Demand and Inventory Management for the Creation of an Automated Information Management System: A Case Study Applied to an Ecuadorian Supermarket

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Abstract

In 2020, due to the COVID-19 pandemic, supermarkets took over as distributors of essential products. Due to this same situation, even the behavior of consumers changed radically since food, cleaning products, and personal hygiene products increased their presence at historical levels. This situation forced several commercial sectors to evaluate their data to respond immediately to the requirements of consumers. Therefore, the need arises for efficient and optimal planning of the products on the rack that are offered, focusing on those of greatest demand and sale to consumers. The present research study was carried out in an Ecuadorian supermarket, in which methodologies for the treatment of forecasts and inventories were applied through the historical sales data provided by the company for the years 2018, 2019, and 2020. Forecast models were applied to reduce uncertainty regarding planning the supply of the different products offered in the supermarket. The models were ARIMA, Holt, Holt-Winters, Seasonal Simple, and Winters Additive, while for the treatment and efficiency planning of the existing stock within the company; that is, having enough products to satisfy the demand, different inventory models and respective EOQs (economic order quantities) were applied according to the case. The information on sales management has been compiled and standardized in a Microsoft Excel template for the optimal flow of information and the recording of internal operations, achieving efficient product planning to avoid shortages in the supply chain.

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Cárdenas-García, P. L., Ichau-Tabango, D. M., Pando-Sigua, P. J., & Avilés-Sacoto, S. V. (2023). Demand and Inventory Management for the Creation of an Automated Information Management System: A Case Study Applied to an Ecuadorian Supermarket. In Lecture Notes in Logistics (Vol. Part F268, pp. 191–212). Springer Science and Business Media B.V. https://doi.org/10.1007/978-3-031-32032-3_8

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