. Demonstrate knowledge and understanding of the role of quantitative analysis in generating value from data.
- Apply basic statistical techniques to business and management problems.
- Communicate quantitative ideas effectively in written form.
- Use a variety of visual models to represent statistical results.
- Use Excel for data analysis and presentation.
A company sells its products all over Europe. The company has designated geographic sales territories, each the responsibility of a single sales representative who services a number of retail outlets within his or her territory. The company wants to find out which factors influence the quantity of sold units and the impact each factor has on sales. For this, a random sample of 90 sales territories of the firm’s sales organisation was drawn. Information was collected on the number of units of the product sold, along with values for seven possible predictor variables, in each territory.
Sales were hypothesised to be a function of the following variables: - The advertising budget in that territory during the past year (Advertising; in €s);
- How long the territory sales representative had been employed by the company (Time with Company; in months);
- What percentage of the market potential the company actually had in this territory (Market Share);
- The market size in the territory, measured as total sales of products within the same product category (Market Potential);
- The number of retail outlets the sales representative was responsible for in this territory (Outlets);
- The average rating of the company in each territory (Rating);
- The number of meetings between the sales representative and someone from top management (Nb of meetings; semi-annually).
The Excel spreadsheet “QAM CW DATA 2021.xlsx” contains data for the 90 sample sales territories.
You are tasked to conduct the data analysis to provide the CEO with insights about what drives or predicts sales. For this you should write a summary of your findings and recommendations for the company in management terms, so the CEO knows what to focus the company’s
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attention on. Bear in mind that the CEO is very busy, not a fan of statistics jargon and thus wants easily accessible information.
The CFO has also announced their interest in your findings because they are hoping for a mathematical model to predict future sales. Unlike the CEO, the CFO is a bit of a statistics whizz and will critically examine your analysis and assumptions.
To please both of them, you should write a report of maximum 2500 words (this is excluding tables and graphs) with the following structure:
Start with the summary of the findings and recommendations arising from your analysis. This is aimed at the CEO so it has to go first, as they won’t read the rest of the report. Remember they want information fast and concise but do value completeness. The summary and recommendations to the CEO should constitute the main part of the report.
The second part of the report, which could be the appendix, should demonstrate and explain the steps you have taken in your analysis, the full model of what drives sales and which assumptions you have made and tested. Remember this needs to be statistically accurate, as the CFO will examine it critically and might recommend scrapping your results to the CEO if they don’t trust your procedure. This part does not need to include a lot of writing/text but must include tables and graphs with some explanation.
Your work should be presented in a word document, not in an Excel file.
You will
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be assessed on:
The correctness of your models and statistical analysis
The correctness and details in your interpretations of all the output
The clarity of the interpretation of your analysis for management’s (CEO) understanding
The structure and presentation style of the report
Recommendations arising from the analysis and suggestions for future work Conducting any relevant extended analysis beyond the basic brief (especially if based on your own independent reading with relevant sources)