Enhancing Sales Forecasting with Data Science Case Study

A leading company struggled with manual data retrieval and inconsistent data, impacting sales forecasting accuracy. To streamline the process, a dedicated data science team implemented a multi-algorithm approach using Holt-Winters, Neural Networks, ETS, and ARIMA. Tailored models for different product categories, rolling forecasts, and Copilot integration enhanced efficiency and decision-making. The focus on high-margin products further boosted sales performance. Learn how this data-driven solution overcame challenges and transformed the sales forecasting process for better accuracy and strategic insight. Dive into the full case study!