Unit 3
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LDR 5301-22.01.00-1B23-S1, Methods of Analysis for Business Operations•Unit III Article Review
Connie StanleyTotal Score:highRisk Created with Sketch.
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Article Review
Connie Stanley
1Columbia Southern University
September 3, 2022
Article Review
When calculating the likelihood of an event occurring a certain number of times within a given time frame, statisticians often turn to the Poisson distribution.
When the idea was first conceived, it was this French mathematician's full name is Simeon Denis Poisson.
1How to minimize overhead while still satisfying customers who seek support via online chat is the topic of Tezcan and Zhang's (2014) article "Routing and Staffing in Customer Service Chat Systems with Impatient Customers"
(IM).
They were interested in finding out how likely it was that users would give up on the IM due to long wait times and what could be done to cut wait times while simultaneously raising agent productivity.
Introduction
The term "customer service chat"
(CSC) refers to a service offered by many firms (often via their website) that puts clients in direct, real-time contact with a support representative.
2This is done in real time, as opposed to sending an email and waiting for a response, as is the case with typical email enquiries (Tezcan & Zhang, 2014).
1However, it has been pointed out that IM is now slower than a standard phone call. This is because an agent still has to read the message and type up a response, which can take extra time if they are juggling numerous customers at once.
There are some drawbacks to CSC systems, such as the need for technical expertise on the part of the customer, delayed contact, and an absence of natural dialogue.
3Their benefits, however, include lower operating costs than telephone customer service support.
2Tezcan and Zhang (2014) state that a distinguishing feature of CSC systems is their capacity to facilitate collaborative browsing or screen sharing between the agent and the customer during the troubleshooting of a computer or software problem.
Customers don't have to stop everything they're doing to focus just on the agent helping them, since they can continue doing so while the person is resolving their issue.
1According to the article's findings, CSCs are having trouble maintaining low staffing levels while yet offering satisfactory customer service.
This is especially the case when there are many people waiting in line but just a small number of available employees to serve them.
In many businesses, having a single agent deal with several clients has long been recognized as a source of inefficiency.
The productivity of a service worker remains strong even when they have three consumers.
1When they have four or more customers to service, though, their efficiency begins to decline, which is where the routing system comes in (Tezcan & Zhang, 2014).
4Incorporating Poisson Distribution
1The efficiency or inefficiency of multitasking is the starting point for any consideration of how a CSC can keep up a certain level of service to consumers (with respect to arrival rates and service speeds) with a minimum employees.
In the second place, we must determine a practical routing policy for the CSC.
Tezcan and Zhang (2014) also evaluate agents'
performance by counting the number of consumers they're currently helping and calculating the percentage of those customers who will "abandon"
1their service request (due to lengthy wait or response times).
This study employs the Poisson distribution to analyze the likelihood of an agent's productivity dropping due to the large number of customers assigned to them, the routing needed to spread the workload, and the level of client "abandonment,"
and to speculate how a CSC would be able to improve.
1Customer service calls to the CSC throughout a typical workday represent the number of independent occurrences that occur in a constant amount of time without regard to the preceding event (the number of customers that contact the CSC each day, is not guaranteed to be the same as the previous day).
Favoring the Poisson Distribution Over Others
1Given that "Poisson distribution describes circumstances in which customers arrive independently during a specific time interval, and the number of arrivals varies on the duration of the gap,"
5it was chosen above alternative distributions (Render et al., 2018, p.
48).
1Because clients arrive at the CSC at different times during the workday (in this case, they utilize the IM when they need an issue resolved), and because the quantity of customers that message the CSC can change, that phrase sums up the situation extremely well.
An agent could help one customer and have to wait an hour before helping another, or they could have to help many customers simultaneously.
1Since there is usually never a "fixed"
3period of time that clients will IM the CSC, a normal distribution would not have been appropriate for this type of research.
Means (the average of numbers) and standard deviations (the variance from the mean) are used in normal distributions, which have parallel sides.
One day a CSC might handle more than 100 IMs, the next day maybe just 10, and each IM might arrive at different times and last for different amounts of time.
1Practical Applications of Poisson Distribution
3Working at the New York City Military Entrance Processing Station has given me plenty of opportunities to put my knowledge of Poisson Distribution to use (NYC MEPS).
1Every day at the New York City Military Entrance Processing Station (MEPS), where I work, we have anywhere from one to thirty-five people come in to be enlisted into the United States Army. The fact that the daily enlistment rate at MEPS varies indicates that the occurrences are random and unrelated to one another.
However, the reality that candidates will be showing up at MEPS daily is a constant.
References
3Render, B., Stair, R. M., Jr., Hanna, M. E., & Hale, T.
S.
(2018).
3Quantitative analysis for management (13th ed.).
Pearson.
3https://online.vitalsource.com/#/books/9780134518558
Tezcan, T.
& Zhang, J.
(2014).
3Routing and Staffing in Customer Service Chat Systems with Impatient Customers. Operations Research, 62(4), 943–956.
Source Matches (24)- 1Student paper100%
Student paper
Columbia Southern University
Original source
Columbia Southern University
- 1Student paper90%
Student paper
How to minimize overhead while still satisfying customers who seek support via online chat is the topic of Tezcan and Zhang's (2014) article "Routing and Staffing in Customer Service Chat Systems with Impatient Customers"
Original source
How to minimize overhead while still satisfying customers who seek support through online chat is the focus of Tezcan and Zhang's "Routing and Staffing in Customer Service Chat Systems with Impatient Customers"
- 2Student paper74%
Student paper
This is done in real time, as opposed to sending an email and waiting for a response, as is the case with typical email enquiries (Tezcan & Zhang, 2014).
Original source
As opposed to writing an email and waiting for a response, as is the case with regular email inquiries, instant messaging is done in real-time (Tezcan & Zhang, 2017)
- 1Student paper80%
Student paper
However, it has been pointed out that IM is now slower than a standard phone call. This is because an agent still has to read the message and type up a response, which can take extra time if they are juggling numerous customers at once.
Original source
However, it has been pointed out that IM is still slower than a regular phone call This is because an agent must still read the message and manually compose a response, which might take extra time if they are assisting numerous clients at once
- 3Student paper63%
Student paper
Their benefits, however, include lower operating costs than telephone customer service support.
Original source
However, their advantage include costing less to operate than telephone customer service support
- 2Student paper64%
Student paper
Tezcan and Zhang (2014) state that a distinguishing feature of CSC systems is their capacity to facilitate collaborative browsing or screen sharing between the agent and the customer during the troubleshooting of a computer or software problem.
Original source
From the article, it is identifiable that CSC systems also have the distinctive capacity to facilitate collaborative browsing or screen sharing as the agent tries to remedy a customer's issue either on the software or computer (Tezcan & Zhang, 2017)
- 1Student paper87%
Student paper
According to the article's findings, CSCs are having trouble maintaining low staffing levels while yet offering satisfactory customer service.
Original source
The article's analysis shows that CSCs are having trouble maintaining low staffing levels while yet offering satisfactory customer service
- 1Student paper76%
Student paper
When they have four or more customers to service, though, their efficiency begins to decline, which is where the routing system comes in (Tezcan & Zhang, 2014).
Original source
Once they have four customers or more, though, their output begins to decline, which is where the routing system comes in
- 4Student paper65%
Student paper
Incorporating Poisson Distribution
Original source
Why Poisson Distribution
- 1Student paper69%
Student paper
The efficiency or inefficiency of multitasking is the starting point for any consideration of how a CSC can keep up a certain level of service to consumers (with respect to arrival rates and service speeds) with a minimum employees.
Original source
The Use of Poisson Distribution The efficiency or inefficiency of multitasking is the starting point for analyzing how a CSC can provide a certain level of service to clients (concerning arrival rates and service speeds) while keeping worker levels to a minimum (Seghier & Zeghdoudi, 2021)
- 1Student paper72%
Student paper
their service request (due to lengthy wait or response times).
Original source
their service request to get an available agent's service rate and level (due to lengthy wait or response times)
- 1Student paper94%
Student paper
Customer service calls to the CSC throughout a typical workday represent the number of independent occurrences that occur in a constant amount of time without regard to the preceding event (the number of customers that contact the CSC each day, is not guaranteed to be the same as the previous day).
Original source
Customer service calls to the CSC throughout a normal workday represent the number of independent occurrences that occur in a consistent amount of time without regard to the preceding event (the number of customers that contact the CSC each day, is not guaranteed to be the same as the previous day)
- 1Student paper76%
Student paper
Given that "Poisson distribution describes circumstances in which customers arrive independently during a specific time interval, and the number of arrivals varies on the duration of the gap,"
Original source
Poisson Distribution Over Other Type of Distribution Given that "Poisson distribution describes circumstances in which customers come independently over a specific period, and the number of arrivals varies on the duration of the gap,"
- 5Student paper66%
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it was chosen above alternative distributions (Render et al., 2018, p.
Original source
(Render et al., 2018, p
- 1Student paper67%
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Because clients arrive at the CSC at different times during the workday (in this case, they utilize the IM when they need an issue resolved), and because the quantity of customers that message the CSC can change, that phrase sums up the situation extremely well.
Original source
Since consumers come in at different times throughout the day (in this case, they utilize the IM when they need a problem resolved), and the quantity of customers that message the CSC might change, this remark sums up the situation rather well (Seghier & Zeghdoudi, 2021)
- 1Student paper71%
Student paper
Since there is usually never a "fixed"
Original source
Since there is seldom a "fixed"
- 3Student paper77%
Student paper
period of time that clients will IM the CSC, a normal distribution would not have been appropriate for this type of research.
Original source
Normal distribution would not have been appropriate for this type of research because there is almost never a “set” amount of time that customers will IM the CSC
- 1Student paper64%
Student paper
Practical Applications of Poisson Distribution
Original source
A Poisson XLindley distribution with applications
- 3Student paper66%
Student paper
Working at the New York City Military Entrance Processing Station has given me plenty of opportunities to put my knowledge of Poisson Distribution to use (NYC MEPS).
Original source
Poisson Distribution can be used in my everyday life because I work at the New York City Military Entrance Processing Station (NYC MEPS)
- 1Student paper87%
Student paper
Every day at the New York City Military Entrance Processing Station (MEPS), where I work, we have anywhere from one to thirty-five people come in to be enlisted into the United States Army. The fact that the daily enlistment rate at MEPS varies indicates that the occurrences are random and unrelated to one another.
Original source
Depending on the day, the New York City Military Entrance Processing Station (MEPS) where I work may have anywhere from one to thirty-five potential new Army recruits The fact that the daily enlistment rate at MEPS varies indicates that the occurrences are random and unrelated to one another
- 3Student paper100%
Student paper
Render, B., Stair, R. M., Jr., Hanna, M. E., & Hale, T.
Original source
Render, B., Stair, R M., Jr., Hanna, M E., & Hale, T
- 3Student paper100%
Student paper
Quantitative analysis for management (13th ed.).
Original source
Quantitative analysis for management (13th ed.)
- 3Student paper100%
Student paper
https://online.vitalsource.com/#/books/9780134518558
Original source
https://online.vitalsource.com/#/books/9780134518558
- 3Student paper100%
Student paper
Routing and Staffing in Customer Service Chat Systems with Impatient Customers. Operations Research, 62(4), 943–956.
Original source
Routing and Staffing in Customer Service Chat Systems with Impatient Customers Operations Research, 62(4), 943–956
- 1Student paper100%
