This methodology leverages artificial intelligence, specifically machine learning algorithms, to predict future product or service needs. It analyzes historical sales data, market trends, seasonality, and external factors like economic indicators and promotional activities to generate accurate forecasts. For instance, a retail company might employ it to anticipate the quantity of specific items required at each store location during the holiday season, optimizing inventory levels and minimizing stockouts or overstocking.
Accurate prediction of future requirements offers significant advantages for businesses. It allows for more efficient resource allocation, improved supply chain management, reduced costs associated with excess inventory, and enhanced customer satisfaction by ensuring product availability. The evolution of these advanced forecasting techniques is rooted in the increasing availability of large datasets and the advancements in computational power, allowing for more sophisticated modeling and analysis.
