Abstract

The last twenty years of computer integration significantly changed the process of service in a call center service systems. Basic building modules of classical call centers – a switching system and a group of humans agents – was extended with other special modules such as skills-based routing module, automatic call distribution module, interactive voice response module and others to minimize the customer waiting time and wage costs. A calling customer of a modern call center is served in the first stage by the interactive voice response module without any human interaction. If the customer requirements are not satisfied in the first stage, the service continues to the second stage realized by the group of human agents. The service time of second stage – the average handle time – is divided into a conversation time and wrap-up time. During the conversation time, the agent answers customer questions and collects its requirements and during the wrap-up time (administrative time) the agent completes the task without any customer interaction. The analytical model presented in this contribution is solved under the condition of statistical equilibrium and takes into account the interactive voice response module service time, the conversation time and the wrap-up time.

Highlights

  • The proposed analytical model belongs to the category of Markovian models which means that the flow of incoming calls is described by homogeneous Poisson pro

  • The mean number of calls E [XT ] in call center is equal to the sum of mean values of calls in interactive voice response (IVR) module E [XI ], calls in queue E [XQ] and active conversations with agents E [XC ]

  • In Tab. 1 is a short summary of results for call center with N = 100 trunk lines and S = 70 agents

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Summary

Introduction

The presented model supposes that these calls have completed its service and will no longer interact with the call center. The third phase of service – the conversation with an agent – is represented by i.i.d. exponential random variables with mean service rate μ and CDF e−μt t tC. Once a customer completes its conversation with the assigned agent, the trunk line is released and the service continues to the last phase – the after call work. In this phase, the agent completes the tasks related to the call. Which is as well represented by an i.i.d. exponential random variable with mean rate α and CDF (i+1)pθ i+1,j-1,k min(j+1,S-k+1)μ λ (i+1)(1-p)θ i,j+1,k-1 i+1,j,k e−αt t tA.

Analytical Model
System Parameters
Numerical Results
Influence of Wrap-Up Time
Conclusion
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