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Managing the Global Supply Chain and Sustainability
2,500 words
Managing the Global Supply Chain and Sustainability – Individual Company Case Analysis
This assessment is an individual company case analysis for the Level 7 module Managing the Global Supply Chain and Sustainability. Students are required to select a real organisation of any size, type, industry or country and produce a comprehensive analysis of one operations performance objective. The available performance objectives are cost, dependability, flexibility, speed and quality. The report should identify current issues faced by the chosen organisation in relation to the selected objective and critically analyse the factors affecting its performance. Students are expected to apply relevant theories, concepts and tools covered during lectures and seminars to the selected company case. Rather than providing only descriptive explanations of theoretical concepts, the assessment requires students to demonstrate how these concepts can be applied to understand the organisation's operational or supply chain challenges. The analysis should consider how relevant theories, models or tools could contribute to improving the company's performance. The report should also provide a critical discussion of appropriate performance-improvement practices. These may include the use of digital technologies, sustainability practices, supply chain strategies, operational approaches or other relevant methods. Students should relate these practices directly to the findings from their chosen company case and consider their practical implications. Academic evidence and real-world examples should be used to support the analysis, with appropriate attention given to supply chain and operations management literature. The assessment is designed to develop students' ability to understand supply chain strategies, assess their contribution to agility, viability and sustainability, propose practical solutions to modern logistics and supply chain challenges, and evaluate how digital technologies and sustainability practices can improve supply chain performance. The report should therefore demonstrate analysis, application of theory, critical evaluation and evidence-based recommendations rather than simply describing the organisation or its supply chain. The individual report has a maximum length of 2,500 words, excluding references, tables, figures and appendices. It must include a contents page, be spell-checked and follow the specified formatting requirements. The report should use Arial 12-point font, 1.5 line spacing, A4 page size and 2.54 cm margins. Academic sources such as journal articles and books should be used, and all sources cited within the report must appear in a Harvard-style reference list. The report is submitted through Moodle Turnitin as a Word document.
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Fundamentals of Digital Technologies
Fundamentals of Digital Technologies – Group Project and Individual Refinement
This assessment is a project-based assignment for the DG4FDTL Fundamentals of Digital Technologies module. It is designed to develop students' practical understanding of digital technologies by combining mathematical concepts, programming, algorithms, data analysis and learning methods within a real-world project. The project is structured around a common group component, known as the Group Trunk, and an individual component in which each student develops a specialised refinement of the shared project. The project topics are designed around key areas covered by the module, including linear algebra, calculus, probability, learning algorithms, algorithms and Python programming. Students work in groups to establish a common project foundation and then develop an individual refinement that extends the functionality or analytical capabilities of the shared system. The project guidance is intended for a mixed cohort that may include Data Science, Computer Science and Business Analytics students. The assessment is divided into two main components: Proposal and Implementation. The Proposal accounts for 40% of the assessment, while Implementation accounts for 60%. Both the group trunk and individual trunk contribute to the assessment. The group proposal requires students to describe what the group intends to build, explain the problem being addressed, outline the proposed approach and identify the main functions and responsibilities within the project. Students should demonstrate a clear understanding of the project objectives and provide an appropriate plan for developing the shared system. The implementation stage requires students to develop the common group functionality and then complete their individual refinement. The shared component provides the basic project framework, while the individual refinement allows each student to investigate a specific aspect of the problem and add specialised functionality. Depending on the selected project topic, individual refinements may involve data analysis, visualisation, optimisation, prediction, monitoring, reporting or other computational features. The project topics include practical applications such as productivity and task-management systems, supermarket sales analysis and other data-driven applications. Students are expected to use Python and appropriate libraries or computational techniques to implement their solutions. The project materials provide examples involving data structures, CSV files, functions, numerical calculations, visualisation and analytical dashboards. The assessment emphasises both technical implementation and the student's ability to explain the problem, approach and functionality of the developed system. Students should demonstrate appropriate use of programming concepts, mathematical foundations, algorithms and data-analysis techniques. The individual refinement should clearly extend the common project and demonstrate the student's own contribution to the overall solution. Overall, the assessment develops practical digital-technology skills through collaborative project development followed by individual technical refinement. It provides experience in project planning, programming, computational problem solving, data analysis, visualisation and the application of mathematical and algorithmic concepts to practical problems.
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Consultancy Project
1,464 words
Enhancing Sustainable Supply Chain Practices through Digital Transformation: A Case Study of Unilever Plc
This consultancy project proposal examines how digital transformation can enhance sustainable supply chain practices at Unilever Plc. Unilever is presented as a multinational fast-moving consumer goods organisation operating across more than 190 markets, with a complex global supply chain and sustainability commitments linked to the United Nations Sustainable Development Goals. The proposal focuses on the challenges associated with achieving supply chain transparency, managing fragmented sustainability data, and balancing sustainable sourcing and operational costs. The project investigates how emerging digital technologies, particularly blockchain, the Internet of Things (IoT) and Artificial Intelligence (AI), could support greater transparency, traceability, operational efficiency and sustainability within Unilever's supply chain. The organisational analysis identifies issues including the complexity of tracing raw materials across multi-tier supply chains, fragmented procurement and sustainability information systems, and the tension between sustainability investments and short-term operational costs. The proposal also considers infrastructure readiness, data security and employee upskilling as factors affecting digital transformation. The research aims to examine how digital transformation technologies could improve sustainable supply chain planning at Unilever while supporting long-term business and environmental goals. Three objectives are established: examining sustainability challenges affecting Unilever's global supply chain, assessing how blockchain, IoT and AI could improve transparency, traceability and efficiency, and proposing strategic recommendations for integrating digital innovation into Unilever's sustainability framework. The central research question examines how digital transformation can contribute to an ethical, transparent and sustainable supply chain while maintaining operational efficiency. A qualitative exploratory case-study research design is proposed. The main emphasis is on secondary data, including Unilever's annual reports, sustainability information, digital transformation publications, company news, industry articles and analyst reports. Where feasible, primary data may be collected through semi-structured expert interviews and a short qualitative questionnaire. The proposed analysis includes thematic analysis, document review and descriptive statistics using relevant secondary numerical data. Validity is supported through triangulation, while reliability is addressed through consistent coding and an audit trail. The proposal also addresses ethical considerations, including research integrity, transparency, confidentiality, informed consent, anonymity, GDPR requirements, plagiarism avoidance, Harvard referencing and potential corporate bias or greenwashing. Overall, the project explores the potential contribution of digital innovation to Unilever's sustainability objectives and the wider responsible digitalisation of the FMCG supply chain.
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Computing and Digital Technologies
3,000 words
Contemporary Computing and Digital Technologies: AI Agents Hackathon Reflective Report
This postgraduate reflective assessment forms part of the Contemporary Computing and Digital Technologies module and is based on experiential learning undertaken through an AI-focused hackathon. The hackathon theme, “AI Agents Unleashed – Building the Future of Automation,” requires MSc students from computing-related disciplines to collaborate on intelligent agent-based solutions capable of automating complex tasks, solving real-world problems and supporting human decision-making. The hackathon encourages students to investigate agent-based system design, intelligent automation and responsible AI development. Potential applications include autonomous cybersecurity monitoring, multi-agent systems for information gathering and decision support, automated data pipelines, intelligent software-development assistants, and conversational systems such as virtual tutors or career coaches. Students may use code-based approaches or platforms such as Flowise, Microsoft Power Automate and Make.com, while more advanced implementations can use technologies including LangChain, AutoGen, Python-based agent SDKs, APIs and large language models. The 3,000-word Individual Reflective Report, worth 70% of the module assessment, evaluates the student's learning and professional development arising from these experiential activities. The first component is a 2,000-word Portfolio of Evidence, requiring evidence-based reflection on participation in the hackathon. Students should evaluate their leadership and teamwork competencies using concrete evidence such as screenshots, code commits and feedback while identifying key lessons for personal and professional development. They must also consider how the experience applies to future research, career development or professional practice. The remaining 1,000 words comprise a Critical Self-Reflection examining the student's personal contribution and achievement of learning-contract goals. Students are expected to critically consider challenges encountered, how those challenges were addressed, lessons learned and their development as effective collaborative team members. Overall, the assessment integrates technical experimentation, reflective practice, teamwork, leadership, professional development and responsible use of emerging AI technologies, supported by a structured portfolio of evidence
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Global Supply Chain Management / Operations Management
2,494 words
Global Supply Chain and Operations Performance: Company Case Analysis
This Level 7 individual assignment requires students to produce a 2,500-word company case analysis examining an important operations performance issue within a real organisation. Students may select an organisation of any size, type, industry or country and must concentrate their analysis on one operations performance objective: cost, dependability, flexibility, speed or quality. The report requires students to identify the current challenges faced by the chosen organisation in relation to the selected performance objective and critically examine those challenges using relevant operations and supply chain management theories, concepts and analytical tools. Rather than providing only a descriptive account of organisational activities, students are expected to apply appropriate theoretical frameworks to the case and evaluate how these concepts could contribute to improved organisational and supply chain performance. A significant component of the assignment involves critically discussing appropriate best practices for performance improvement. These may include digital technologies, sustainability practices or other relevant operational and supply chain approaches. Students should connect these practices directly to findings from their chosen company case and assess their practical relevance, opportunities and limitations. Academic literature and appropriate real-world evidence should be used throughout to substantiate the analysis and recommendations. The assignment evaluates students' ability to analyse supply chain and operations problems, apply academic theory to organisational practice, and develop evidence-based conclusions and practical recommendations. The marking rubric places substantial emphasis on analysis and discussion (30%), application of theory (30%), and conclusions and recommendations (30%), with the remaining 10% allocated to presentation, logical structure, English expression and correct referencing. The report must use Harvard referencing, include a contents page, and follow the specified academic formatting requirements, including Arial size 12, 1.5 line spacing and A4 pages with 2.54 cm margins.
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