International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Building Real-Time Workforce Analytics Dashboards in SAP SuccessFactors Using SAP BTP and Embedded Machine Learning Models

Abstract

This study investigates the design and deployment of real-time workforce analytics dashboards within the SAP SuccessFactors ecosystem, leveraging the capabilities of the SAP Business Technology Platform (BTP) and embedded machine learning models. The primary objective is to transform static HR reporting into predictive, interactive decision support tools. Using a design science approach, the research integrates data pipelines from SAP SuccessFactors through SAP Data Intelligence, processes this information via SAP HANA, and visualizes insights using SAP Analytics Cloud. Custom machine learning models, trained on historical HR data, predict employee attrition and engagement scores. The results show substantial improvements in the accuracy and speed of workforce analysis, enabling timely interventions in talent management and strategic planning. Stakeholder feedback highlights the dashboard’s role in proactive workforce governance. The study concludes that embedding machine learning into HR dashboards through SAP BTP enables data-driven decision-making and positions HR departments as strategic business enablers.

Country : USA

1 Manoj Parasa

  1. USA

IRJIET, Volume 6, Issue 10, October 2022 pp. 148-152

doi.org/10.47001/IRJIET/2022.610030

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