Jasmine Guglielmi
Demand Forecasting for Size Curve Optimisation in Luxury Retail.
Rel. Daniele Apiletti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024
Abstract
Retail firms face considerable issues as a result of product overstock and under stocking, especially in the context of fundamental tourism dynamics and seasonal bias. These problems can lead to missed sales opportunities, lower client satisfaction, and increased business expenditures. Intrinsic tourism characteristics, such as changes in visitor numbers and spending habits, can make it difficult for shops to precisely forecast demand. Seasonal biases, such as higher demand for certain items at various periods of the year, affect inventory management even more. To effectively address these difficulties, retailers must establish strategic inventory management procedures and use data analytics to estimate demand and improve product offers.
An effective size distribution is a crucial element in the management of inventory levels, the reduction of waste, and the improvement of customer satisfaction
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