1. Introduction to Supply Chain Management:

• Overview of supply chain concepts and components
• Importance of analytics in optimizing supply chain operations
• Current trends and challenges in supply chain management

2. Data Analytics Fundamentals:

• Introduction to data analytics tools and techniques
• Understanding data sources and data collection methods in supply chain management
• Data preprocessing and cleaning for supply chain data

3. Supply Chain Performance Metrics:

• Key performance indicators (KPIs) for evaluating supply chain performance
• Measurement and analysis of metrics such as inventory turnover, on-time delivery, and lead time
• Benchmarking and setting performance targets

4. Demand Forecasting and Inventory Optimization:

• Techniques for demand forecasting using statistical methods and machine learning algorithms
• Inventory optimization strategies to minimize costs and maximize service levels
• Inventory management models (e.g., EOQ, JIT) and their applications

5. Supply Chain Network Design:

• Fundamentals of supply chain network design and optimization
• Strategic decisions in network design including facility location, capacity planning, and transportation routing
• Network optimization models and simulation techniques

6. Supplier Relationship Management (SRM):

• Importance of supplier relationships in supply chain management
• Supplier performance evaluation and risk management
• Strategies for improving collaboration and communication with suppliers

7. Transportation and Logistics Analytics:

• Analyzing transportation data to optimize routing, scheduling, and mode selection
• Logistics optimization techniques for cost reduction and efficiency improvement
• Real-time tracking and monitoring of shipments

8. Warehousing and Distribution Analytics:

• Warehouse layout optimization and space utilization analysis
• Order picking and fulfillment optimization
• Distribution center performance measurement and improvement

9. Sustainability and Green Supply Chain Analytics: – Role of analytics in sustainable supply chain management – Environmental impact assessment and carbon footprint measurement – Strategies for integrating sustainability into supply chain operations

10. Supply Chain Risk Management: – Identifying and assessing supply chain risks – Risk mitigation strategies and contingency planning – Using analytics for risk prediction and decision-making in uncertain environments

11. Case Studies and Practical Applications: – Analyzing real-world supply chain analytics case studies across various industries – Applying analytics techniques to solve supply chain challenges and improve performance – Hands-on projects and simulations to reinforce learning and practical skills developmen