Customer Support Optimization through Waiting Line Simulation: A Financial Institution Case Study

Abstract

The financial sector is a section where customer service is essential to guarantee customer satisfaction, trust, and credibility, and to improve productivity. For this reason, the main objective of this paper was to optimize the customer service at the waiting lines. Within the methodology used, a simulation tool was designed to estimate customer service times. This simulation model had the characteristic of predicting the behavior of the system and optimizing the allocation of schedules and appropriate number of servers, without affecting the perception of the quality of service. The design contemplated the use of probabilistic models of Poisson and Erlang, as well as the waiting line models proposed by Kendall and Lee. In order to estimate the results, the Montecarlo methodology was used, which allows obtaining random numbers according to the established probabilistic distribution. The simulation system was developed in Excel and macro programmed in Visual Basic. As a result of the simulation run, it was proposed to reduce a universal full-time server on cashier 1 and place a 6-hour part-time server to service during times with higher customer demand. Finally it could be concluded that it was possible to simulate the behavior of waiting lines and the results of the simulation determined decision criteria for the correct assignment of human resources.