Economies of Scal
Respond to two peers dicussion listed below . T
Waiting Line Models
Study the two cases (Link Below)in bank call center and bank tellers staffing probelms and comment on the importance of the waiting line theory then give another similar case study of the application of this theory for deeper understanding of the theory.
Waiting Line Models
(YD) Peer 1
A waiting line is also known as a queue, and the body of knowledge dealing with waiting lines is known as queueing theory (Anderson et al., 2015). A multiple-server waiting line consists of two or more servers that are assumed to be identical in terms of service capability. When there is only one server and each customer has to stand and wait for service, it can be referred to as a single-channel waiting line. The Kendall notations help identify the model for solving different queuing theory scenarios. Organizations in various sectors, such as healthcare organizations, implement queuing theory for handling emergency cases (Johnston et al., 2022).
Given scenario
Srivastava (2016) explained about mean arrival rate distribution of service rate to customers in the queue. The assumptions of waiting line theory are mentioned concerning simple queuing scenarios. The statistical code for R software had been given for calculating the number of servers needed to give service within the target time set by the bank’s management. The bank tellers need to give service (λ = 20, μ = 4), and the waiting time (W) at each server has been calculated. It is found that with nine servers (representative), the waiting time comes to 30 seconds. In the second scenario of Srivastava (2016), the bank needs to conduct operations, so the wait time is less than 30 seconds. An R code had been used (λ = 100, N = 50, μ = 20). Using the R code, it is found that 7 representatives (servers) are needed to make the waiting time less than 30 seconds so that every customer enters the bank.
Similar case study
The waiting line theory is applicable in many real-time scenarios; the real-time application of the waiting line theory at a gas filling station has been described. For every one hour, 35 vehicles enter the gas station and each vehicle needs 3 minutes for service time when using a gas filling. The number of gasoline pumps required in the station is calculated using waiting line theory to make the average waiting time less than 4 minutes. (λ = 35, μ = 20). An online calculator was used to calculate the number of servers based on the arrival rate and waiting time. The waiting time with three gasoline pumps (waiting time = 0.798 minutes, average waiting time = 3.789 minutes) and four gasoline pumps (waiting time = 0.156 minutes, average waiting time = 3.156 minutes). Since there is no significant difference between three gasoline pumps and four gasoline pumps, three gasoline pumps are suggested for the gasoline station. Every customer’s wait time is less than one-minute average time is less than 4 minutes.
Conclusion
The waiting line theory helps minimize the overall operating costs and benefits in the utilization of services at an optimal level. When the number of servers is optimal and wait time is less, it will increase customer satisfaction. The techniques of waiting line theory are implemented for cost minimization and optimal average waiting time.
References
Anderson, D. R., Cochran, J. J., Sweeney, D. J., Camm, J. D., Williams, T. A. (2015). An Introduction to Management Science: Quantitative Approaches to Decision Making. United States: Cengage Learning.
Johnston, A., Lang, E., & Innes, G. (2022). The waiting game: managing flow by applying queuing theory in Canadian emergency departments. Canadian Journal of Emergency Medicine, 24(4), 355-356.
Srivastava, T. (2016, April 28). How to predict waiting time using Queuing Theory ? https://www.analyticsvidhya.com/blog/2016/04/predict-waiting-time-queuing-theory/
Peer2
(RA) Waiting lines are part of the common business world in which the business’ variation in demand must be manageable in order to minimize customer abandonment and bottlenecks in the supply chain. Waiting line theory focuses on customer service demand, such as hourly customer arrivals, the actual waiting line time, and the service resources from human capital to machines to handle customer volumes effectively (Anderson, 2018).
The service demand considers the elements of population size, the pattern of arrivals at the queuing system, and the behavior of the arrivals (Dumitru, 2014). Most waiting line models assume in infinite populations of arrivals which is often not realistic. Waiting time is the time a customer waits in order to be serviced, which can be limited or unlimited. Most waiting line models assume unlimited queue lengths based on the assumption that there could be an infinite population of arrivals, such as Google searches continuously worldwide. Again, in most cases with line theory we assume a first in first out service that does not prioritize on urgency (Dumitru, 2014). The service resources of the business look at the configuration of the service system and pattern of service. (Dumitru, 2014). Does the business have only a single-channel system and does it have the capabilities of expanding channels? For example, does the bank have one tellers, or does the bank have the ability to add multiple teller? Another example is when call your TV/internet provider, in which there are numerous options that customer is prompted with based on the service suport needed. Logically we would assume that more resources should be allocated to higher demand needs, especially as average time with customer increases. This may or may not be true. From the business’ perspective, the business may want to allocate the most resources to reducing wait time for new services, valuing call abandonment as the highest value. A business may want to allocate little time to those who want to discontinue their service and hope for call abandonment. Striving for call abondment to retain customers can be argued to be a bad tactic, because if we allocate higher resources that result in short wait times to customers in customer serpartion stage, may we may have a higher chance of retaining through promotion versus making them wait and becoming very angry. Personally when I have to wait 30 minutes to discuss discontinuing a service, my mind is set.
Waiting line theory can be applied to most businesses and in many cases more than one way. For example, a grocery store can use waiting line theory to reduce the wait time in checkout.. The business can also use the theory in its receiving dock area to reduce bottleneck of goods, not simply to get product on the shelf faster, but to avoid surcharge from couriers that can be passed on for excessive wait times. The waiting line theory helps managers determine how much we need to spend to be efficient based on acceptable variance that does not impact profits adversely.
References
Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J. (2018). An introduction to management science: quantitative approach. 15th Edition. Cengage learning.
Dumitru, T. R. O. A. N. C. A. (2014). The Importance of Proper Management of Waiting Lines. Revista Economică, 66(5).
How to predict waiting time using queuing theory? Analytics Vidhya. (2016, April 28). Retrieved August 21, 2022, from https://www.analyticsvidhya.com/blog/2016/04/predict-waiting-time-queuing-theory/
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