Demand Forecasting Model
Neighborhood-level order forecasting for peak periods
overview
Demand forecasting models for peak commercial periods like Mother's Day and Valentine's. Combines historical patterns, seasonality and external signals; forecast vs actual tracked continuously.
- Bayesian shrinkage (κ) + bootstrap model
- Granularity: Neighborhood → District → City
- Supports stock, capacity and campaign decisions
- Browser-based interactive visualization (Plotly)
impact / value
From planning on gut feel and last year's numbers to neighborhood-level demand forecasts that drive stock, capacity and campaign decisions.
Before: Peak-period demand was largely estimated from last year's numbers and gut feel; stock and capacity were over- or under-planned and campaigns were set up blindly.
After: With a Bayesian shrinkage (κ) + bootstrap model, demand is forecast down to the neighborhood; stock, capacity and campaign decisions rest on data. Forecast vs actual is tracked continuously to calibrate the model, and a browser-based interactive visualization puts everyone on the same page.
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