Machine Learning in Predicting Demand for Fast-Moving Consumer Goods: An Exploratory Research

Abstract

Abstract More accurate prediction of the demand for fast-moving consumer goods is a competitive factor for manufacturers and retailers, especially in the fashion, technology and fresh food sectors. This exploratory research presents the benefits of Machine Learning in sales forecasting for short shelf-life and highly-perishable products, as it surpasses the accuracy level of traditional statistical techniques and, as a result, improves inventory balancing throughout the chain, reducing stockout rates at points of sale, improving availability to consumers and increasing profitability.