1 x 3-hour workshop weekly
18 units of BUSN topics
Assignment(s), Test(s), Quizzes
Topic description

Use of information and data analytical tools help managers to more efficiently and effectively design and manage their supply chains by making informed decisions regarding sourcing, warehousing, production and capacity management, distribution network design, transportation and risk analysis. This topic is designed to help graduates to develop skills for generating value from data and making better decisions regarding material flows in the supply chain. The topic also provides students with insight into supply chain digitalisation and how technology advancements and big data solutions influence supply chain analytics. The topic builds on skills in descriptive, predictive, and prescriptive analytics which are applicable in various domains of supply chain.

Educational aims

This topic aims to provide students with knowledge and skills to analyse the typical decision problems involved in the major domains of supply chain and help them to master the analytical tools, techniques and methods which can be utilised to solve those problems.

Expected learning outcomes
On completion of this topic you will be expected to be able to:

  1. Explain the fundamental perspectives of supply chain analytics and how digitalisation may influence supply chain management
  2. Explain the applications of data analytics along the Supply Chain Operations Reference (SCOR) model domains
  3. Formulate the analytical models along the SCOR model domain areas (demand forecasting, supplier selection, inventory management, production and capacity planning, transportation problems, and distribution network design)
  4. Effectively use supply chain analytics techniques with computing packages such as Excel