Supply Chain Risk Analytics

The course is designed to equip students with the necessary skills and knowledge to identify, analyze, and manage supply chain risks through data analytics techniques. The course will cover key concepts and methods in risk analysis, data management, statistical modeling, and visualization. Students will learn how to use these tools to evaluate the impact of risks on supply chain performance and develop effective risk management strategies.

Course Outline:

1. Introduction to Supply Chain Risk Management

• Definitions of Supply Chain Risks
• Importance of Supply Chain Risk Management
• Key Risk Categories in Supply Chain Management
• Types of Supply Chain Risks

1. Data Management for Supply Chain Risk Analytics

• Data Collection and Preprocessing
• Data Integration and Cleansing
• Data Storage and Retrieval
• Data Visualization Techniques

1. Statistical Modeling for Supply Chain Risk Analytics

• Descriptive Statistics and Exploratory Data Analysis
• Probability Distributions and Simulation
• Regression Analysis and Forecasting
• Machine Learning Techniques for Risk Analysis

1. Supply Chain Risk Analytics Tools and Techniques

• Risk Identification and Assessment
• Risk Monitoring and Control
• Risk Response and Mitigation
• Risk Communication and Reporting

1. Case Studies in Supply Chain Risk Analytics

• Case studies from various industries
• Real-world examples of supply chain risks and their impact on performance
• Case studies on effective risk management strategies

1. Future Trends in Supply Chain Risk Analytics

• Emerging Technologies in Supply Chain Risk Management
• Sustainability and Social Responsibility in Supply Chain Management
• Future Trends in Supply Chain Risk Management

Prerequisites:

• Basic understanding of statistics and data analytics
• Familiarity with Excel and/or R programming language

Recommended Textbook:

• “Supply Chain Risk Management: An Emerging Discipline” by Gregory L. Schlegel and Robert J. Trent.

Assessment:

• Midterm Exam (30%)
• Final Exam (40%)
• Group Project (30%)

Instructor Profile

Note: The course syllabus and assessment methods are subject to change based on instructor’s discretion.