2692-2967ISSN (Online)
2770-0216ISSN (Print)
Volume 2 , Issue 2 , PP: 82-88, 2021 | Cite this article as | XML | Html | PDF | Full Length Article
Shereen Zaki 1 * , Mahmoud M. Ismail 2 , Mahmoud M. Ibrahim 3
Doi: https://doi.org/10.54216/AJBOR.020202
The success of any business organization depends on efficient supply chain management (SCM) that ensures the timely delivery of products to customers. The retail analysis technique (RAT) has emerged as a powerful tool for optimizing SCM by enabling companies to identify and analyze sales trends, inventory levels, and customer demand patterns. This paper explores the use of retail analysis techniques in SCM and how they can be leveraged to enhance the efficiency and effectiveness of supply chain operations. We then present a unified RAT framework that integrates data mining, predictive analytics, and machine learning for optimizing SCM. Additionally, the paper presents a case study of a company that has successfully implemented retail analysis techniques in its SCM practices. The case study highlights the specific strategies and tactics that the company used to optimize its supply chain operations and achieve significant improvements in efficiency and performance. Our analysis shows that RAT is an effective technique for optimizing SCM, and companies that implement it can gain a competitive advantage in the marketplace.
Supply Chain , Retail Analysis , Optimization
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