Course Code: SCM307
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Synopsis

The enablers function in supply chain management (SCM) is essential in equipping different functions with digital capabilities and data analysis to enhance efficiency. SCM307 Supply Chain Analytics and Modelling examines the methodologies and tools used in analysing and optimising supply chain processes. Learners will engage with both theoretical concepts and practical applications, beginning with an overview of analytics in the context of SCM. Key topics include data collection and analysis techniques which form the foundation for effective decision-making. The course delves into predictive and prescriptive models that aid in forecasting and strategic planning as well as linear programming models for resource optimisation. Students will also learn about decision analysis and descriptive models to understand supply chain dynamics and performance metrics. The course emphasises simulation concepts and tools, allowing students to create simulation models that address real-world supply chain challenges. By the end of the course, students will gain practical skills in applying analytics and modelling techniques to solve complex supply chain problems, equipping them with the knowledge and skills necessary to enhance efficiency and drive innovation in supply chain operations.
Level: 3
Presentation Pattern: EVERY JAN

Topics

  • Supply Chain Analytics and Modelling in Practice
  • Supply Chain Analytics Concepts
  • Data Collection and Analysis
  • Predictive Models
  • Prescriptive Models
  • Linear Programming Models
  • Decision Analysis
  • Descriptive Models
  • Simulation Concepts and Tools
  • Simulation Modelling
  • Simulation for Supply Chain Problem
  • Applications of Supply Chain Analytics and Modelling

Learning Outcome

  • Show how supply chain analytics and modelling concepts are applied in practice to assess supply chain performance and support decision-making.
  • Examine data collection and analysis techniques used for extracting, processing, and analysing supply chain data to support decision-making.
  • Appraise the role of technology in implementing supply chain models to improve process efficiency and visibility.
  • Apply data analytics and modelling methods to uncover patterns, predict outcomes, and develop optimised solutions for supply chain challenges.
  • Construct simulation models to evaluate supply chain problems, enabling scenario analysis and improving operational decision-making.
  • Analyse strategies that reduce environmental impact and promote sustainability within the supply chain.