Demand Forecasting and Inventory Analytics

This course is designed to provide students with an understanding of inventory analytics, including how to use data to optimize inventory levels, reduce costs, and improve customer service. Students will learn about key inventory metrics and how to analyze them to make data-driven decisions. The course will cover inventory management techniques, including inventory optimization, demand forecasting, and inventory replenishment.

Course Outline:

1. Introduction to Inventory Analytics

• Definition of Inventory Analytics
• Benefits of Inventory Analytics
• Key Concepts in Inventory Analytics
• Inventory Metrics and Performance Measures

1. Inventory Optimization

• Types of Inventory
• Economic Order Quantity (EOQ) Model
• Reorder Point (ROP) Model
• Safety Stock Analysis

1. Demand Forecasting

• Time Series Analysis
• Regression Analysis
• Seasonal Forecasting
• Forecast Accuracy Metrics

1. Inventory Replenishment

• Just-In-Time (JIT) Inventory
• Materials Requirement Planning (MRP)
• Distribution Requirements Planning (DRP)
• Capacity Planning

1. Inventory Performance Measurement

• Inventory Turnover
• Days of Supply
• Stockout Rate
• Customer Service Level

1. Inventory Analytics Tools

• Excel Inventory Analytics Tools
• Inventory Management Software
• Data Visualization Tools

Prerequisites:

• Basic knowledge of inventory management concepts
• Familiarity with Excel or other data analysis tools

Recommended Textbook:

• “Inventory Management and Production Planning and Scheduling” by Edward A. Silver, David F. Pyke, and Rein Peterson.

Assessment:

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

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