International Journal of Science, Engineering and TechnologyAuthors: Prithul More
Abstract: The transition of modern enterprises toward digital maturity has redefined workforce management from a support function into a strategic powerhouse. This review article examines the systematic integration of big data analytics and machine learning within SAP-based environments, specifically focusing on the synergy between SAP S/4HANA and SuccessFactors. By leveraging the vast data repositories inherent in these systems, enterprises can move beyond historical reporting to achieve predictive and prescriptive capabilities. We explore how machine learning models enhance the entire employee lifecycle, from optimizing talent acquisition and predicting attrition to automating complex demand forecasting for shift-based labor. The core of this framework lies in the ability of the SAP Business Technology Platform to harmonize structured transactional data with unstructured behavioral signals, creating a unified business data fabric. This article analyzes the technical architecture required for such integration, highlighting the role of in-memory computing and cloud-native analytics. Furthermore, we address the critical barriers to implementation, including the challenges of data silos, the complexities of global privacy regulations like GDPR, and the necessity for explainable artificial intelligence in human resources. By synthesizing current technological trends and future directions such as the rise of generative AI copilots and total workforce management this review provides a comprehensive roadmap for organizations seeking to transform their human capital into a measurable competitive advantage through data-driven intelligence.
DOI: https://doi.org/10.5281/zenodo.18221586
