Supply Chain Analytics and Information Management
- How big data and predictive analytics capability may help improve the supply chain performance?
The assignment will be assessed via a written report (100% of the marks of the module).
You are required to write a report of no more than 4,000 words (excluding appendices, references and bibliography lists).
Choose a topic that is relevant to Operations and Supply Chain Management with special emphasis on understanding the role of emerging technologies like big data analytics capability, Block Chain technology, Internet of Things, Drone technology, Cyber security, Visualisation, and other applications of information technology in improving supply chain performance.
Besides choosing a topic, you also need to find and discuss the case study of a company engaged with the topic you have selected. The case study needs to be contained in an academic journal or publication such a published book.
Structure, Assessment Criteria and Learning Outcomes
Your report should be structured as follows. The assessment criteria and the assessed learning outcomes are also reported below.
|1. Introduction||Appropriateness and clarity of the definition and description of the topic, motivation on how the topic is relevant for theory and practice||20%||LO1, LO2, LO4, LO5|
|2. Literature review||Appropriateness and criticality of the literature review||25%||LO1, LO3|
|3. Case company description||Appropriateness and clarity of the presentation of the case company and how it engages with the chosen topic||10%||LO2, LO3|
|4. Challenges and benefits for the case company||Appropriateness and criticality of the discussions on the challenges and benefits for the case company||15%||LO2, LO3, LO5|
|5. Discussions: implications to the theory, implications to the practice and further scope of the study||Appropriateness and quality of the synthesized lessons learned||15%||LO1, LO3, LO4, LO5|
|Overall Quality||Quality of language and presentation of the report produced||15%||LO1- LO4|
Please note that all sources, whether academic or practitioner, must be properly cited and referenced using the Harvard Referencing Style.
The module has the following Learning Outcomes:
- LO1: Demonstrate a systematic understanding of relevant theories at the forefront of the discipline that contribute to supply chain analytics
- LO2: Critically and originally assess the role of information management and relevant technologies in supply chains working individually and in groups
- LO3: Exhaustively apply capabilities and skills in advanced quantitative methods, including big data, text mining, social media mining, data quality and cleansing, data visualisation and neural networks
- LO4: Formulate critical solutions to problems through the application of modelling techniques that rely on statistical software packages in an original and self-directed way
- LO5: Critically debate and analyse how data scientists/supply chain analysts create supply chain value through an appropriate management of information and data