This ebook Retail Analytics: Integrated Forecasting and Inventory Management for Perishable Products in Retailing (PDF) addresses the challenging task of inventory management and demand forecasting in retailing. It analyzes how information from point-of-sale (PoS) scanner systems can be used to improve inventory decisions and develops a data-driven approach that integrates demand forecasting and inventory management for perishable products while taking unobservable lost sales and substitution into account in out-of-stock situations. The ebook subsequently demonstrates the benefits of this new approach in numerical studies that utilize real data collected at a large European retail chain. Using linear programming; a new inventory function that reflects the causal relationship between demand and external factors such as price and weather is proposed. Furthermore; the ebook derives an optimal inventory policy for a multi-product setting in which the decision-maker faces an aggregated service level target; and analyzes whether the decision-maker is subject to behavioral biases based on real data for bakery products.