Supply Chain Analytics
This course and accompanying short case studies will facilitate tactical and operational level complex decision problems under uncertainties
Date and time
Location
UNSW Canberra City Campus
37 Constitution Avenue CIT J Block Reid, ACT 2600 AustraliaRefund Policy
About this event
- 1 day 7 hours
Area of Interest: Capability Management
Course Summary
Managing supply chains (SCs) is one key factor for many organisations, while new technologies and data-driven software solutions offer the policymakers to optimise their decision-making processes. Diversification in local and global supply and distribution, increased customer expectations, increasing involvement of man and smart machines in the Industry 4.0 era, and enormous customisation of products results in a significant increase in complexity in the decision-making process. Consequently, traditional manual planning activities are challenged, and organisations need to change the planning process. To overcome this challenge at first sight, decision-makers need to understand the benefits of supply chain analytics in making a reasonable and reliable base for decision-making for modern SCs.
This short course will familiarise participants, especially those who engage with day-to-day decision-making in SCs or are interested in planning to follow that career path. This course and accompanying short case studies will facilitate both tactical and operational level complex decision problems under uncertainties. No prior knowledge is assumed. However, basic skills in Microsoft Excel and knowledge of High School level maths would be an advantage
Duration: 2 Days
Delivery Mode: Live simulcast online course
Course Outline
Learning Outcome
9:00 am to 9:15 am: Housekeeping and Introduction
• Knowing each other
• How the course is structured.
9:15 am to 10:30 am: Data Analytics vs Supply Chain Analytics: Introduction [Lecture 1]
• Explain Data Analytics and how that is related to supply chain analytics
• Define and demonstrate ‘Decision Making’ types
• Defining Business Analytics
• Explain the categorisation of Analytical Methods and Models
• An introductory description of SC analytics explaining the methodology’s three main components
• What are Big Data and Big Data Analytics?
• Business Analytics in Practice
• Legal and Ethical Issues in the Use of Data and Analytics
11:00 am to 12:00 pm: Basic Concepts of Operations Management and Value Chains
[Lecture 2]
• Explain the concept and importance of operations management.
• Describe what operations managers do.
• Explain the differences between goods and services.
• Define the concept of the value and explain how the value of goods and services can be enhanced.
• Summarise the historical development of OM.
• State the current and future key challenges facing OM.
• Explain the use of analytics in operations management
• Describe how customers evaluate goods and services
• Describe different types of technology and their role in manufacturing and service operations
• Explain the benefits and challenges of using technology
• Describe key technology decisions
12:00 pm to 12:45 pm: Designing Operations &
Using Supply Chain Analytics
[Lecture 3]
• Explaining how Data/Decision Analytics is related to SC Strategies
• Describe the steps involved in designing goods and services.
• Eleven elements of SC design decisions
• SC Design Trade-offs
• Location Problems.
2:00 pm to 4:30 pm: Linear Programming and Transportation Models
[Lecture 4]
• Introduction to Optimisation and Linear Programming
• Spreadsheet Modelling
• Network Models
• Transportation Problems
• Exercises (with Excel)
Module 2 (Day 2)
9:00 am to 11:45 am: Analytics in Managing Inventories in Supply Chains
[Lecture 5]
• Explain the importance of inventory, types of inventories, and key decisions and costs.
• Describe the major characteristics that impact inventory decisions.
• Describe how to conduct an ABC inventory analysis.
• Explain how a fixed-order-quantity inventory system operates and how to use the economic order quantity (EOQ) and safety stock models.
• Explain how a fixed-period inventory system operates.
• Exercises (with Excel)
12:00 pm to 12:45 pm: Supply Chain Risk Analytics
[Lecture 6]
• Describe what digital technology-based extensions can trigger the developments toward Supply Chain Risk Analytics
2:00 pm to 4:00 pm: Analytics in Sourcing/Purchasing Decisions
[Lecture 7]
• Describe why Purchasing is important
• Explain the seven-stage supplier selection process as an enabler to world-class supplier selection
• Develop an understanding of a quantitative supplier evaluation and selection tool
• Explain Multi-criteria Decision Making (MCDM) Technique
• Exercise: Supplier selection (with Excel)
4:00 pm to 4:15 pm: Conclusion & Course Feedback
Course Learning Outcome
The participants will learn the fundamentals of modern supply chains and the role of data analytics in supply chains.
The participants will gain skill in using decision-making tools by Excel solver for solving case studies inspired from real-life.
Affiliated Courses
• Business Analysis and Valuation (professional course)
• Decision Making in Analytics (program code: ZZCA6510)
• Master of Decision Analytics (program code: 8634)
Who should attend
This introductory course is for anyone interested in solving decision problems in different supply chains for Defence, Government agencies, public and private sector organizations. This course is suitable for anyone faced with complex and dynamic decision problems in either public or private sector.