Posted: August 8th, 2022

COMP 2 Scenario: Your organization is evaluating the quality of its call center

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COMP 2
Scenario:
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).
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.
SEE ATTACHED EXCEL
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. Include your
calculations in the summary
CITE ALL SOURCES
SEE RUBRIC

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