Reference no: EM133105393

Data Driven Decisions for Business

Learning outcome 1: Critically evaluate the evolving use of data in solving business problems, presenting logical arguments based on evidence

Learning outcome 2: Explore how data analytics can be used within a business context

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

Learning outcome 4: Critically evaluate different business analytical techniques as part of planning a data analytics initiative.

Scenario

You have recently been employed as a data analyst in a consultancy called Wood From The Trees (WFTT). The consultancy was established 10 years ago and specialises in helping companies that don't have the skills available internally to analyse data to support business decision-making. WFTT has successfully established a strong reputation and it is now working with internationally recognised brands.

As WFTT expands, it continues to bring in new employees. The recruitment strategy is to employ less experienced people and give them the support and development they need to succeed in the company. They like recruits to have a broad management experience and not be specialist analysts, because they offer more commercially relevant and actionable recommendations.

As part of the approach to introducing you to how the company works WFTT has asked 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. The responses to requests detailed below should be included in a summary Microsoft Word report.

In your first week as a junior consultant you have been familiarising yourself with one of WFTT's major clients, Bangles International Jewellery (BIJ). BIJ operates in multiple country markets across the three continents of Asia, North America and Europe. It does not currently operate in Africa, South America or Australasia. Although a lot smaller, BIJ aims to compete against companies such as Signet, LVMH and Cartier. BIJ sells through a network of distributors and also owns a small number of signature stores in New York, London and Mumbai. It also owns concessions in major airport hubs.

Research objectives and tasks

Your line manager is happy with your performance and because you have familiarity with the BIJ data she has asked you to lead the next stage of the project. BIJ invested in a marketing campaign in the UK in May 2021. As part of this, the Director of Product & Marketing has commissioned WTTF to conduct data-driven research. The core business question that the Director wants you, as a business consultant to address is:

Did the marketing campaign have a positive impact on sales performance in the UK?

A set of data is available (see module dataset spreadsheet file).

Because this is your first client report for WFTT your line manager has given you additional details regarding the structure and content that she expects to see. This is set out in Section 3 - Report Structure.

You have five tasks to complete for your summative report. The first four 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

Summarise what you are going to present in the report and justify your plan for delivering the research project to BIJ. Ensure you also clearly reference a data analytics framework as part of your plan. Finally, specifically explain how data analytics can add value and drive improved business performance for BIJ.
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 framework and explain how the selected framework can be used to addresses the core business question to be answered in your consultancy project: Did the marketing campaign have a positive impact on sales performance in the UK?
• Present BIJ's own business Key Performance Indicators (KPIs) and how improved analytics enables improvements against these KPIs.

Task 2: Data quality issues and remedies
Discuss both the generic issues that data analysts encounter in sourcing, reviewing and cleansing data and also specific issues with the project data that BIJ 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 the data problems you have identified with the BIJ dataset. Explain how you identified the problems and how you propose to address them.

Task 3: Data analysis and commentary
Set out and explain the results of your numeric data analysis in the form of tables, summary data and supporting commentary. Explain how your results inform understanding of BIJ's performance and business operations. This should include three tables setting out:

(Table A) Data and trends in sales volume and value by month, by year and across the whole analysis period
(Table B) Benchmark comparisons of category performance covering sales volume and value by quarter, by year and across the whole analysis period, and
(Table C) Benchmark comparisons of sales volume and value between markets by quarter, by year and across the whole analysis period.

Guidelines:
• Include summary exploratory data calculations, for example trend data, top and bottom performing categories, ranges, averages, standard deviations; top and bottom performing time-periods
• 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 data.

Task 4: Data charting and commentary
Use your data charting and interpretation skills to develop visual presentations of your findings together with bullet-points setting out the key findings and inferences from the charting. This should include three charts presenting:

(Chart A) Comparison of sales value trends across markets over time (Chart B) Category performance comparisons between markets, and
(Chart C) Impact of the marketing campaign in the UK market itself, and in comparison, with other markets.

Guidelines:
• Ensure you provide well-presented and labelled charts
• Use a combination of visual data presentation techniques such as bar charts, stacked bar charts, trend charts, pie charts and treemap 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
Based on your analysis and findings in Tasks 3 and 4 set-out your conclusions and recommendations.
Guidelines:
• What conclusions can be inferred regarding BIJ's business performance and operations?
• What are your business recommendations to BIJ Board?
• Note that it is acceptable here also to put forward possible actions that BIJ might take, based not only on your findings but also on your wider knowledge of business, BIJ's own market sector and business data analytics.

3. 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)

Attachment:- Data Driven Decisions for Business.rar