This project demonstrates how to build a proactive risk assessment tool for supply chain management. It combines traditional performance metrics with an NLP-driven geopolitical risk score to provide a holistic view of supplier reliability. The final deliverable is an interactive dashboard built in Tableau Public.

• Problem: Supply chain disruptions from poor supplier performance and unexpected global events can cause significant financial and operational damage.
• Solution: This dashboard provides a data-driven solution, enabling supply chain managers to identify high-risk suppliers and make informed decisions to mitigate potential disruptions.

1. Data Generation: Used Python with pandas and numpy to generate a synthetic dataset of supplier performance metrics (on-time delivery, quality scores).
2. Geopolitical Risk Scoring (NLP): Used a Python script to simulate news sentiment analysis, deriving geopolitical risk scores for each supplier's country.
3. Risk Algorithm: Created a weighted scoring model to combine performance and geopolitical risks into a single total_risk_score.
4. Interactive Dashboard: Built a professional, interactive dashboard in Tableau Public to visualize the results, including a risk heatmap and supplier details.

• Data Analysis & Scripting: Python, Pandas, NumPy
• Natural Language Processing: TextBlob
• Data Visualization: Tableau Public

You can explore the full, interactive dashboard here: Live Dashboard Link on Tableau Public

Created by AKLILU ABERA