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.
- Data Generation: Used Python with
pandas
andnumpy
to generate a synthetic dataset of supplier performance metrics (on-time delivery, quality scores). - Geopolitical Risk Scoring (NLP): Used a Python script to simulate news sentiment analysis, deriving geopolitical risk scores for each supplier's country.
- Risk Algorithm: Created a weighted scoring model to combine performance and geopolitical risks into a single
total_risk_score
. - 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