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DOI: 10.15862/06INOR124 (https://doi.org/10.15862/06INOR124)

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Ganenko O.M., Gorozhanina E.I. Construction of block diagrams of a simulation model of the customer service process. Russian journal of resources, conservation and recycling. 2021; 11(1). Available at: https://resources.today/PDF/06INOR124.pdf (in Russian). DOI: 10.15862/06INOR124

Construction of block diagrams of a simulation model of the customer service process

Ganenko Olga Mikhailovna
Povolzhskiy State University of Telecommunications and Informatics, Samara, Russia
E-mail: zhdanova63@gmail.com

Gorozhanina Evgeniya Ivanovna
Povolzhskiy State University of Telecommunications and Informatics, Samara, Russia
E-mail: zhdanova63@gmail.com

Abstract. The article, which is part of the author’s dissertation research, is devoted to the construction of a simulation model, namely a discrete-event model of the customer service process «as is» and «as will be».

The introduction substantiates the relevance of the research topic, highlighting the object and subject of the study. A hierarchical structure of the system of quality indicators for infocommunication services has been constructed. There are 4 levels of indicators, at each level quality indicators are highlighted, namely: service speed indicators (average service time for a technical fault, average response time for reference services); satisfaction indicators (percentage of calls regarding technical aspects of service, percentage of calls regarding organizational aspects of service) and others. A hypothesis has been put forward about a change in the state of the service process after the introduction of a functional dialog agent into the process, which involves a reduction in customer service time.

To test the hypothesis about reducing customer service time, discrete-event simulation models of the process «as is» and «as will be» were built, since modeling in terms of queuing theory not only improves the understanding of existing processes in the company, but also helps to identify bottlenecks and identify areas for further optimization, which ultimately leads to increased customer satisfaction and the efficiency of the company as a whole.

Within the framework of the developed discrete-event model, the main attention is paid to two main stages: modeling the receipt of requests and modeling the processing of requests. Process optimization includes the introduction of an automated diagnostic system, namely a functional conversational agent to reduce wait time and increase request processing throughput.

Block diagrams of discrete-event simulation models of the service process were also constructed in terms of the AnyLogic environment, and the advantages of its use were highlighted. The main objects used to create discrete-event models that describe the mathematical state of the simulated system are presented.

Keywords: simulation model; discrete event modeling; simulation modeling; service process; AnyLogic modeling environment; infocommunications industry; indicator system

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