AI-Driven Item Demand Forecasting for a Large Outdoor Clothing Company

THE BACKGROUND

The client, a globally renowned outdoor clothing and gear company, operates with a strong emphasis on sustainability and product quality. With a diverse product catalog that spans thousands of items, each categorized by style and color, the company follows a dual-season structure: Spring and Fall, each lasting six months. Accurate demand forecasting is critical for their business, driving the merchandising, inventory, and overall operational planning processes.

Their existing forecasting process was limited in its ability to adapt to rapid shifts in consumer demand and emerging market trends, creating inefficiencies in product availability and inventory management. Compounding the complexity, some items carry over from one season to the next, while others are introduced anew or discontinued after a single season.

Building an advanced AI-driven forecasting solution capable of handling these nuances would significantly enhance the client’s ability to predict demand accurately at a granular level.