This project demonstrates an end-to-end supply chain analysis and inventory management solution. Using Python for advanced sales forecasting and Tableau for interactive visualization, I developed a data-driven system to predict demand, proactively manage inventory, and create a strategic purchase order plan.
- The Live Inventory Dashboard (Google Sheets) A dynamic dashboard built in Google Sheets to monitor key metrics like Days of Supply and automatically flag inventory risks.
-
Advanced Sales Forecasting (Tableau) An interactive line chart visualizing historical sales (Y) and a 6-month sales forecast (Yhat) generated using the Prophet library in Python.
-
Inventory Status Visualization (Tableau) A color-coded chart that uses visual alerting (Green for "Healthy," Red for "Risk") to provide an at-a-glance view of inventory health across all SKUs.
-
The Final Dashboard (Tableau) The complete, end-to-end dashboard combining all key insights, published and ready for sharing.
- Data-Driven Purchase Plan (Q3 & Q4 2025): Based on the analysis, a purchase order of $1,665,600.00 was recommended to meet forecasted demand and prevent stockouts.
- Proactive Risk Management: The dashboard provides a system to flag inventory risks early, allowing for timely decision-making.
- Python, Pandas, Prophet, Google Sheets, Tableau
-
Live Google Sheets Dashboard: https://docs.google.com/spreadsheets/d/1WTgrwlUb9VTFM-pDlE5EaB0jVqSSJ-ctwDPXaT6bfgI/edit?usp=sharing
-
Interactive Tableau Dashboard: https://public.tableau.com/app/profile/aklilu.abera/viz/AuraGlowSupplyChainDashboard/Dashboard1
-
Python Forecasting Code: https://github.com/akeDataAnalyst/aura-glow-supply-chain-project/blob/main/script/forecasting_script.ipynb