Optimizing Returns and Refunds Management in SAP: Leveraging Data-Driven Insights and Advanced Automation
Abstract
Efficient returns and refunds management is a critical component of supply chain and customer service operations, significantly impacting customer satisfaction, operational efficiency, and profitability. This research explores the optimization of returns and refunds processes within SAP systems, leveraging advanced technologies such as automation, machine learning, and predictive analytics. The study identifies key challenges in traditional returns management, including process inefficiencies, high costs, and delayed resolutions. It proposes an integrated framework that utilizes SAP's capabilities, enhanced with intelligent automation and data-driven insights, to streamline workflows, reduce processing time, and improve decision-making. By analyzing real-world case studies and implementing simulation models, the research demonstrates measurable improvements in cost savings, error reduction, and customer satisfaction. The findings provide actionable strategies for businesses to transform their returns and refunds operations into a competitive advantage while aligning with sustainability goals through reduced waste and optimized resource utilization.
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