Abstract
Retail store operations face a variety of challenges and complexities. Determining the best assortment is the main problem in the retail store. This re-search presents a practical methodology for the analysis of products in the assortment with the goal of reducing the excess items and improve sales and profit margin of a retail store without affecting customer satisfaction. The methodology integrates 6 steps that allow to optimize products of a portfolio in categories, sub categories and segments, through Pareto analysis and clustering analysis using the BCG matrix. The methodology was applied in an independent supermarket. The results in the case of the application for non-perishable products, allowed to identify a set of different products (n = 152), of which they were prioritized in a subcategory (oils) in which 90 products were prioritized. In the example, it shows how 21 products have significant results in the variety of products. The combination of the global and local category of the product, the net profit, the inventory rotation and the participation of the growth provides a multifactorial analysis in the decision-making to supply with products a retail store seeking to increase the level of service and maximizing profits.
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Coronado-Hernandez, J.R. et al. (2020). A Method to Rationalize the Product Portfolio in Retail Stores. In: Gunjan, V., Senatore, S., Kumar, A., Gao, XZ., Merugu, S. (eds) Advances in Cybernetics, Cognition, and Machine Learning for Communication Technologies. Lecture Notes in Electrical Engineering, vol 643. Springer, Singapore. https://doi.org/10.1007/978-981-15-3125-5_51
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DOI: https://doi.org/10.1007/978-981-15-3125-5_51
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