Development of a Sales and Demand Forecasting Analytics System
Data Science — 2025, Undergraduate
web applicationdemand forecastingsales analyticspredictive analytics
This study developed a sales and demand forecasting analytics system that profiles historical demand, applies trend and seasonal models, and generates forecasts with accuracy bands. The system compares forecasts against actuals and alerts planners to outliers. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, FastAPI, Statsmodels, and PostgreSQL. The findings showed that the system improved planning accuracy and reduced forecast effort, while achieving a high System Usability Scale score. The study recommends adoption by retail and distribution firms.
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