Demand Forecasting for Regional Distribution
A national logistics provider struggled with inventory lag in northern Kanto. Our lab applied a localized weather-impact model combined with regional transit data to reduce stock-outs by 22% during peak seasonal shifts. This methodology used a neural network approach fine-tuned for small-sample regional inputs.