OIM7504-B Supply Chain Analytics and Technology Management Coursework Assignment Brief 2026 | Bradford

DEPARTMENT

Business Analytics, Circular Economy and Entrepreneurship

MODULE TITLE

Supply Chain Analytics and Technology Management

MODULE CODE

OIM7504-B

TYPE OF ASSESSMENT

Coursework – counts for 40% of the module mark 

Instructions for Students (University Rules)

Your essay is an opportunity to demonstrate your understanding of key concepts and debates covered in this module, and to show your progress in developing core academic research and writing skills. You will be assessed on five main criteria: structure – how well you have organised your writing and material; knowledge – the quality and depth of your understanding of the topic; critical thinking – how well you handle and engage with concepts or ideas that are debated; writing and expression – your ability to communicate knowledge and ideas clearly and concisely; and academic integrity standards – the quality of your referencing and bibliography. A marking rubric is available in Canvas which explains these criteria and how they will be applied.

The referencing style used at Bradford University is Harvard. You can find guidance on referencing here: Referencing and Plagiarism - Help - University of Bradford

Please use Arial font, size 12. Text should be double-spaced.

Submission of the essay will be via Canvas. A submission link will be set up within the Assessment folder. Your essay should be submitted as a Word document.

Work that is over the stated word length will attract a penalty in proportion to the additional words (e.g. 5%). Please do not make it unnecessarily long, try to be concise and focused.

All submissions are checked by Turnitin plagiarism detection software. A separate link in Canvas allows you to review your essay prior to submission. Please note that there is no permitted Turnitin score percentage. You should focus on ensuring your essay meets the university guidelines for referencing and academic integrity: What is plagiarism? - Find out about - University of Bradford

If you have any questions about this assignment, please speak with your module leader in good time before the deadline.

Please ensure you allow enough time for completing your work. Avoid submitting it very close to the deadline in case of technical issues (e.g. broken Wi-Fi). It is your responsibility to ensure you submit the correct file and on time.

Assignment Background

Throughout the course you have learnt about the importance of data and use of analytics for the performance of the SCs. Today many companies and supply chain networks make remarkable improvements thanks to the analytics used in several functions of SCs. In this assignment you are asked to analyse a data set by employing the analytics you learned in the module.

Assignment Outline

· Define a hypothetical supply chain issue or find a real-life case and propose research question(s) to analyse your case.

· If real data is available for your research questions, use the real data. If not, find a data set from an external source (e.g. https://ec.europa.eu/eurostat/web/main/data/database, https://www.data.gov.uk/, Refinitiv (available for UoB students), FAME (available for UoB students), https://www.statista.com/ (available for UoB students), …) suitable for your research questions.

· Analyse the data set by employing the data analytics you learned in the module.

· Before starting your analysis, make sure to get familiar with the data set. Check the variables available in the data set, understand what they denote, check the data types of the variables, etc.)

· Conduct your analysis in R.

· Please focus your analysis on your research questions. Please do not calculate any analytics only for the sake of increasing the number of your analytics in your coursework. Choose and calculate only the relevant analytics for your research question.

· Interpret your findings and answer your research questions.

· Your coursework needs to include 2000 words in total (excluding R code to be included in Appendix and references). Please do not exceed this word count.

Your coursework needs to include:

A)  Introduction – Explanation of your supply chain issue and formulation of research questions (30%)

· Describe your hypothetical supply chain issue or real-life case (5%).

· Explain why the issue/problem is important for businesses, benefit from previous studies (literature) to discuss the importance of your case (10%).

· Formulate your research question(s) clearly (at most 3 research questions) (10%).

· Briefly discuss how these questions can be answered. Which analytics may help? How can they help? What type of analysis should be conducted to help the company? Describe the analytics or the statistical tests you choose to use (5%).

B)   Data description (15%)

· Describe your data set.

· Explicitly provide your data source (3%).

· Define the variables that you will use in your analysis (7%).

· Provide the scales of measurement, units, time scales for these variables (5%).

C) Data Analysis and Findings - Presentation and interpretation of data analysis to address your research questions (40%)

· Calculate and present descriptive statistics (for the variables that you use) and report these in a table and interpret them in the text (5%).

· Describe your analysis steps, conduct your analysis, and calculate the analytics you have proposed in Part A using R codes. Present your findings in tables/figures/plots within the text (main body of the coursework). Do not forget to conduct only the relevant analysis for answering your research questions (15%).

· Interpret all of your findings, provide explanations, discuss how your research questions are answered (10%).

· Conduct the analysis in R. Build your own codes for your data set and analytics.

· Leave key R codes as text in the Appendix (not as images) (use Consolas) (10%)).

D) Conclusions – Implications/Recommendations based on insights from your analysis (15%)

· After presenting the findings, provide a discussion on the overall implications of your findings for the business (“So what?”).

· Provide recommendations based on your findings.

· Further support your statements based on the literature (recommended).

The coursework must be submitted via the Canvas "Assignments" section. The deadline date for this assignment will be released on Canvas in due course.