Shipment Count Forecasting

Project Details

Summary

Leveraging Python's Prophet library, I built customer-specific shipment count forecasting models. T-tests validated predictions, and 90-day/6-month forecasts were generated. A performance metric tracked model accuracy. The data then seamlessly flowed into a Power BI dashboard, enabling interactive analysis by various parameters. This empowered decision-makers with valuable customer trend insights, driving strategic initiatives and optimized operations.

Tools

• Python: I streamlined data processing, generated forecasts via Prophet, and assessed model accuracy with t-tests and MSE.

• Power BI: Built an interactive dashboard to visualize forecasted shipment counts, giving stakeholders the ability to evaluate predictions and trends.