Supply Chain Analytics Project | Python · Streamlit · Plotly
Part of a logistics optimization portfolio by Emmanuel Beristain Guzmán
An interactive web dashboard for monitoring supply chain operations in real time. Built to demonstrate applied knowledge of logistics KPIs, data visualization, and operational analytics — skills directly relevant to SAP MM/SD, supply chain consulting, and logistics analytics roles.
The dashboard simulates 12 months of realistic logistics data across five key performance indicators, with filters, supplier scorecards, and route efficiency analysis.
| KPI | Description | Target |
|---|---|---|
| OTD | On-Time Delivery rate | ≥ 95% |
| Inventory Turnover | How many times stock cycles per year | ≥ 8x |
| Freight Cost/Unit | Average shipping cost per unit dispatched | Minimize |
| Fulfillment Rate | Orders completed without backorder | ≥ 95% |
| Lead Time | Average supplier delivery time (days) | Minimize |
- ✅ Interactive KPI cards with month-over-month delta
- ✅ Trend charts for OTD, fulfillment, freight cost, lead time
- ✅ Monthly order volume visualization
- ✅ Supplier performance scorecard (color-coded)
- ✅ Route efficiency scatter map (cost vs. transit days vs. volume)
- ✅ Sidebar filters by period and data seed
- ✅ Fully responsive — works on desktop and tablet
Dashboard running locally — dark industrial aesthetic
logistics-dashboard/
│
├── dashboard.py # Main Streamlit app — all logic + UI
├── requirements.txt # Python dependencies
├── README.md
└── screenshot.png # Dashboard preview (for GitHub)
git clone https://github.com/net421/logistics-dashboard.git
cd logistics-dashboardpip install -r requirements.txtstreamlit run dashboard.pyThe app opens automatically at http://localhost:8501
Sidebar controls:
- Use the month sliders to filter the analysis period
- Change the data seed to regenerate a different dataset scenario
Main panels:
- KPI Cards — current month snapshot with delta vs. previous month
- Trend Charts — 12-month performance evolution with targets
- Supplier Scorecard — ranked table with conditional formatting
- Route Map — bubble chart: cost vs. days, sized by volume, colored by OTD
This dashboard maps directly to real logistics management tools:
| Dashboard element | Real-world equivalent |
|---|---|
| OTD tracking | Delivery performance in SAP SD / TM |
| Inventory turnover | Stock analysis in SAP MM (MMBE, MB52) |
| Supplier scorecard | Vendor evaluation in SAP MM (ME61) |
| Lead time monitoring | Purchasing info record in SAP MM |
| Freight cost per unit | Condition records in SAP TM / MM |
Understanding and visualizing these KPIs is core to supply chain consulting and SAP functional configuration.
| Tool | Use |
|---|---|
| Python 3.10+ | Core logic and data processing |
| Streamlit | Web app framework |
| Plotly | Interactive charts |
| pandas | Data manipulation |
| numpy | Synthetic data generation |
- Supply chain KPI definition and monitoring
- Interactive data visualization for operations
- Dashboard design and UX for logistics teams
- Python scripting for analytics automation
- Synthetic data generation for prototyping
Emmanuel Beristain Guzmán
Logistics Engineer | Supply Chain Analytics | SAP Functional Trainee
📍 México (Remote) · 📧 emmanuel.beristain.guzman@gmail.com
🔗 github.com/net421
Part of a series of supply chain analytics projects. See also: EOQ/ROP inventory simulator, demand forecasting, and VRP route optimization.