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Marketing and Advertising Analysis

You are the regional marketing vice president overseeing all US marketing for an international pharmaceutical distributor. Your team has recently submitted a proposed budget for advertising and marketing spending for the upcoming year to support 10% annual revenue growth for your company’s best-selling product, Dilomatox.  A summary of that budget along with this year’s forecasted data (forecasted since your fiscal year isn’t quite complete yet) is below:

DILOMATOX – Proposed Marketing Budget (DATA TABLE IN WORD DOCUMENT)

 

Proposed   Budget (Next Year)  Current   Forecast (This Year)     %   Change

 

Advertising and   Marketing Spending (total)   $64,250,000   $56,860,000   +13%

 

Product Revenue  $1,164,471,000  $1,058,610,000   +10%

 

Marketing   Spending as % of Revenue   5.52% 5.37%

Your senior budgeting committee reviews your budget, and the CFO sends you a summary of her team’s findings a week ahead of your budgeting meeting with the CEO. The CFO explains to you she will not support your proposed budget increase, because your main competitor Zoraffil is forecasted to spend 8.5% less on advertising and marketing but is on target to earn 7.5% more revenue. Furthermore, she has recommended that your budget be reduced to 4.57% of revenue to match what Zoraffil has achieved. To meet this goal, she has asked you to reduce your proposed budget by $11 million before next week’s meeting with the CEO. Your team has already begun identifying which marketing and advertising programs it would choose to cut.

CURRENT YEAR FINANCIAL FORECASTS (TABLE IN ATTACHED WORD DOC);

 

                                                                  Dilomatox         Zoraffil            %   Change

 

Advertising and   Marketing Spending (total)  $56,860,000  $52,040,000    -8.5%

 

Product Revenue  $1,058,610,000   $1,138,510,000     +7.5%

 

Marketing   Spending as % of Revenue   5.37%  4.57%

To support their findings, the committee has supplied your team with the attached data filePreview the document, providing weekly marketing spending and revenue (in millions of dollars) for the last 52 weeks for both brands.

Your task is to analyze this data, ‘uncover the story’ behind how advertising spend and revenue for these brands are related (or not!), and to write a managerial summary that you can use to justify your proposed advertising and marketing budget. You should organize your summary in a way that provides a strong and coherent argument, but in that argument your analysis should answer all of the following questions:

  1. Answer      parts a-b below:
    1. Describe       the relationship between advertising and revenue for Dilomatox. Would you       characterize these relationships as strong or weak? Support your response       with relevant graphs and statistics.
    2. Describe       the relationship between advertising and revenue for Zoraffil. Would you       characterize these relationships as strong or weak? Support your response       with relevant graphs and statistics.
  2. Analyze      the multivariate relationship between Dilomatox’s revenue and the other      variables provided (Dilomatox’s marketing spend, Zoraffil’s revenue, and      Zorafill’s marketing spend). Is there a significant relationship between      Dilomatox’s sales and any (or all) of these variables? Support your      response with relevant charts or statistics.
  3. What      percent of the variation in revenue does advertising and marketing spend      explain for both brands? Explain.
  4. Based      on your analysis, if both brands ceased all advertising and marketing      spend, how much revenue would be lost? Explain.
  5. What      impact will the CFO’s proposed $11 million dollar cut to your budget have      on Dilomatox revenue next year?

Your managerial summary should include a description of the statistical tests or processes used to answer each question, an explanation of the necessary results (appropriate descriptive or graphical summaries, statistics like r-values and least-squares regression equations, predicted values – and if appropriate estimates of error for any parameters or predictions made). It should also show that any required assumptions for any statistical procedures used are valid. Use a 95% level of significance for any statistical tests.