In the introduction, the nature of data will be discussed, outlining what we mean by data, exploring what data might be needed, and examining the sharing and curating of data. There will be an initial focus on research, understanding how data might be interpreted and investigating how data can be used and communicated.
Following the introduction, students will be introduced to research techniques, arming students with a grammar and vocabulary with which to approach both the remainder of the module and their dissertation. In this section of the module there will be some consideration of research philosophy, concentrating on epistemology and encouraging students to consider what might constitute valid and reliable data, including data collection tools and associated issues. This will lead into considering specific data types, including a discussion of statistical confidence and some examination of both descriptive and inferential statistics. This module will equip students with the tools to collect, analyse and report data, both quantitative and qualitative. The module will also provide the opportunity for students to write their proposal for their dissertation or project proposals formally assessed before the start of the dissertation or company project module in the summer. This design support students to start to plan for their final project during semester 2 and culminating with a proposal by the end of the semester.
The third part of the module will seek to examine research in business applications with a specific focus on SCM applications. Here, students will learn about KPIs and their use (and misuse) and the way data can be linked to business drivers.
Students will also be introduced to the ways in which data might be shared throughout the supply network and consider the risks and benefits of this. In discussing data sharing and decision-making, the module will bring in the final part around technologies employed in better managing the supply chain, such as RFID and EDI. The module will also touch on new and emerging technologies and their applications such as the Internet of Things (IoT), Blockchain, AI and machine learning and robotics and automation. The module will mix theoretical underpinnings with practical applications and technical skills. There will also be a clear scope for criticality, particularly in the latter parts of the module.
Learning Outcomes
By the end of the module students should be able to:
Critically examine the different forms of data and their relevance to research and SCM applications.
Critically discuss epistemology within the context of research and decision-making.
Apply technical skills required to manipulate different forms of data to inform decision making or research conclusions.
Use literature to inform the design of a research or business project
Apply qualitative and quantitative data analysis to inform decision making or research conclusions.
Define a research or project proposal problem, including searching for relevant sources, critically evaluating and synthesising material and data that can be taken both into a research context and a business setting.
Design and plan an independent research project, including the selection of appropriate research methods, which will allow research objectives to be met within a given timeframe.
Critically examine the use of data in a supply chain context through practical application to cases and examples.
Critically analyse how technologies can be used to gather, sift and curate data in order to tackle demand and supply problems that are found in supply networks.
Assessment
Assessment Methods & Exceptions
Assessment:
Assessment: Individual Research or Company Project proposal. (1500 words - 50%) Individual Essay (2000 words – 50%).