Methods for evaluating the efficiency of information processing in call centers

Feliks Kasatkin¹, Sergey Makarenko^2,3

¹Medical Information and Analytical Center of the Zaporozhye region.
²Saint Petersburg Electrotechnical University 'LETI'.
³Financial University under the Government of the Russian Federation.

DOI 10.24412/2410-9916-2026-2-173-196

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Abstract

Problem statement. In call centers there is an objective contradiction between the need to improve the quality of service and the desire to minimize costs. The lack of a scientifically based efficiency criterion aggregating the quality of information processing in the Central Bank and the resource consumption of this processing does not allow us to formalize the optimization task in conditions when obtaining a true assessment of the quality of information processing in the Central Bank from customers is difficult, and the relationship between the customer and the provider of information processing services in the Central Bank is a non-zero sum game. The purpose of the work is to develop a scientifically based methodology for evaluating the effectiveness of information processing in a data center, in the form of a value function that integrates the quality and resource consumption of information processing in a data center, as well as to determine the criterion of quasi-optimality of information processing in a data center, to assess the degree of proximity of the quality of information processing in a data center to optimal without excessive resource costs for a rigorous solution of the optimization problem. Novelty: For the first time, it is proposed to use the value function as a criterion for the effectiveness of information processing in a data center, aggregating the common quality indicator (QQ) of information processing in a data center and savings on the unit price of information processing services with the achieved quality level. The type of functional dependence of the price of a unit of service on the defense industry is scientifically substantiated, and a quantitative criterion for the quasi-optimality of the achieved value of the defense industry in a non-strict solution of the optimization problem is introduced. Result: A methodology has been developed for calculating the efficiency of information processing in a data center in the form of a value function for equal and unequal importance of the quality and resource consumption of information processing in a data center from the point of view of a decision maker. It is shown that within the boundaries of the study, a linear dependence of the price of a unit of information processing service in the data center on the achieved value of the defense industry is necessary and sufficient. The optimal value of the defense industry is determined as a function of the specific weights (significance) of the quality and resource consumption of information processing in the data center. A quasi-optimality criterion has been developed for non-strict optimization of the quality of information processing in the data center. Practical significance: The developed methodology allows the customer of data center services, without additional costs, to receive feedback from customers and to strictly solve the problem of optimizing the quality of information processing, solely through the economic stimulation of the supplier, to ensure a quasi-optimal value of the quality of information processing in the data center. The proposed approach is universal for various scales of measurement of private quality assessments and methods of their scalarization, and is also applicable in other areas where the cost of a service depends on its quality (education, healthcare, administrative management, etc.).

Key words

call centers, quality of information processing in call centers, efficiency, value function, quasi-optimality, optimization, integral quality criterion.

Reference for citation

Kasatkin F. Yu., Makarenko S. I. Methods for evaluating the efficiency of information processing in call centers. Systems of Control, Communication and Security, 2026, no. 2, pp. 173-196. DOI: 10.24412/2410-9916-2026-2-173-196 (in Russian).

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