This work is framed in the retail area, focusing on the automatic generation of the optimal assortment to show on the stores’ shelves. The aim of the thesis is to present a new methodology for the automated assortment optimization that is able to generate an optimal product mix for a products’ category by identifying the right trade-off between margin and revenue. This methodology follows an innovative approach and formalizes a corresponding optimization procedure. The approach considers the most important business KPIs (Key Performance Indicator) in the retail sector: margin and revenue. These KPIs are traditionally considered conflicting objectives, as reducing price, for example through discounts and promotions, typically increases revenues while decreasing margins. In our methodology, the optimal assortment is identified by finding a balanced trade-off between revenue and margin that results in the maximum possible increase of profits. The procedure analyzes past sales of a product's category and generates the list of products to be added and removed from the current assortment, thus creating a new product mix that leads to an increase in both revenue and margin. The proposed procedure is implemented, tested on a store and evaluated based on its trend. The experimental results are used to demonstrate its effectiveness and to measure the impact on the retailer’s profits. Several analyses are carried out on the optimized category to compare the results before and after the new assortment implementation and to analyze how and to what extent the assortment's performance has changed with the changes in the assortment introduced by the methodology.
Questo lavoro si colloca nell’ambito della grande distribuzione, e in particolare nella generazione automatica di un mix di prodotti da posizionare sugli scaffali dei negozi. Lo scopo della tesi è di presentare una nuova metodologia per l’ottimizzazione automatica dell’assortimento che sarà in grado di generare un nuovo assortimento per una categoria di prodotti identificando il giusto trade-off tra margine e fatturato. La metodologia proposta segue un approccio innovativo e formalizza la procedura di ottimizzazione corrispondente. L’approccio considera i due più importanti KPIs (Key Performance Indicator) di business nell’ambito della grande distribuzione: margine e fatturato. Questi KPIs sono tradizionalmente considerati contrastanti, in quanto la riduzione del prezzo, ad esempio attraverso sconti e promozioni, aumenta tipicamente i ricavi riducendo al contempo i margini. Nella nostra metodologia, l’assortimento ottimo è ottenuto individuando il giusto compromesso tra margine e fatturato che si traduce nel massimo aumento possibile di profitto. La procedura analizza le vendite passate di una categoria di prodotti e suggerisce la lista di prodotti da aggiungere dall’assortimento e quelli da rimuovere, creando un nuovo mix di prodotti che porta ad un incremento sia del margine che del fatturato. La procedura proposta è implementata, testata in un negozio e valutata in base al suo andamento. I risultati ottenuti sono utilizzati per valutarne l’efficacia e per misurarne gli effetti basandosi sui guadagni del rivenditore. Sono state eseguite numerose analisi sulla categoria di prodotti ottimizzata per poter confrontare i risultati prima e dopo l’implementazione del nuovo assortimento e per poter analizzare come e quanto le performance dell’assortimento sono cambiate con l’introduzione dei nuovi prodotti.
A comprehensive methodology for assortment optimization in the retail industry
SABATELLI, ANTONELLA
2017/2018
Abstract
This work is framed in the retail area, focusing on the automatic generation of the optimal assortment to show on the stores’ shelves. The aim of the thesis is to present a new methodology for the automated assortment optimization that is able to generate an optimal product mix for a products’ category by identifying the right trade-off between margin and revenue. This methodology follows an innovative approach and formalizes a corresponding optimization procedure. The approach considers the most important business KPIs (Key Performance Indicator) in the retail sector: margin and revenue. These KPIs are traditionally considered conflicting objectives, as reducing price, for example through discounts and promotions, typically increases revenues while decreasing margins. In our methodology, the optimal assortment is identified by finding a balanced trade-off between revenue and margin that results in the maximum possible increase of profits. The procedure analyzes past sales of a product's category and generates the list of products to be added and removed from the current assortment, thus creating a new product mix that leads to an increase in both revenue and margin. The proposed procedure is implemented, tested on a store and evaluated based on its trend. The experimental results are used to demonstrate its effectiveness and to measure the impact on the retailer’s profits. Several analyses are carried out on the optimized category to compare the results before and after the new assortment implementation and to analyze how and to what extent the assortment's performance has changed with the changes in the assortment introduced by the methodology.File | Dimensione | Formato | |
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MasterThesis_Sabatelli.pdf
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https://hdl.handle.net/10589/144823