Author: Arend Pryor | Created: 04/23/2021
Details: Sharing content created as part of pursuing my MBA degree
Assignment: Write a response to the following in a minimum of 500 words taking the following questions into consideration based on customer service essentials:
Why are there economies of scale in queuing systems?
What are the pros and cons of pooled-queue systems and separate-queue systems? Provide examples along with your opinion of the best option.
Provide an example of how variability can reduce capacity.
Once compromised, how can capacity be restored?
If you happened to call up your favorite pizza place only to find they were so backed up that the wait time was an hour and a half, you might just decide that Mexican food sounds like a better choice. Many businesses today offer some type of queue system, which allows customers the option of waiting in line (physically or virtually) for products or services. Having these systems in place gives your customers the option of waiting when demand exceeds the company’s available resources. While offering this type of system might seem like common sense, offering the right type of system based on the situation can lead to increased efficiencies like shorter wait times that benefit both the customer and the company. Pooled and separate-queuing systems are examples of options available to companies who need them. In the sections below we will cover the details of each along with their pros and cons. Before we move ahead, it is also important to mention the area of variability and the negative impacts it can have on queuing systems. This will also be discussed along with recommendations for getting things back on track.
When production processes increase and become more efficient, this is known as economies of scale and can result in cost gains and even a competitive advantage for the organization (Kenton, 2021). In companies that provide a service to customers or for those who have a call center, demand can sometimes build to the point where all available resources are busy and will be unable to service the customer. When demand exceeds capacity, such is the case in these examples, adding some form of queue can serve as a holding ground where customers have the option of waiting for a resource to become available. Thus, adding queues provides the ability for companies to increase their capacity by providing customers with a way of waiting in line to be served rather than finding no resources available and deciding to leave.
Queued systems have also shown the ability to handle higher levels of utilization without negatively affecting customer wait times (Cachon & Terwiesch, 2019). In other words, the addition of queues can increase the efficiency of a process by preventing potential customers from taking their business elsewhere and result in gains for the company.
While separate or single-queue systems operate independently to meet the demand of their customers (think bank teller or Subway sandwich maker), in a pooled-queue system, two or more individual systems that often mirror the capabilities of each other, are grouped or pooled (think grocery stores with both live checkers and self-check out options). Both of these systems offer their own list of pros and cons, the details of which are included below:
Pooled-queue System:
Pros:
Pooled queues can be set up so that customers with specific needs can be matched up with the right resource (Single vs. Multiple Queues: Which Is Right for You?, 2020)
Decreased interarrival time and increased capacity due to more servers
Interarrival Time: Elapsed time that exists between serving customers. It starts when one leaves and ends when the next one arrives
Reduction in denial of service probability
Processing time and implied utilization will remain unchanged, but utilization can increase slightly
Cons:
Pooling systems results in large benefits at first, however, as more systems are added to the pool, the benefits seen are marginal and continue to decrease as more systems are added to the pool
While pooling systems can result in increased capacity for one particular location, it can cause a decrease in capacity for nearby locations if machines and/or resources were taken from those locations for the new pool.
Pooling can provide increased efficiency, however, the trade-off could come at a cost of decreased convenience of location. Finding the right balance is the key. (Cachon & Terwiesch, 2019)
Separate-queue Systems:
Pros:
Can be easier to set up than pooled queues and offer their own level of improved efficiency. One example of these are virtual queues set up by grocery stores during the pandemic that let customers check in via an app once parked. The app will then notify the customer once it is their turn to enter the store.
Some customers like the fairness of these systems as they will not lose their place in line or be cut as they operate on a first come first served basis (Single vs. Multiple Queues: Which Is Right for You?, 2020).
Cons:
Can include a risk of customers getting matched up with a representative who is not as skilled or lacks the experience to assist with their needs
Variability of processing times has a much greater impact on wait times in a single queue system
If the system has a lack of servers, there is a higher chance of slower processing times and the probability of loss will be higher (Cachon & Terwiesch, 2019)
Variability is the enemy of efficiency in the business world and can negatively impact the capacity of a process. One example that comes to mind is that of a tax preparation company that helps customers during tax season. Let’s say that ABC Tax Pros starts with a group of five tax preparers that aid customers with tax questions and filing their yearly taxes. During the first week of January, the number of customers could be low as not everyone has received their W2’s, which results in an interarrival time of demand at 1.5 hours and an average processing time of 1 hour. Based on these numbers, capacity would be calculated at 5 customers per hour. Taking this a step further, we can also calculate the implied utilization for the current capacity using the formula (p / (a * m)) and this would give us a value of 13%.
If we checked back on the company near the middle of March, as the deadline for tax season is just around the corner, we might now see that the interarrival time is more frequent at 45 minutes. With customers coming through the doors more frequently, it stands to reason that variability of the types of tax returns needing to be processed will also increase somewhat. For this reason, let’s assume that the average processing time is now 1.3 hours. Using these updated numbers, capacity would now be calculated as 3.8 customers per hour, which is a decrease from the previous calculation of 5 customers per hour. Just as before, we can calculate implied utilization, which is now at 35%. As seen, the increase in variability seen by the tax preparers, impacted capacity by reducing it from 5 customers per hour to 3.8 customers per hour. Finding ways to reduce variability would help to combat this issue.
In a perfect world, or more accurately, in a perfect business process, capacity would always have the ability to keep up with demand despite unexpected variability, however, we know this is often not the case. The variability experienced by the tax preparers during the busy part of the season in the previous section resulted in an increase in the average processing time and subsequently reduced their capacity. Based on past experiences, this situation is no doubt expected, however, what should companies do to restore capacity? First and foremost, companies should analyze how work currently gets done and ensure they specify guidelines or standardized working procedures to create consistency and take the guesswork out. This will help alleviate a portion of the variability and help increase capacity (Cachon & Terwiesch, 2019). Next, companies should review the size of their inventory buffer, if one currently exists, and figure out if increasing it would help to offset the effects of variability on processing times. However, it is important to note that while adding buffers can offer some benefits, adding too much can mask issues in the process that will emerge sooner or later (Cachon & Terwiesch, 2019).
Without giving it much thought, most of us have come to accept and even expect having to wait in line sooner or later. As shown above, queues are the saving grace for most companies and a way of retaining customers until they can be served. These systems show signs of having economies of scale in that enhancing them can lead to increased efficiencies, capacity and utilization. Pooled and separate-queue systems are two of the more popular types of queue systems in use and the decision to use one over the other can be found by weighing the pros and cons as we did above. Once you have a system in mind, it is important to check in on things and analyze the impact that variability has on it and then to take steps to mitigate it and keep things like capacity at an acceptable level in order to meet the demand of your customers. After all, the demand for a particular product or service combined with the type of queue being offered, can do a lot to help soften the blow of being stuck in a queue, but only for so long.
References
Cachon, G., & Terwiesch, C. (2019). Operations Management 2nd Edition, International
Student Edition. (2nd ed.). McGraw-Hill Education.
Kenton, W. (2021). Economies of scale. Investopedia.
Single vs. multiple queues: Which is right for you? (2020). JRNI.
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