Description:

The Supply Chain Delay Prediction Tool is a data-driven forecasting system designed to help businesses anticipate and mitigate delays in supply chain operations.
It uses historical shipment records, weather conditions, traffic data, port congestion reports, supplier performance metrics, and real-time logistics feeds to predict when and where delays are likely to occur.

By applying big data analytics and machine learning models, the tool generates delay risk scores for each shipment or supply chain route, allowing companies to take proactive measures—such as rerouting shipments, sourcing from alternate suppliers, or adjusting production schedules.

Key Features:

1. Real-Time Data Integration – Fetches shipment tracking updates from carriers, ports, and logistics APIs.

2. Predictive Delay Scoring – Assigns probability scores (e.g., 85% chance of delay) for each shipment or supplier.

3. Customizable Delay Factors – Allows users to weigh the impact of weather, traffic, customs clearance, and supplier reliability.

4. Historical Trend Analysis – Identifies patterns in past delays to improve accuracy over time.

5. Risk Alerts & Notifications – Sends alerts via email/SMS if a shipment’s delay probability exceeds a threshold.

6. Scenario Simulation – Lets managers test “what-if” scenarios (e.g., changing the shipping route or supplier) to see the impact on delivery times.

7. Dashboard & Visual Analytics – Displays maps with high-risk areas, delay hotspots, and timelines.

8. Supplier Performance Tracking – Monitors and ranks suppliers based on on-time delivery records.

Technology Stack:

• Backend: Node.js / PHP / Java (for ML model hosting, API handling, and scheduling)

• Frontend: HTML, CSS, Bootstrap, JavaScript (for dashboard UI)

• Database: MySQL / MongoDB (for shipment data, performance logs, and model results)

• Visualization: Chart.js, D3.js, and Leaflet.js for geospatial delay maps

• Machine Learning: Python (scikit-learn, XGBoost) for predictive modeling; models can be integrated into backend via REST APIs

• External APIs: Google Maps API, OpenWeatherMap, Carrier APIs (FedEx, DHL, UPS)

Example Use Case:

• A global electronics manufacturer experiences frequent delivery delays due to port congestion in certain regions.

• The tool identifies that during the monsoon season, shipments via Port X have a 70% higher delay probability.

• The company reroutes sensitive shipments to an alternate port, reducing late deliveries by 25% in 3 months.