Computing Discrete Simulations for Efficient Queuing Management of Financial Aid Services

Introduction

Managing bank queues efficiently is crucial for maintaining customer satisfaction, operational efficiency, and compliance with regulations. Nevertheless, it involves overcoming significant challenges related to demand variability, resource constraints, and the need for technological and procedural adaptations. During emergency crises such as the COVID-19 pandemic, offering robust measures for discrete simulations becomes challenging due to significant and unexpected variations in customer arrival rates. This study proposes computing discrete event simulations based on queuing theory and tests of the empirical probability distribution for each particularity to support improvements in waiting times for segments of Caixa Econômica Federal (CEF) responsible for financial aid services (Express, Tellers, and Gov-Social sectors).

Methods

The methodology involves conducting discrete event simulations (DES) using real-time data collection to accurately model customer arrival and service rates. Key parameters included the expected queue length, waiting time, and number of arrivals per unit time, based on service time, the number of servers, the number of clients, and the average waiting time per month. We apply the Kolmogorov-Smirnov test to identify the most fitting probability distributions for these rates, adjusting them as needed on each scenario.

Results

The computing simulations indicated a potential reduction in queue size by approximately 45%. Specifically, hiring at least one more employee for the Express sector in some specific production scenarios could decrease the average waiting time from 36 minutes to 17 minutes, thereby increasing the capacity to serve more customers. In extreme pandemic scenarios, six more employees are necessary to maintain reasonable service times.

Conclusions

The study's findings suggest that strategic employee allocation can significantly improve service efficiency in high-demand sectors at CEF. By implementing the recommended staffing changes, financial institutions can offer satisfactory service, enhance business profitability, and better manage the effects of the pandemic or similar public emergency contexts.