Assessment Descriptor

Module: ITAO7109 – Analytics with Artificial Intelligence

Semester:  January to April 2025

Assignment: Individual Report on Country-Level Performance

Submission: before Monday 4^th April December 2025 23:59 hrs

Word count: 3,000 (excluding references and appendices)

P.S. This module is assessed 100% by an individual written project. Please also note that the dataset that has been given to be used for this assessment is based on an available dataset downloaded for Educational purposes from a well-known source Kaggle. The module teaching team does not own the data set and hence, cannot comment on the accuracy of data or can be held liable for any misinformation that might be presented in the dataset. This is only to be used for educational purposes.

A multinational company (mostly operating based in the UK and ROI) is now considering expanding its business to many other EU countries and the rest of the world. However, any global business venture has a wide variety of challenges/implications that need to be addressed by proper risk-benefit planning. This requires a thorough assessment of country-level performance in terms of global economic factors such as GDP, and Import/Export among others. The dataset provided has many such variables with a vast pool of data. Based on this dataset, Students are asked to produce a report of 3000 words (+/- 10%, excluding appendices and reference list) based on the following information.

Assessment Task

In the first stage of the project, the company would like to better understand the country-level performance. The company currently uses Excel for reporting, but the insights generated are a little less interactive for them. Hence, they would also like to understand how more advanced dashboarding tools can be used to support decision-making. They have therefore asked you to develop a dashboard and analysis as an initial proof of concept that can be presented to the board. They would also like you to provide a written summary of the insights gained from the dashboard.

The company has also heard about more advanced business analytics in the media, but they do not have expertise in this area. They are interested in understanding more about this area and whether there are opportunities to apply more advanced analytics in their business. They do not want you to implement this yet as they are unsure about the value. As a consultant, you are keen to promote this as a potential follow-on project, and will therefore discuss the opportunities and challenges of this in the final report.

The technical and written tasks that you should carry out are detailed below:

Part 1 (20% of the overall Marks):

Using the relevant software, carry out an exploratory analysis of the data. You should produce at least five visualisations and a country-level performance dashboard for senior supply chain managers, and potentially for other business users. Include any relevant visualisations and the final dashboard in your report.

Part 2 (30% of the overall Marks):

After the initial stage, the company would like to explore the use of predictive analytics to help the organisation to examine how the country’s economy is performing based on various indicators and where the country will be in the future in terms of its economic performance so that they can plan on business expansion/development decisions. To do this they would like you to build a model to predict country performance. They would also like to gain insights into the factors that may be contributing to the county’s economic performance and what they should do about it.

Part 3 (20% of the overall marks)

In this part of the project, you are expected to use a generative AI tool (discussed in the class) for conducting a descriptive analysis of the data.

Part 4 (30% of the overall marks)

This is the final part of the project. In this part, you will use a tool with automated machine learning features (discussed in the class) for conducting predictive analytics. You will run various models and select the best model.

After conducting these analyses, you will submit a report.

The maximum word count for the assignment is 3000 words (excluding tables, figures, references and appendices). Students will be penalized for exceeding the word count by more than 10%. Harvard referencing style. should be used. Students are required to submit the assignment via CANVAS by 11:59 pm on 4^th April 2025. Students must submit the written report along with screenshots/exported images of the dashboard, visualisations, and outputs from various tools.

The written report should cover the following areas (but is not limited to these):

1. Background Introduction: Provide an overview of the business problem. Where appropriate include references to the wider literature.

2. Analysis, results and discussion:

a) Discuss the design of the solution, providing a brief description of the analytics tasks undertaken and reasons why these were used.

b) Present the results from the visualisation of the data and from the predictive model.

c) Also compare the results from parts 1-4, and critically examine if the findings from different parts are similar or different, and together what they imply.

3. Concluding Remarks:

a) Implications: Consider the main implications of the project for both theory and practice. Consider any limitations of the project.

b) Recommendations:

· Drawing on the analysis and wider literature, provide recommendations that the company could take to expand into the global market.

· Drawing on the wider literature, summarise the benefits and limitations of advanced analytics, and recommend a project for follow-up work.

4. List of References: This should be listed following a Harvard style. Please refer to the University’s library website for more information on Harvard Referencing.

5. Appendices: In the appendices, you may choose to include some of the software outputs/screenshots. If you chose to furnish your screenshots here, you need to signpost that in your main report where to find those.

In addition, the individual assignment will be assessed using the postgraduate conceptual marking scale as recommended by the University (as outlined in Appendix 1 and the Queen’s Management School Postgraduate Student Handbook for further information).

The following criteria are also considered when assessing the assignment:

· Demonstrate wide reading and understanding of the assignment task

· Ability to synthesise and critically evaluate relevant material

· Quality and relevance of evidence/example presented to support position/claims

· Structure including planning, organising, flow and coherence

· References – quality of citations and correct style. used

· Overall presentation

Please note that the School has a number of policies governing the submission of student work. For all elements of assessment associated with this course, you must be familiar with the School’s policies on:

· ‘Participation, Preparation for Classes and Private Study’;

· ‘Preparation and Submission of Assessed Work’; and

· ‘Plagiarism, Collusion and Fabrication’.

These policies are detailed in the Queen’s Business School Postgraduate Student Handbook.

Appendix 1: Conceptual Equivalents Scale Postgraduate