Supply Chain Demand Forecasting
Predicting Product Demand Using AI & Machine Learning
This application forecasts future demand for products (SKUs) in a supply chain network using historical sales data, machine learning models, and AI-powered insights.
What Are We Forecasting?
📦 Product Demand
We forecast the daily demand (number of units) for a specific product (SKU) in a particular region. For example: "How many units of SKU123 will be needed in the North region over the next 7 days?"
Example Scenario:
- • Product: SKU123 (Electronics Item)
- • Region: North America
- • Historical Data: Last 14 days of sales
- • Forecast Period: Next 7 days
🎯 Why It Matters
Inventory Optimization
Stock the right amount - not too much, not too little
Cost Reduction
Minimize storage costs and prevent stockouts
Better Planning
Prepare for demand spikes during events or promotions
System Architecture & Flow
Historical Data
14 days of sales
ML Model
ARIMA Forecast
Predictions
7-day forecast
Event Data
Promotions, holidays
LLM (GPT)
AI explanations
Knowledge Graph
Supply chain context
Machine Learning
ARIMA time series model analyzes historical patterns to predict future demand
Statistical ForecastingLarge Language Model
GPT-3.5 generates forecasts and natural language explanations for predictions
AI-Powered InsightsGraph RAG
Knowledge graph connects suppliers, products, warehouses, and events for context
Contextual IntelligenceHow It Works
Load Historical Data
System loads demand time series and event data for SKU123 in North region
Run ML & LLM Forecasts
ARIMA model and GPT generate independent 7-day forecasts
Generate Explanations
AI analyzes events and provides natural language explanations for each forecast day
Build Knowledge Graph
Create supply chain graph connecting suppliers, plants, SKUs, warehouses, and events
Visualize Results
Display interactive charts, graphs, and insights in a comprehensive dashboard