European Journal of Computer Science and Information Technology (EJCSIT)

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Benefits of Implementing SAP Solutions to Minimize Shrinkage and Optimize Business Operations

Abstract

This article examines how implementing SAP solutions can effectively minimize inventory shrinkage and optimize business operations across the retail and manufacturing sectors. Shrinkage—defined as inventory loss due to theft, damage, administrative errors, or discrepancies—represents a significant challenge that directly impacts profit margins and operational efficiency. The article demonstrates how SAP’s integrated enterprise resource planning capabilities provide comprehensive solutions through enhanced inventory management, data accuracy, and multilayered control mechanisms. By leveraging SAP Extended Warehouse Management, Inventory Manager, Global Batch Traceability, and Integrated Business Planning, businesses can achieve substantial improvements in inventory visibility, tracking accuracy, and loss prevention. The integration of advanced analytics and machine learning capabilities enables predictive identification of potential shrinkage issues, exception-based monitoring, automated reconciliation, and root cause analysis, transforming reactive loss prevention into proactive risk management. Furthermore, when SAP solutions are integrated with a complementary security system, including point-of-sale monitoring, physical security infrastructure, vendor controls, and risk-based authentication, businesses establish a “defense in depth” approach that addresses shrinkage across all potential vectors. Beyond direct shrinkage reduction, these implementations yield broader benefits, including decreased operational costs, improved cash flow management, reduced stockouts, enhanced customer satisfaction, and increased inventory turnover—ultimately strengthening competitive positioning in challenging market environments.

Keywords: Enterprise Resource Planning, Inventory shrinkage, SAP implementation, loss prevention, retail security, supply chain optimization

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This work by European American Journals is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License

 

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Email ID: editor.ejcsit@ea-journals.org
Impact Factor: 7.80
Print ISSN: 2054-0957
Online ISSN: 2054-0965
DOI: https://doi.org/10.37745/ejcsit.2013

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