Demand Forecasting for Wave Planning

SKU-level daily demand forecasting aligned with SAP EWM wave planning logic. Forecast outputs exposed via OData services for SAP integration.

Overview

Demand forecasting directly feeds wave management and inbound planning—core EWM functions. This project demonstrates how forecasting connects to warehouse operations, providing reliable short-horizon demand signals for operational planning.

Key Features

• SKU-Level Forecasting: Per-SKU daily demand prediction using Prophet
• Wave Planning Integration: Forecasts translate into actionable wave planning suggestions
• Seasonality Handling: Weekly patterns, monthly trends, and holiday effects
• SAP Integration Ready: Forecast outputs exposed via OData services
• Interactive Dashboard: Streamlit app for visualization and planning

Business Impact

• ✅ Enables proactive wave planning vs reactive order processing
• ✅ Helps optimize warehouse capacity and labor allocation
• ✅ Reduces peak-day bottlenecks through early identification
• ✅ Improves inbound scheduling efficiency

Installation

git clone https://github.com/jbondata/ewm-demand-forecasting.git
cd ewm-demand-forecasting
pip install -r requirements.txt

Usage

Streamlit Dashboard

streamlit run streamlit_app.py

SAP-EWM Integration

• Wave Creation Rules: Forecast outputs inform SAP EWM wave creation logic
• OData Services: Forecasts exposed via OData for Fiori app consumption
• CDS Views: Understanding of semantic data modeling for S/4HANA
• Operational Relevance: Demonstrates how forecasting connects to warehouse operations

License

MIT License - see LICENSE file for details.