seconds means that the call center aims to answer 80% of calls within 20 seconds.
Q6: How does shrinkage affect call center operations?
A6: Shrinkage is the time that agents are unavailable to handle calls due to various reasons. Shrinkage affects call center operations by reducing the effective number of agents available to handle calls, which can impact service levels and customer satisfaction.
Q7: What are some other factors that call centers should consider when optimizing their workforce?
A7: Call centers should also consider factors like call types, skill levels, and scheduling preferences when optimizing their workforce. These factors can impact call center performance and should be taken into account along with the Erlang model.
Conclusion
In conclusion, the Erlang model is a powerful tool for call centers to optimize their workforce and manage their resources effectively. By taking into account various factors like call volume, average handling time, and service level goals, call centers can arrive at the optimal number of agents required to handle calls efficiently. The Erlang model has several benefits, including increased efficiency, optimized staffing levels, improved customer satisfaction, and cost-effectiveness.
If you are a call center manager, we highly recommend using the Erlang model to enhance your operations and improve customer experience. With the right technology and tools, you can automate the process of determining the optimal workforce and focus on delivering excellent service to your customers.
Thank you for reading this article on the Erlang model. We hope that you found it informative and useful. Please feel free to share your thoughts and feedback with us in the comments section below.
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