1. Assessment Brief
2.1. Assessment learning outcomes
This assessment is designed to gauge your understanding, skills and application of common data
analysis techniques used in business and other organizations today. As such you need to demonstrate your attainment in these areas according to the four Module Learning Outcomes (LOs):
• LO1: Critically evaluate the evolving use of data in solving business problems, presenting logical arguments based on evidence
• LO2: Explore how data analytics can be used within a business context
• LO3: Critically appraise the presentation of data within a business environment • LO4: Critically evaluate different business analytical techniques as part of planning a data analytics initiative.
2.2. Scenario
You have recently been employed by Olympic Sports Ltd. as a data analyst. Olympic Sports Ltd. is an UK-based manufacturer of sport products selling across the UK and abroad. The company offers its products under its brand Olympic. The brand includes sports clothes such as outerwear, t-shirts, shirts, shorts, trousers and footwear for all kind of sports (e.g. Aerobics, Athletics, swimming, Basketball, Boxing, Climbing, Cricket and Cycling).
Olympic Sports Ltd. has grown successfully selling its brand across many of the high street retailers in the UK including John Lewis, H&M and M&S. The company has also expanded business in other countries in Europe, in particular in France and Germany where it uses leading local retailers to sell its products.
As Olympic Sports Ltd. expands, it continues to increase its data analytic roles within the organization to strengthen its strategic decision-making capabilities. The recruitment strategy is to employ young professionals with strategic and data analytics skills willing to provide Olympic Sports Ltd. top management with a strong evidence-based foundation for their business decisions. They like recruits to have a broad management experience combined with a strong academic background. Your MSc Management degree at BPP University was a key element in their decision to recruit you.
As part of the induction process at Olympic Sports Ltd., you have joined the Finance Department as junior data analyst. Your manager requested you to complete a number of tasks to ensure that you have a grounded knowledge and understanding of data analytics and its application in decision making. This is your opportunity to demonstrate your capability and give your employer the confidence to let you run your own project in the future.
As part of your first duties, your manager asked you to join the team in charge of the development of next year’s Business Plan for the company. The team is analyzing different options for growth, which include expanding in more countries abroad, new product development and diversification into new business areas. However, it makes sense to define the strategy based on these options only
if the current business model does not provide the expansion and growth opportunities expected by the top management. So, you have been given the responsibility to analyze Olympic Sports Ltd. current business performance.
Your job will be to analyze the performance of the business in the UK, France and Germany. Olympic Sports Ltd. has experienced strong competition in these countries from international sport brands such as Nike, Adidas, Puma, Fila and Reebok. So, the performance in these countries is a good indication of the current overall market position of the company.
2.3. Research objectives and tasks
The Finance Director, who is responsible for assessing the financial viability of the company to invest in the different growth scenarios, is interested in understanding the option of opening its own branded shops, so that the company can sell its products directly to customers without going through distributors and local retailers. This strategy will also allow Olympic Sports Ltd. to strengthen its brand against competitors who have already branded shops such as Nike. For this purpose, he wants you to:
Question 1: Perform a sales value and volume analysis of the three countries to identify the best country to open the first branded shop.
As part of the analysis, the Creative Director wants to consider the re-development of the product portfolio. He wants to focus on improving current products in terms of quality and design, therefore enhancing the market position and competitiveness of the Olympic brand. However, since the budget for product development has been reduced in the last few years, the improvement efforts have to be concentrated only on a few products, that is, the high-selling products. The current portfolio of sport products is made of the following product categories:
• Outerwear
• t-shirts
• shirts
• shorts
• trousers
• footwear
In this respect, he wants you to:
Question 2: Perform an analysis of the product offering to identify best performing sport products.
In addition to competing against global brands, Olympic Sports Ltd. has also experienced strong competition from retailer’s private brands. A private brand, also called a private-label brand, is a brand owned by a company and offered by that company alongside and competing with brands from other businesses/suppliers. Many high-street retailers have developed their own private brands as a way to improve their profitability at the expenses of their suppliers’ business. Olympic brands face pressure from private labels which in many cases offer equivalent sport products at less price and have more shelf space at the retailers’ stores. One option Olympic Sports Ltd.’s management is
considering to balance this pressure is to become a manufacturer for private brands. By supplying sport products to private brands, the company could improve production (asset utilization) achieving economies of scale which translate in lower cost of production for Olympic branded products, therefore allowing to keep profitability even under price promotions.
Taking a cautious approach to dealing with private brands where distribution partners are also competitors, in June 2022 the company ran a trial in Germany where two outsource contracts were signed with leading retailers to produce their private brand sportswear products lines. The revenue of Germany is the combination of the sales from the Olympic brand and the income from the production of sport products for private brands. The Sales Director is keen to understand if this new strategy could be expanded to other countries. So, he wants you to address the question:
Question 3: Did the two contracts signed in Germany to produce sport products for private brands have a positive impact on the sales performance of the subsidiary?
The responses to the issues detailed above should be included in a summary MS Word report that you save and submit as a PDF format file.
Because this is your first project within Olympic Sports Ltd., the Finance Director has given you additional details regarding the structure and content that it is expected to see in your report. This is set out in Section 3 – Report Structure.
A set of data is available (see module dataset spreadsheet file). Since the data comes directly from the country offices, quality issues are present which will require your attention!
You have five tasks to complete for your summative report. The first three are exactly the same as for your formative report and you should update your answers to these tasks based both on feedback on your formative submission together with your own further learning across the module.
Task 1: Introduction and project plan (20 marks)
Summarize what you are going to present in the report and justify your plan for delivering the research project to the Financial Director. Ensure you also make clear reference to a data analytics project framework as part of your plan. Finally, specifically explain how data analytics can add value and drive business performance improvement for Olympic Sports Ltd.’s subsidiaries.
Guidelines:
• State the purpose of report and describe the report structure and contents • Present your overall project plan for delivering the project
• Ensure that your project plan explicitly refers to a data analytics project framework and explain how the selected framework can be used/applied to address the core three business questions assigned to you.
• Suggest a list of Key Performance Indicators (KPIs) for Olympic Sports Ltd.’s subsidiaries and explain how better data analytics enables improvements against these KPIs.
Task 2: Data preparation quality issues and remedies (10 marks)
Discuss first the generic issues that data analysts encounter in collecting, integrating and cleaning data. Second, discuss the specific quality issues with the project data that the Finance department has provided and how you propose to address those issues.
Guidelines:
• List and explain generic data problems and how to identify them. What are the different options for resolving these generic issues?
• List all data problems you have identified in the Olympic Sports Ltd. dataset. Explain how you identified the problems (give examples of the issues) and how you propose to address/solve them.
Task 3: Data analysis and commentary (20 marks)
Using tables, set out and explain the results of your numeric data analysis, including summary of exploratory data and supporting commentary. Explain how your results provide an understanding of Olympic Sports Ltd.’s subsidiaries performance. This should include three tables setting out:
(Table A) Data and trends in sales volume and value by month, by year and across the 3 years period,
(Table B) Benchmark comparisons of sport products categories performance covering sales volume and value by quarter, by year and across the 3 years period, and
(Table C) Benchmark comparisons of sales volume and value between subsidiaries by quarter, by year and across the 3 years period.
Guidelines:
• Include summary exploratory data calculations for total sales value and volume. The analysis could include for example top and bottom performing sport product categories, ranges, averages, standard deviations; top and bottom performing time-periods, etc.
• Ensure your tables are professionally presented: headings, units, data formats. Highlight and annotate key data elements
• For each table include firstly an explanation of the table and its contents and then a bullet point list of what you can see or infer from the analysis of the data.
Task 4: Data visualization and commentary (20 marks)
Using data charting/graphics, develop visual presentations of the data together with bullet-points setting out the key findings and inferences from your analysis of the charts/plots. This should include three charts presenting:
(Chart A) Comparison of sales value trends across subsidiaries over time
(Chart B) Sport product categories performance comparisons between subsidiaries, and (Chart C) Impact of the two contracts signed in Germany to produce sport products for private brands, and in comparison with the other two subsidiaries.
Guidelines:
• Ensure you provide well-presented and labeled charts
• Use a combination of visualization plots and techniques such as bar charts, stacked bar charts, trend charts, pie charts and tree map charts
• For each chart include firstly an explanation of the chart and its contents and then a bullet point list of what you can see or infer from the data.
Task 5: Conclusions and recommendations (20 marks)
Based on your analysis and findings in Tasks 3 and 4 set-out your conclusions and recommendations. Ensure you address the three issues raised by the top management.
Guidelines:
• What conclusions can be inferred regarding Olympic Sports Ltd.’s subsidiaries sales performance and operations? Remember to include the answers to the three issues/questions raised by Olympic Sports Ltd. top management.
• What are your business recommendations to Olympic Sports Ltd.’s CEO and top management?
• Include any suggestions related to data analytics and its better use within the organization. • Note that it is also acceptable to add to your data analytics recommendations, possible actions that Olympic Sports Ltd. might take, based not only on your findings but also on your wider knowledge of the business and sport apparel market sector.
Report Structure and References (10 marks)
In addition, ten marks are awarded for the overall professionalism of your report and the adoption of academic standards.
Guidelines:
• Your report should follow the section naming structure and order set out in the Brief. You should also add your own sub-headings as you see fit to demonstrate your ability to on develop structure and content
• Your report should include an auto-generated contents page including section headings and subheadings. The contents page should also include a page-referenced list all tables, charts and figures provided in our report. Remember to number all pages in your report, for example ‘Page 8 of 12’.
• Ensure you develop your discussion in a logical progression: Findings, inferences, conclusions, recommendations
• Do not make general assertions without supporting evidence
• Zero spelling errors and grammatical mistakes
• Cite all your sources in the body of the text and in the Referencing using the Harvard Referencing style
• Include a blend of industry research, case studies and academic references
2. Report Structure
You should set out your report according to the following heading structure. You should add sub headings under this overall structure as you feel fit to demonstrate your ability to on-develop the
section themes and to provide meaningful sub-structure. But you must use this overall structure in order to provide a consistent framework against which your marker will allocate marks. You will be deduced marks if you do not follow this structure. Also note that there is no requirement for producing an Executive Summary.
University Cover Page
Table of contents
1. Introduction and project plan
2. Data quality issues and remedies
3. Data analysis and commentary
4. Data charting and commentary
5. Conclusions and recommendations
6. References
7. Appendix (optional)
In addition, you may wish to add further appendices as you see fit in order to support your work.
Word count: 2,500. Cover Page, Table of Contents, References, Appendices, Tables, Charts and Figures do not count towards word count.
3. Mapping Learning Outcomes to Assessment Tasks
The table below sets out the mapping between the four Module Learning Objectives and the key
tasks in your Summative Assessment which test your achievement against these Learning Objectives.
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Learning Outcome |
Mapping to Summative Assessment Tasks |
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LO 1: Critically evaluate the evolving use of data in solving business problems, presenting logical arguments based on evidence |
Task 1: Introduction and project plan Task 5: Conclusions and recommendations |
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LO 2: Explore how data analytics can be used within a business context |
Task 2: Data quality issues and remedies Task 3: Data analysis and commentary |
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LO 3: Critically appraise the presentation of data within a business environment |
Task 4: Data charting and commentary |
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LO4; Critically evaluate different business analytical techniques as part of planning a data analytics initiative |
Task 1: Introduction and project plan |
4. Marking Guide (Student version)
The assignment is marked out of 100 and counts towards 100% of your module mark. The following table shows the tasks, marks and marking rubric. You should iteratively self-assess your performance against the Marking Guide as you develop your draft submission, in order to evaluate your performance against your target grade.
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Assignment task Distinction (70-100%) Merit (60-69%) Pass (50-59%) Low Fail (40-49%) Fail (0-39%) |
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1: Introduction and project plan (20 marks, LO1, LO4) |
Guidelines: • State the purpose of report and describe the report structure and contents • Present your overall project plan for delivering the project • Ensure that your project plan explicitly refers to a data analytics project framework and explain how the selected framework can be used/applied to address the core three business questions assigned to you. • Suggest a list of Key Performance Indicators (KPIs) for Olympic Sports Ltd.’s subsidiaries and explain how better data analytics enables improvements against these KPIs. |
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Excellent presentation of an analytical framework or approach that can be used to answer the business question. Excellent justification of why this analytical framework or approach can be effective in answering the business question. |
Good presentation to any analytical framework or approach that can be used to answer the business question. Good justification of why this analytical framework or approach can be effective in answering the business question. |
Satisfactory presentation to any analytical framework or approach that can be used to answer the business question. Satisfactory justification of why this analytical framework or approach can be effective in answering the business question. |
Limited mention of analytical framework or approach that can be used to answer the business question. Limited justification of why this analytical framework or approach can be effective in answering the business question. |
Weak/No mention to analytical framework or approach that can be used to answer the business question. Weak/No justification of why this analytical framework or approach can be effective in answering the business question. |
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2: Data quality issues and remedies (10 marks, LO2) |
Guidelines: • List and explain generic data problems and how to identify them. What are the different options for resolving these generic issues? • List all data problems you have identified in the Olympic Sports Ltd. dataset. Explain how you identified the problems (give examples of the issues) and how you propose to address/solve them. |
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Assignment task Distinction (70-100%) Merit (60-69%) Pass (50-59%) Low Fail (40-49%) Fail (0-39%) |
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Excellent identification of appropriate errors and explanation how they can be fixed. Student identifies some relevant errors in the database and give specific recommendation on how to solve them. |
Good identification of appropriate errors and good explanation how they can be fixed. Student identifies some errors and give recommendation on how to solve them. |
Satisfactory identification of appropriate errors and basic explanation how they can be fixed. Student has identified some errors. |
Limited identification of appropriate errors and weak explanation how they can be fixed. |
Weak/No identification of appropriate errors and weak explanation how they can be fixed. |
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3: Data analysis and commentary (20 marks, LO2) |
Guidelines: • Include summary exploratory data calculations for total sales value and volume. The analysis could include for example top and bottom performing sport product categories, ranges, averages, standard deviations; top and bottom performing time-periods, etc. • Ensure your tables are professionally presented: headings, units, data formats. Highlight and annotate key data elements • For each table include firstly an explanation of the table and its contents and then a bullet-point list of what you can see or infer from the analysis of the data. |
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Excellent use of tables to present the outcome of the data analysis run to reply to the business question. Commentary to tables is detailed. |
Good use of tables to present the outcome of the data analysis run to reply to the business question. Commentary on tables is good. |
Satisfactory use of tables to present the outcome of the data analysis run to reply to the business question. Commentary to tables is satisfactory. |
Limited use of tables to present the outcome of the data analysis run to reply to the business question. Commentary to tables is limited. |
Weak/No use of tables to present the outcome of the data analysis run to reply to the business question. Commentary to tables is weak/there is not. |
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4: Data charting and commentary (20 marks, LO3) |
Guidelines: • Ensure you provide well-presented and labeled charts • Use a combination of visualization plots and techniques such as bar charts, stacked bar charts, trend charts, pie charts and tree map charts • For each chart include firstly an explanation of the chart and its contents and then a bullet-point list of what you can see or infer from the data. |
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Excellent use of charts to present the outcome of the data analysis run to reply to the business question. Commentary to charts is detailed. |
Good use of chart to present the outcome of the data analysis run to reply to the business question. Commentary on charts is good. |
Satisfactory use of charts to present the outcome of the data analysis run to reply to the business question. Commentary to charts is basic. |
Limited use of charts to present the outcome of the data analysis run to reply to the business question. Commentary to charts is limited. |
Weak/No use of charts to present the outcome of the data analysis run to reply to the business question. Commentary to charts is weak/there is not. |
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Assignment task Distinction (70-100%) Merit (60-69%) Pass (50-59%) Low Fail (40-49%) Fail (0-39%) |
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5: Conclusions and recommendations (20 marks, LO3) |
Guidelines: • What conclusions can be inferred regarding Olympic Sports Ltd.’s subsidiaries sales performance and operations? Remember to include the answers to the three issues/questions raised by Olympic Sports Ltd. top management. • What are your business recommendations to Olympic Sports Ltd.’s CEO and top management? • Include any suggestions related to data analytics and it’s better use within the organisation. • Note that it is also acceptable to add to your data analytics recommendations, possible actions that Olympic Sports Ltd. might take, based not only on your findings but also on your wider knowledge of the business and sport apparel market sector. |
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Excellent summary of key insights and satisfactory answer to the business question. Excellent discussion of how the analysis can be improved and excellent presentation of concerns about how the analysis is done. |
Good summary of key insights and good answer to the business question. Good discussion of how the analysis can be improved and good presentation of concerns about how the analysis is done. |
Satisfactory summary of key insights and satisfactory answer to the business question. Basic discussion of how the analysis can be improved and basic presentation of concerns about how the analysis is done. |
Limited summary of key insights of the report. Limited discussion of how the analysis can be improved and weak presentation of concerns about how the analysis can be done. |
Weak/No summary of key insights of the report. Weak discussion of how the analysis can be improved and weak/no presentation of concerns about how the analysis can be done. |
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Report Structure and References (10 marks. Applies across all LOs tasks) |
Guidelines: • Your report should follow the section naming structure and order set out in the Brief. You should also add your own sub-headings as you see fit to demonstrate your ability to on-develop structure and content • Your report should include an auto-generated contents page including section headings and sub-headings. The contents page should also include a page-referenced list of all tables, charts and figures provided in our report. Remember to number all pages in your report, for example ‘Page 8 of 12’. • Ensure you develop your discussion in a logical progression: Findings, inferences, conclusions, recommendations • Do not make general assertions without supporting evidence • Zero spelling errors and grammatical mistakes • Cite all your sources in the body of the text and in the Referencing using the Harvard Referencing style • Include a blend of industry research, case studies and academic references. |
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Assignment task Distinction (70-100%) Merit (60-69%) Pass (50-59%) Low Fail (40-49%) Fail (0-39%) |
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For a distinction the report will use a consistent approach to headings, tables and graphs. Sources will be correctly cited and there will be a complete set of references in the correct format and in alphabetical order. There is evidence of extensive independent reading and research. Formatting and presentation is professional throughout. |
Referencing has few if any errors. The report is reasonably well presented but could be improved by greater attention to detail. There is evidence of wider reading and research. |
There is a satisfactory number of references, but the correct format is used, albeit with some errors. There may be some errors in formatting and presentation, but the report is reasonably professional in appearance. |
Limited research with inappropriate references. Limited professional appearance of report and slides |
Weak/No research with inappropriate references. No professional appearance of report and slides |
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5. Marking Guide (Tutor version)
Tutors: The assignment is marked out of 100 and counts towards 100% of the student mark.
The following table shows the tasks, marks and marking rubric. Please ensure you take account of the individual task marking structure for distinction, merit, pass and fail mark allocations.
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Assignment task Distinction (70-100%) Merit (60-69%) Pass (50-59%) Low Fail (40-49%) Fail (0-39%) |
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1: Introduction and project plan (20 marks, LO1, LO4) |
Guidelines: • State the purpose of report and describe the report structure and contents • Present your overall project plan for delivering the project • Ensure that your project plan explicitly refers to a data analytics project framework and explain how the selected framework can be used/applied to address the core three business questions assigned to you. • Suggest a list of Key Performance Indicators (KPIs) for Olympic Sports Ltd.’s subsidiaries and explain how better data analytics enables improvements against these KPIs. |
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Excellent presentation of an analytical framework or approach that can be used to answer the business question. Excellent justification of why this analytical framework or approach can be effective in answering the business question. (15-20 marks) |
Good presentation to any analytical framework or approach that can be used to answer the business question. Good justification of why this analytical framework or approach can be effective in answering the business question. (13-14 marks) |
Satisfactory presentation to any analytical framework or approach that can be used to answer the business question. Satisfactory justification of why this analytical framework or approach can be effective in answering the business question. (10-12 marks) |
Limited mention to analytical framework or approach that can be used to answer the business question. Limited justification of why this analytical framework or approach can be effective in answering the business question. (8-9 marks) |
Weak/No mention to analytical framework or approach that can be used to answer the business question. Weak/No justification of why this analytical framework or approach can be effective in answering the business question. (0-7 marks) |
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2: Data quality issues and remedies (10 marks, LO2) |
Guidelines: • List and explain generic data problems and how to identify them. What are the different options for resolving these generic issues? • List all data problems you have identified in the Olympic Sports Ltd. dataset. Explain how you identified the problems (give examples of the issues) and how you propose to address/solve them. |
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