Machine Learning in SAP Workflows: A Study of Predictive Analytics and Automation

Vedaprada Raghunath, Mohan Kunkulagunta, Geeta Sandeep Nadella

Abstract


This study explores the integration of machine learning (ML) into SAP workflows to enhance predictive analytics and automation capabilities in enterprise resource planning (ERP) systems. By leveraging ML algorithms, businesses can streamline operations, reduce manual interventions, and derive actionable insights from vast datasets within SAP environments. The research highlights key applications such as demand forecasting, fraud detection, and process automation, supported by case studies demonstrating quantitative improvements in efficiency and accuracy. A hybrid approach combining supervised and unsupervised learning models is proposed, enabling tailored predictions and automated decision-making. The findings underscore the transformative potential of ML in optimizing SAP workflows, paving the way for intelligent ERP solutions

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References


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