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Stockout Reduction Using Forecasting Methods, the EOQ Model and a Safety Stock in a Peruvian SME in the Commercial Sector

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Date
2024
Author(s)
Borja Gonzales, Ariana Allison
Perez Soto, Alejandra Beatriz
Flores Pérez, Alberto Enrique
Metadata
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Abstract
Effective inventory management is a constant challenge for SMEs. Stockouts represent a significant obstacle that affects the operability and profitability of these companies. The aim of this study is to develop an affordable and comprehensible solution to reduce stockout in a Peruvian company in the commercial sector. This article presents an improvement proposal leveraging forecasting methods (Holt-Winters and SARIMA), the EOQ model and a safety stock. To evaluate the efficacy of our model, simulations were conducted using Microsoft Excel, followed by the assessment of three key indicators: stockout, bias and inventory turnover. The results indicate a substantial decrease in stockouts by 75%. An economic evaluation demonstrated the prospective profitability of the proposal, as it yielded a Net Present Value (NPV) of 9 031 USD, an Internal Rate of Return (IRR) of 92% and a payback period of 59 days. Subsequent sensitivity analysis confirmed profitability even under adverse scenarios. These findings, coupled with the model’s adaptability and the generalizability of conditions, imply broader prospects for the implementation of this proposal, extending its relevance to diverse industries and countries. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
URI
https://hdl.handle.net/20.500.12724/20886
DOI
https://doi.org/10.1007/978-3-031-56373-7_6
How to cite
Borja Gonzales, A. A., Perez Soto, A. B.,& Flores Pérez, A. E. (2024). Stockout Reduction Using Forecasting Methods, the EOQ Model and a Safety Stock in a Peruvian SME in the Commercial Sector. Communications in Computer and Information Science. https://doi.org/10.1007/978-3-031-56373-7_6
Publisher
Springer Science and Business Media Deutschland GmbH
Subject
Inventory control
Economic lot size
Business forecasting
Sales forecasting
Economic forecasting
Small business
Retail trade
Materials management
Business logistics
ISSN
18650929
Event
Communications in Computer and Information Science
Collections
  • Ingeniería Industrial [145]


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