|Perfect Number of Pages to Order||5-10 Pages|
DAT565Call Center Waiting Time Spreadsheet Essay
This assignment is intended to give you an opportunity to strengthen your skills in gathering and analyzing business-related information. It provides a deeper understanding of how companies can look at globalization as part of their strategic and operational plans. The assignment has two parts: one focused on information research and analysis, and the other is on applied analytics.
“How Netflix Expanded to 190 Countries in 7 Years” from Harvard Business Review
Call Center Waiting Time
Part 1: Globalization and Information Research
Context: Companies that perform well in their country of origin usually consider expanding operations in new international markets. Deciding where, how, and when to expand is not an easy task, though.
Many issues need to be considered before crafting an expansion strategy and investing significant resources to this end, including:
the level of demand to be expected for the company’s products/services
presence of local competitors
the regulatory, economic, demographic, and political environments
Carefully researching and analyzing these and other factors can help mitigate the inherent risk associated with an overseas expansion strategy, thus increasing the likelihood of success.
As a data analyst in your company’s business development department, you’ve been tasked with the responsibility of recommending countries for international expansion. You’ll write a report to the company’s executive team with your research, analysis, and recommendations.
Write a 525-word summary covering the following items:
According to the article listed above, what were the most important strategic moves that propelled Netflix’s successful international expansion?
The article mentions investments in big data and analytics as one of the elements accompanying the second phase of overseas expansion. Why was this investment important? What type of information did Netflix derive from the data collected?
According to the article, what is exponential globalization?
Not all international expansion strategies are a resounding success, however. Research an article or video that discusses an instance in which an American company’s expansion efforts in another country failed. According to the article/video you selected, what were the main reasons for this failure? Do you agree with this assessment?
Explain some of the reasons why certain companies’ expansion plans have failed in the past.
Part 2: Hypothesis testing
Context: 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.
Access the Call Center Waiting Time file. Each row in the database corresponds to a different call. The 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 of 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 of α=0.05.
Assess if the new protocol served its purpose. (Hint: this should be a test of means for 2 independent groups.)
Submit your calculations and a 175-word summary of your conclusions.
Respond to the following in a minimum of 175 words:
Models help us describe and summarize relationships between variables. Understanding how process variables relate to each other helps businesses predict and improve performance. For example, a marketing manager might be interested in modeling the relationship between advertisement expenditures and sales revenues.
Consider the dataset below and respond to the questions that follow:
Advertisement ($’000) Sales ($’000)
Construct a scatter plot with this data.
Do you observe a relationship between both variables?
Use Excel to fit a linear regression line to the data. What is the fitted regression model? (Hint: You can follow the steps outlined on page 497 of the textbook.)
What is the slope? What does the slope tell us? Is the slope significant?
What is the intercept? Is it meaningful?
What is the value of the regression coefficient, r? What is the value of the coefficient of determination, r^2? What does r^2 tell us?
Use the model to predict sales and the business spends $950,000 in advertisement. Does the model underestimates or overestimates ales?
(1) Explain the difference between correlation and cause and effect. Give examples to explain each concept.
(2) Explain the difference between simple linear regression and multiple regression. Give examples to explain each concept.
(3) What does a scatter plot tell us? What does a scatter plot not able to tell us? How do you determine that a scatter plot might be helpful in visualizing the overall outcome?
(4) Why do you think that regression analysis is used more in the workplace more often than cause and effect?
Time series are particularly useful to track variables such as revenues, costs, and profits over time. Time series models help evaluate performance and make predictions. Consider the following and respond in a minimum of 175 words:
Time series decomposition seeks to separate the time series (Y) into 4 components: trend (T), cycle (C), seasonal (S), and irregular (I). What is the difference between these components?
The model can be additive or multiplicative. When we do use an additive model? When do we use a multiplicative model?
The following list gives the gross federal debt (in millions of dollars) for the U.S. every 5 years from 1945 to 2000:
Year Gross Federal Debt ($millions)
Construct a scatter plot with this data. Do you observe a trend? If so, what type of trend do you observe?
Use Excel to fit a linear trend and an exponential trend to the data. Display the models and their respective r^2.
Interpret both models. Which model seems to be more appropriate? Why?
What are the primary usages for time series modeling? What tools do we have to display the concept visually?
What are the limitations of time series modeling? How do we mitigate the limitations?
What are some of the ways your organization uses time series modeling? Provide real-time examples.
How do your view Statistics and Data Analytics differently than you did at the beginning of this course?