Module BUSI4AM15: Supply Chain Analytics

Department: Management and Marketing

BUSI4AM15: Supply Chain Analytics

Prerequisites

• Data Science for Business (BUSI4X915)

Corequisites

• None.

Excluded Combination of Modules

• None.

Aims

• To provide an appreciation of how analytics can provide supply chain managers with decision support
• To provide knowledge of, and ability to apply, a range of analytics techniques to aid decision making across different supply chain processes

Content

• Overview of analytical tools used for supply chain decision making
• Optimization models for supply chain network design
• Analytical tools for customer segmentation and demand planning
• Optimal sourcing decisions
• Inventory Planning and analytics
• Optimal production planning and scheduling
• Distribution and logistics planning
• Overview of supply chain risk analytics
• Machine Learning applications for supply chain planning

Learning Outcomes

• Upon successful completion of the module, the students should:
• Develop critical understanding of the relevant analytical and scientific techniques to plan and manage supply chains
• Develop specialised knowledge of the relevant analytical techniques to plan and manage supply chains to improve supply chain performance

• Upon successful completion of the module, the students should be able to:
• Visualise supply chain data
• Critically analyse supply chain data using appropriate analytical tools, and develop data-driven recommendations to improve supply chain performance

• Effective written communication skills
• Planning, organising and time-management skills
• Problem solving and analytical skills
• Data presentation and visualisation, interpreting and using data
• Making effective use of communication, information technology and other digital technologies

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• On-site teaching will typically include a mix of taught input, group work and discussion, use of case studies to emphasize real-world applications, and industry-informed sessions. Online learning will be divided into study weeks and will typically include activities facilitated by the teaching team and specially produced resources. Facilitated activities will make use of a range of educational technologies to include digital collaboration spaces and live online sessions. Learning resources vary according to the learning outcomes but typically include: video content, directed reading, reflective activities and opportunities for self-assessment.
• The summative assessment comprises online assessments and a written assignment which will test students’ theoretical understanding, their knowledge of relevant techniques and types of analysis and their ability to apply these to a particular, real-world context.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

The formative assessment serves to encourage students to study regularly and to monitor their learning progress. Students will undertake a series of activities aligned to the module content, which can include group presentations, individual or group reflections on specific topics receiving ongoing feedback on theoretical knowledge and how it is applied. Tutors provide feedback on formative work and are available for individual consultation as necessary (usually by email and video call).

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University