You manage a call center that processes orders. One measure of efficiency in your department is the time spent on each call. You need to report to your superiors on the time-per-call in your call center each month. You’ve identified a small group of employees who are considerably more efficient than the others, and you know that efficiency tends to decrease, in general, on Fridays.Identify the ethical issue(s) involved in developing a sampling protocol:Group of answer choicesThere are none. It’s a simple mathematical operation.In order to get a random and representative sample, you need to consider how efficiency fluctuates over the month, and sample call times on a frequency that includes every day of the week.The analysis and reporting should consider the impact of extreme values in the data.
Question
You manage a call center that processes orders. One measure of efficiency in your department is the time spent on each call. You need to report to your superiors on the time-per-call in your call center each month. You’ve identified a small group of employees who are considerably more efficient than the others, and you know that efficiency tends to decrease, in general, on Fridays.Identify the ethical issue(s) involved in developing a sampling protocol:Group of answer choicesThere are none. It’s a simple mathematical operation.In order to get a random and representative sample, you need to consider how efficiency fluctuates over the month, and sample call times on a frequency that includes every day of the week.The analysis and reporting should consider the impact of extreme values in the data.
Solution
The ethical issues involved in developing a sampling protocol in this scenario include:
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Bias in Sampling: If you only consider the small group of employees who are more efficient, it may lead to biased results. It's important to include all employees in the sample to get a true representation of the time-per-call in your call center.
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Time Variation: Efficiency tends to decrease on Fridays. Therefore, if you sample more on Fridays, it may skew the results. It's important to sample call times on a frequency that includes every day of the week to get a more accurate measure of efficiency.
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Extreme Values: The analysis and reporting should consider the impact of extreme values in the data. If there are calls that take an extremely long or short time, these could skew the average time-per-call. It's important to consider these values and decide how to handle them in the analysis.
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