Analytics for Supply Chain & Operations (MGMT30020)

Undergraduate level 3Points: 12.5Not available in 2025

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Overview

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This subject focuses on quantitative models for informing supply chain and operational decisions.  It explores techniques for how organisations can more effectively deploy operational and supply chain modelling using analytics to evaluate and analyse real time data to gain insights from them, including: demand forecasting, newsvendor optimal ordering, bullwhip effect and supply chain optimal ordering, optimizing production planning, queuing, and staff allocation. The subject will also equip students with the ability to apply big data analytic techniques and effectively communicating insights from their analyses with non-expert decision-makers and stakeholders (suppliers, customers, managers).

Intended learning outcomes

On successful completion of this subject, students should be able to:

  • Understand major analytics frameworks and tools for supply chain and operations management;
  • Develop analytics models for forecasting and optimising supply chain and operations processes;
  • Critically analyse problem context relevant to supply chain and operations and develop analytics model corresponding to the problem; and
  • Use unstructured data, large datasets through advanced analytics to identify points of improvement in supply chains and operations.

Generic skills

On successful completion of this subject, students should have improved the following generic skills:

  • High level skills in: problem solving; statistical reasoning; application of theory to practice; synthesis of data and information; evaluation of data and other information; use of computer software; accessing data and other information from a range of sources.
  • Moderate level skills in: written communication; critical thinking; receptiveness to alternative ideas; collaborative learning; team work. 

Last updated: 4 March 2025