Augmenting SAP S/4HANA Sales and Distribution Processes through AI/ML-Driven Predictive Analytics: A 2024 Enterprise Perspective

Authors

  • Surya Narayana Chakka Independent Researcher, USA
  • Venu Gopal Avula Independent Researcher, USA
  • Rahul Modak Independent Researcher, USA

Keywords:

AI integration, SAP S/4HANA, predictive analytics, sales accuracy, order fulfillment, inventory management

Abstract

This study explores the integration of Artificial Intelligence (AI) and Machine Learning (ML) within SAP S/4HANA to enhance Sales and Distribution (SD) processes. It reviews what AI/ML-based predictive analytics hold in terms of optimizing delivery and demand forecast targets, inventory and sales accuracy. By means of a mixed-method research design, real-world case studies were observed across the globe-retail and leader global car manufacturing companies that use SAP S/4HANA with AI / ML capabilities. The most important results of work have been recorded in increased operational efficiency, i.e. 20 percent more on-time deliveries and a 15 percent rise in accuracy of sales. The adoption of AI/ ML minimized stockouts, overstock and excess stock costs, and furnished the businesses with data-driven intelligence to make more sound decisions. The study comes to a conclusion that AI/ML integration of SAP S/4HANA has considerable advantages to SD processes, enhancing business performance, helping it gain competitive advantage as we become a digital-first world. In future, studies may be conducted on whether these technologies are applicable at large in various industries.

Published

20-05-2024

How to Cite

Surya Narayana Chakka, Venu Gopal Avula, & Rahul Modak. (2024). Augmenting SAP S/4HANA Sales and Distribution Processes through AI/ML-Driven Predictive Analytics: A 2024 Enterprise Perspective. Well Testing Journal, 33, 629–643. Retrieved from https://welltestingjournal.com/index.php/WT/article/view/200

Issue

Section

Original Research Articles

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