Description

Introduction

Accurate demand forecasting is the foundation of a resilient supply chain. Traditional methods often fall short in dealing with volatile markets, vast datasets, and real-time changes. This course introduces AI-powered demand forecasting using Supply.AI—a modern solution that leverages machine learning, big data, and predictive analytics. You’ll learn how AI enhances forecasting accuracy, reduces stockouts and overstocking, and enables smarter business decisions across industries.

Prerequisites

• Basic understanding of supply chain or inventory management

• Familiarity with data analytics or Excel-level data tools

• No prior AI or coding experience required (conceptual focus)

Table of Contents

1. Introduction to Demand Forecasting

    1.1 Importance in Supply Chain Planning
    1.2 Challenges with Traditional Forecasting
    1.3 Overview of Supply.AI

2. Foundations of AI and ML in Forecasting

    2.1 Supervised Learning for Time Series
    2.2 Feature Engineering Basics
    2.3 Model Evaluation Metrics (MAE, RMSE, MAPE)

3. Data Collection and Preprocessing

    3.1 Internal vs External Data Sources
    3.2 Cleaning and Normalizing Data
    3.3 Handling Missing and Anomalous Values

4. AI Models for Demand Forecasting

    4.1 Linear Regression and ARIMA
    4.2 Random Forests and XGBoost
    4.3 Deep Learning: RNNs and LSTMs

5. Using Supply.AI Forecasting Tools

    5.1 Uploading and Preparing Datasets
    5.2 Training and Evaluating Models
    5.3 Visualizing Forecast Outputs

6. Scenario Planning and What-If Analysis

    6.1 Simulating Demand Surges and Drops
    6.2 Seasonality and Trend Detection
    6.3 Forecasting Promotions and New Product Launches

7. Integration with ERP and SCM Systems

    7.1 Data Sync with SAP, Oracle, and Netsuite
    7.2 API-Based Automation Workflows
    7.3 Real-Time Inventory Reordering

8. AI Forecasting for Different Industries

    8.1 Retail and E-commerce
    8.2 Manufacturing and Automotive
    8.3 Healthcare and FMCG

9. Measuring ROI and Forecast Accuracy

    9.1 Inventory Cost Reduction
    9.2 Service Level Improvements
    9.3 Forecast Bias Analysis

10. Ethics, Bias, and Responsible AI

    10.1 Avoiding Algorithmic Bias
    10.2 Data Privacy in Forecasting
    10.3 Transparent Decision-Making

AI-powered demand forecasting with Supply.AI brings unmatched precision and agility to supply chain planning. By combining historical data with advanced algorithms, organizations can better predict market needs and improve their operational performance. With these skills, you’re well-positioned to lead demand planning in the AI-driven supply chain era.