Read the case study. If you were in Alexandra’s position, which one coaching style would most likely appeal to James, and why? What behaviors would you engage in while coaching James to ensure that he is productive? Provide reasons for why you would use the specified actions. Case Study Alexandra was recently promoted from Associate to Senior Associate at Jeffries, Smith, and West, an accounting company in Vancouver specializing in tax audits for companies in the entertainment industry. Before this promotion, Alexandra didn’t have any managing experience with this firm. Still, with the promotion, she now manages a team of six Associates and three Junior Associates. Many employees on her team are people that she has worked with previously and knows quite well from her experience as an Associate. One of the Associates whom Alexandra has worked with and now manages is James. James has worked for Jeffries, Smith, and West for three years and has developed a reputation of “playing hard,” but not always “working hard.” Alexandra has worked with James on two separate occasions. The first time was two years ago when they were on a team that audited Bridge Studios. While on this project, Alexandra observed that James was a very competent person and excelled as a team member. The second time Alexandra and James worked together was nine months ago when they worked on an audit for Vancouver Film Studios. While on this project, Alexandra saw a very different side of James. James seemed to be bored and unengaged with his work. On top of that, Alexandra overheard their managing Senior Associate complain about James’ lack of organization and discipline. Because Alexandra is now James’ manager, she is trying to figure out what she can do to help James be the employee he was when working on the Bridge job. Alexandra reflected upon the differences between the Bridge and the VFS jobs to see what kept him engaged and working hard on the Bridge job or what caused him to be disengaged from the VFS job. One difference between the two projects that stood out to Alexandra was the managing Senior Associate. The managing Senior Associate with the Bridge job, Jackson DeRosa, was probably one of the best managers that Alexandra had encountered since being with the firm. She loved how he was so personable with his subordinates. He seemed to know each employee personally. Even more, he seemed to know what buttons to push to motivate his employees. Throughout the company, Jackson was known as the only manager who always met his deadlines. Everyone loved working for him. In sharp contrast to Jackson was Alexandra’s managing Senior Associate on the VFS job, Gary Boone. In Alexandra’s opinion, Gary was a critical boss who cared only about the numbers and not his employees. Gary often had his employees work 14 hour days on the weekend. Since that time, Gary had left the firm. **Coaching within a Business Environment – specifically HR related

As a brand manager of Pepsi-Cola, you are asked to build an understanding of the sales return
of its marketing mix decisions. To that end, information on weekly brand sales of Pepsi and
Coca-Cola are collected over a period of 116 weeks.
The data cover real-world sales and marketing mix information on Pepsi-Cola and Coca-Cola
aggregated across a selection of grocery stores at 1 European grocery retailer. The Excel file
“cola.xls” contains the data on both brands. Brand 1 in the data refers to Coca-Cola, and brand
2 refers to Pepsi-Cola. For example, “sales.brand1” (column B) refers to the sales of CocaCola, whereas “sales.brand2” refers to the sales of Pepsi-Cola (column K). The objective of the
analysis is to build an understanding of Pepsi’s sales drivers (not Coca Cola’s drivers). In other
words, your response variable will be “sales.brand2” (not “sales.brand1”).
Note that the data are proprietary. No part of the data may be used for other purposes than for
completing this assignment, and please do not further distribute any part of the data.
Brand 1 Brand 2
Coca-Cola Pepsi-Cola
The following variables are available for each brand:
Variable name Variable description
Week Ranges from 1 to 116. “1” indicates the first week of the data, “116” the
last week of the data. “1” corresponds to the first week of January (in
2015).
Sales Total weekly brand sales (expressed in litres)
Feature Percentage of SKUs (Stock Keeping Units) on feature
Display Percentage of SKUs (Stock Keeping Units) on display
Price Average paid price (i.e., after discounts) per litre
Assortment Average number of SKUs (Stock Keeping Units) by the brand stocked
by the retailer
TV Total weekly spending (in euro) on TV advertising
Digital Total weekly spending (in euro) on Digital advertising
OOH Total weekly spending (in euro) on Out Of Home (OOH) advertising
Magazine Total weekly spending (in euro) on Magazine advertising
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Questions
1) Calculate descriptive statistics about the sales and marketing mix variables for both
brands. Report the statistics and summarize learnings and insights. For instance, who is
the market leader? How do the brands compare in terms of pricing, promotion,
assortment? How do the brands compare in terms of allocation of spending between the
four advertising instruments?
2) Estimate a regression model with a log-log specification that explains Pepsi’s sales
(“sales.brand2”) as a function of Pepsi’s own marketing mix variables. Only include
the following 8 predictors in the model: Pepsi’s feature, display, assortment, price, tv,
digital, ooh, and magazine (i.e., exclude Coca-Cola’s marketing mix variables from
your model). Only add a value of 1 to predictors that contain zero values before
estimation. Report the results of the model. Based on this model, what do you conclude
about the relation between Pepsi’s marketing mix variables and its sales?
3) The brand would like to understand whether its TV, OOH, magazine, and digital
advertising have a longer-term effect on its sales. Estimate the same model as estimated
in question 2, but now use an adstock specification for all four advertising instruments,
setting lambda to 0.6 for all four advertising instruments. Report the results of the
model, interpret the estimates about the impact of advertising on sales and about the
impact of the other marketing mix elements, and discuss your findings.
4) Reflect critically on the validity of the estimated coefficients in question 3. For instance,
to what extent can the model accurately predict future outcomes? To what extent are
predictor variables correlated with one another? Are there any potentially important
excluded variables? What are the implications for the validity of your findings? How
can the model be improved?
Evaluation
The overall objective is to illustrate that you can use the available data and modelling
techniques to build an understanding of sales drivers, interpret results to generate insights,
reflect critically on the validity of the model, and provide solutions to overcome limitations of
a model.
Marks are assigned per question:
• Question 1: 20%
• Question 2: 10%
• Question 3: 20%
• Question 4: 40%
• 10% is based on the overall quality of presentation of the answers (e.g., use of
tables/figures to present results, clarity and quality of presented answers)
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Format
• PDF document: Times New Roman 12, single spaced. Maximum 6 pages (excl. cover
page). There is no word count.
o Structure your report along the questions and indicate this clearly using
headings in the report (“Question 1”, “Question 2”, “Question 3”, “Question
4”).
o Integrate tables/figures in the main part of your report
• Submit the R code along with your PDF report.

Sample Solution