Competency Assessment – Call Center Operations

Scenario Evaluation – Summary of Conclusions

The conclusiveness of hypothesis testing helps one determine the truthfulness of certain statements and make conclusions regarding the hypothesized conditions. Such an approach is used in many fields, such as business, where information analysis is used in strategic business management. The present analysis narrows down to how an organization seeks to determine the efficiency of call center activities and its measures’ success. Another element that defines service quality within a call center is the customer’s waiting time before they are connected to an available operator (Ilk & Shang, 2022). Long hold time affects the customer in a negative way where they can hang up the phone or complain about how they were handled. The analysis is, therefore, based on the industry average Time in Queue (TiQ) estimated at 150 seconds, as informed by prior studies.

Another critical indicator is Service Time or (ST), which determines the time a customer service representative takes to solve a customer’s concern. Operators with enhanced experience and understanding can handle calls more quickly than their inexperienced counterparts. As for the strategy of minimizing ST, it is possible to offer additional training to representatives or simply send the calls based on the agents’ fields of interest. According to the current statistical information, the average ST of the company is 210 seconds, which is higher than the industry standard. As a result, the company has placed a new practice that will route callers to representatives with such knowledge. Therefore, the present study proposes to compare the utility of this New Protocol (PE) with that of the Traditional Protocol (TP).

Calculations

Hypothesis Test: Average TiQ

This section involves a hypothesis test to compare the average TiQ with the benchmark of 2.5 minutes at a significance level of α = 0.05. The null and alternative hypotheses are as follows:

Null Hypothesis (H0): The average TiQ is equal to the industry standard of 150 seconds
Alternative Hypothesis (H1): The average TiQ is lower than the industry standard of 150 seconds

H0: μ = 150 vs. H1 : μ < 150

Since the p-value from the analysis (p = 3.5661E-97) is less than 0.05, we reject the null hypothesis and keep the alternative hypothesis. This means that the average TiQ is lower than the industry standard of 150 seconds.

Evaluating whether More Resources Should Be Allocated To Improve TiQ

The hypothesis test results suggest that the company should invest more resources to reduce the Time in Queue (TiQ) so that it goes below the industry average.

Hypothesis Test: Average ST

The findings of this part include a hypothesis test that evaluates whether or not the mean Service Time (ST) with service protocol PE is lower than the mean Service Time with the PT protocol at a significance level specified as α = 0. 05.

Null Hypothesis (H0): The average of ST, the service protocol PE is equal to PT protocol

Alternative Hypothesis (H1): The mean ST with service protocol is lower with PE than with the PT protocol

H0 : PE = PT vs. H1 : PE < PT

Since the p-value from the analysis, p=5.7705E-12, is less than 0.05, we reject the null hypothesis and keep the alternative hypothesis. We can then conclude that the mean ST with the service protocol is lower with PE than with the PT protocol.

An Assessment of Whether the New Protocol Served Its Purpose

The new protocol was adopted to provide the service under the industry’s average time. However, the evaluation of the services shows that the New Protocol (PE) and the Traditional Protocol (PT) did not differ in service time. This implies that the desired goal of using the protocol was not met. Therefore, the organization needs to adopt a new strategy and look closely at putting more measures in place as well as providing better training to the customer relations officers.

Summary of Conclusions

In summary, the company has failed to meet the industry average in terms of service time and time on hold. Hu et al. (2022) propose that one way of lessening the time taken to serve the customer is to direct calls to agents with specialization in the particular area of concern. Still, the application of this approach did not give the expected outcomes regarding the company, which means there is a requirement to develop the current position or examine other approaches. Thus, one of the best practices that can considerably reduce service time is investing in employee training; this will help the staff work faster and better, enhancing customer satisfaction.

Moreover, to overcome the queue time issue, the company can provide more representatives or an IVR system for simple or routine customer inquiries like FAQs. Further, as a tool, the IVR system should be backed up by the design of an extensive website that offers solutions to different customers’ questions, which will minimize their chances of contacting the agents. Before changing the strategies on the new protocol, the company should assess new strategies and measures employed over the next few months to determine the root causes of TiQ and ST and possible ways to reduce them effectively.

References

Doane, D., & Seward, L. (2022). Applied statistics in business and economics (7th ed.). McGraw-Hill.

Hu, K., Allon, G., & Bassamboo, A. (2022). Understanding customer retrials in call centers: Preferences for service quality and service speed. Manufacturing & Service Operations Management. https://doi.org/10.1287/msom.2021.0976

Ilk, N., & Shang, G. (2022). The impact of waiting on customer‐instigated service time: Field evidence from a live‐chat contact center. Journal of Operations Management, 68(5), 487–514. https://doi.org/10.1002/joom.1199

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We’ll write everything from scratch

Your organization is evaluating the quality of its call center operations. One of the most important metrics in a call center is Time in Queue (TiQ), which is the time a customer has to wait before he/she is serviced by a Customer Service Representative (CSR). If a customer has to wait for too long, he/she is more likely to get discouraged and hang up. Furthermore, customers who have to wait too long in the queue typically report a negative overall experience with the call. You’ve conducted an exhaustive literature review and found that the average TiQ in your industry is 2.5 minutes (150 seconds).

Competency Assessment – Call Center Operations

Another important metric is Service Time (ST), also known as Handle Time, which is the time a CSR spends servicing the customer. CSR’s with more experience and deeper knowledge tend to resolve customer calls faster. Companies can improve average ST by providing more training to their CSR’s or even by channeling calls according to area of expertise. Last month your company had an average ST of approximately 3.5 minutes(210 seconds). In an effort to improve this metric, the company has implemented a new protocol that channels calls to CSR’s based on area of expertise. The new protocol (PE) is being tested side-by-side with the traditional (PT) protocol.
Download the Call Center Waiting Time database.
Each row in the database corresponds to a different call. Column variables are as follows.
• ProtocolType: indicates protocol type, either PT or PE
• QueueTime: Time in Queue, in seconds
• ServiceTime: Service Time, in seconds
Perform a test of hypothesis to determine whether the average TiQ is lower than the industry standard of 2.5 minutes (150 seconds). Use a significance level α=0.05.
Evaluate if the company should allocate more resources to improve its average TiQ.
Perform a test of hypothesis to determine whether the average ST with service protocol PE is lower than with the PT protocol. Use a significance level α=0.05.
Assess if the new protocol served its purpose. (Hint: This should be a test of means for 2 independent groups).

Write a 175-word summary of your conclusions.

Link to video:
https://drive.google.com/file/d/1OqanacuQ3wrFh-4bhNMRNcvB90lDqNaJ/view?usp=drive_link