Data Driven Decisions in Business Summative Brief Student Version - CW3

BPP Business School  Coursework Cover Sheet :- Please use this document as the cover sheet for the 1st page of your assessment. Please complete the below table – the gray columns 

Module Name 

Data driven Decisions for Business

Programme Name 

MSc Management

Student Reference Number  (SRN)

Your SRN

Assessment Title 

Your assessment title [CW3(S)]

 

Please complete the yellow sections in the below declaration :

Declaration of Original Work:  

I hereby declare that I have read and understood BPP’s regulations on plagiarism and that this is my original work,researched, undertaken, completed and submitted in accordance with the requirements  of BPP School of Business and Technology.  

The word count, excluding contents table, bibliography and appendices, is ______ words.  Student Reference Number: __________ Date: ______ 

 

By submitting this coursework you agree to all rules and regulations of BPP regarding assessments  and awards for programmes.  

Please note that by submitting this assessment you are declaring that you are fit to sit this  assessment.  

BPP University reserves the right to use all submitted work for educational purposes and may  request that work be published for a wider audience.

Msc Management Data driven Decisions for Business Coursework Assessment Brief [CW3(S)] 

1. General Assessment Guidance

 • Your summative assessment for this module is made up of this 2500 submission which accounts  for 100% of the marks

Please note late submissions will not be marked. 

You are required to submit all elements of your assessment via Turnitin online access. Only  submissions made via the specified mode will be accepted and hard copies or any other digital  form of submissions (like via email or pen drive etc.) will not be accepted

For coursework, the submission word limit is 2500 words. You must comply with the word count  guidelines. You may submit LESS than 2500 words but not more. Word Count guidelines can be  found on your programme home page and the coursework submission page. 

Do not put your name or contact details anywhere on your submission. You should only put your student registration number (SRN) which will ensure your submission is recognised in the  marking process. 

A total of 100 marks are available for this module assessment, and you are required to achieve a minimum 50% to pass this module. 

You are required to use only the Harvard Referencing System in your submission. Any content which  is already published by another author(s) and is not referenced will be considered as a case of  plagiarism. 

You can find further information on Harvard Referencing in the online library on the VLE. You can  use the following link to access this information: 

BPP University has a strict policy regarding the authenticity of assessments. In proven instances of  plagiarism or collusion, severe punishment will be imposed on offenders. You are advised to  read the rules and regulations regarding plagiarism and collusion in the GARs and MOPP which  are available on VLE in the Academic registry section. 

You should include a completed copy of the Assignment Cover sheet. Any submission without this completed Assignment Cover sheet may be considered invalid and not marked.

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.

Learning Outcome 

Mapping to Summative Assessment Tasks

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

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

LO 3: Critically appraise the presentation  of data within a business environment

Task 4: Data charting and commentary

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.

Assignment task Distinction (70-100%) Merit (60-69%) Pass (50-59%) Low Fail (40-49%)  Fail (0-39%)

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.

 

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.

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.

 

Assignment task Distinction (70-100%) Merit (60-69%) Pass (50-59%) Low Fail (40-49%)  Fail (0-39%)

 

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. 

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.

 

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.

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.

 

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.

 

Assignment task Distinction (70-100%) Merit (60-69%) Pass (50-59%) Low Fail (40-49%)  Fail (0-39%)

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.

 

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.

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.

 

Assignment task Distinction (70-100%) Merit (60-69%) Pass (50-59%) Low Fail (40-49%)  Fail (0-39%)

 

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

 

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.

Assignment task Distinction (70-100%) Merit (60-69%) Pass (50-59%) Low Fail (40-49%)  Fail (0-39%)

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.

 

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)

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.

 

Assignment task Distinction (70-100%) Merit (60-69%) Pass (50-59%) Low Fail (40-49%)  Fail (0-39%)

 

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. 

(7-10 marks)

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. 

(6 marks)

Satisfactory identification of  appropriate errors and basic  explanation how they can be  fixed. Student has identified  some errors. 

(5 marks)

Limited identification of  

appropriate errors and weak  explanation how they can be  fixed.  

(4 marks)

Weak/No identification of  appropriate errors and  weak explanation how  they can be fixed.  

(0-3 marks)

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.

 

Excellent use of tables to  

present the outcome of the  data analysis run to reply to  the business question. 

Commentary to tables is  

detailed. 

(15-20 marks)

Good use of tables to present  the outcome of the data  

analysis run to reply to the  business question. 

Commentary on tables is good. (13-14 marks)

Satisfactory use of tables to  present the outcome of the  data analysis run to reply to  the business question. 

Commentary to tables is  

satisfactory. 

(10-12 marks)

Limited use of tables to  

present the outcome of the  data analysis run to reply to  the business question. 

Commentary to tables is 

limited. 

(8-9 marks)

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. 

(0-7 marks)

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.

 

Assignment task Distinction (70-100%) Merit (60-69%) Pass (50-59%) Low Fail (40-49%)  Fail (0-39%)

 

Excellent use of charts to  

present the outcome of the  data analysis run to reply to  the business question. 

Commentary to charts is  

detailed. 

(15-20 marks)

Good use of chart to present  the outcome of the data  

analysis run to reply to the  business question. 

Commentary on charts is good. (13-14 marks)

Satisfactory use of charts to  present the outcome of the  data analysis run to reply to  the business question. 

Commentary to charts is  

satisfactory. 

(10-12 marks)

Limited use of charts to  

present the outcome of the  data analysis run to reply to  the business question. 

Commentary to charts is  

Limited. 

(8-9 marks)

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. 

(0-7 marks)

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 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.

 

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.  

(15-20 marks)

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.  

(13-14 marks)

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. 

(10-12 marks)

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. 

(8-9 marks)

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. 

(0-7 marks)

 

Assignment task Distinction (70-100%) Merit (60-69%) Pass (50-59%) Low Fail (40-49%)  Fail (0-39%)

Report Structure and  

References (10 marks. Applies  across all LOs and 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.

 

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.  

(7-10 marks)

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.  

(6 marks)

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.  

(5 marks)

Limited research with  

inappropriate references. Limited professional  

appearance of report and  slides 

(4 marks)

Weak/No research with  inappropriate references. No professional  

appearance of report and  slides 

(0-3 marks)