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Data Science2025In Progress

Supply Intelligence

Supply Chain Risk Analytics

Supply chain visibility and risk assessment platform. Ensemble ML models predict disruptions, optimize inventory, and recommend supplier diversification across global sourcing networks.

Context

Post-pandemic supply chain shocks exposed the fragility of just-in-time procurement for a global industrial group. Leadership needed a proactive risk system, not a post-mortem dashboard.

The Challenge

Supply chain disruption signals are scattered across news APIs, shipping databases, financial reports, and weather systems. Translating noisy external signals into actionable procurement recommendations is a hard NLP and ranking problem.

The Solution

Building a multi-source signal aggregation layer that combines shipping delay data, geopolitical risk scores, financial health indicators, and weather events. An ensemble model ranks supplier risk in real-time. A React dashboard allows procurement teams to simulate disruption scenarios and explore recommended alternatives.

Methodology

  • ETL pipeline aggregating 15+ external data providers into a unified risk data model
  • NLP-based news monitoring for early-warning geopolitical signals
  • Graph-based supplier network model for second-tier dependency analysis
  • Scenario simulation engine for procurement planning under uncertainty

Impact

In active development. Pilot deployment planned for Q3 2025 with 3 business units.

Technology Stack

Pythonscikit-learnSQLdbtSnowflakeReactNLP

Project Details

CategoryData Science
Year2025
StatusIn Progress