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Waiting Lines Situation at Banking Organizations


Queues represent a common occurrence that people can experience in multiple areas of life (Anderson et al., 2016). For example, people who visit banks are often faced with the problem of having to wait in lines to get help from a bank employee. Therefore, queues are highly standard at banks and other types of financial institutions, and they should be addressed with the help of appropriate management and analysis options.

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According to Onoka, Babasola, Moyo, and Ojiambo (2018), the application of queuing theory, which is a mathematical approach to waiting lines, can be applied to deal with the issue of queues at banking organizations. Using the example of Guarantee Trust Bank, the scholars considered the time that customers spend waiting in lines, the time necessary to spend on each client that is being serviced, the average cost that consumers lose when waiting in queues, as well as the average cost of each server necessary to achieve system optimization.

In the study, the researchers used the First Come First Serve (FCFS) multi-server queuing model that was used to develop a model for the queuing process. While the service rate followed the exponential distribution, the time spent waiting in lines was seen to follow a Poisson distribution. The researchers used a case study approach to analyzing queuing models through the random administration of questionnaires, interviews, as observations of participations.

Based on the results of the analysis, it could be concluded that queuing theory could offer innovative solutions at an optimal level of service. It was shown that hiring more personnel at a financial facility could enhance the capabilities of a bank to address the challenges of queues during busy times. Moreover, it was found that there was still more room for improvement at such departments as Bank cash deposit units, which also experience significant challenges with lines. Another important takeaway from the study is that software was necessary to facilitate the modeling of different banking units. These included customer care units, ATM cash withdrawal units, and others.


In day-to-day life, customers experience severe frustration when they have to wait in lines. The value of the research by Onoka et al. (2018) is associated with offering financial institutions a solution to reduce the occurrence of lines through determining how managers can address the needs of facilities and their customers. Besides, the waiting line optimization solution could be applied to other contexts, such as restaurants and telecommunication services. In the research, it was shown that the problem of queues through applying the FCFS multi-server queuing model could help institutions determine that they need to be more attentive to their staffing solutions.

Hiring more personnel could be a solution to address the challenge of long queues at many facilities. This points to the fact that organizations that deal with large volumes of clients should not save costs on personnel and their training. Having multiple servers that could interact with customers quickly and efficiently shows that queuing problems are not as complex as they may seem. Moreover, the costs that companies incur when there are customers who queue to be served have shown to be higher than the expenses necessary to hire and train new workers. It is recommended to further the research on waiting for line management and analysis due to the skewed perspective on the issue in scholarly literature.


Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., Cochran, J. L., Fry, M. J., & Ohlmann, J. W. (2016). Quantitative methods for business with CengageNOW (13th ed.). Boston, MA: Cengage Learning.

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Onoka, A., Babasola, O., Moyo, E., & Ojiambo, V. (2018). The application of queuing analysis in modeling optimal service level. International Journal of Scientific and Engineering Research, 8(1), 184-194.

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