AI-Powered Workforce Forecasting in SAP Time Management: Predictive Models for Staffing Needs, Absenteeism, and Peak Demand Planning
This research explores the application of Artificial Intelligence (AI) in SAP Time Management to enhance the accuracy and responsiveness of workforce demand forecasting. It solves forecasting staff requirements, absenteeism trends, and demand spikes using predictive models of historical attendance trends, company calendars, and external data. With machine learning algorithms implemented through SAP Analytics Cloud and SAP Business Technology Platform, the research demonstrates how companies can transition from reactive to proactive workforce planning. The research process involves data ingestion from SAP Time and Attendance Management, preprocessing using SAP Data Intelligence, and model training using regression and classification techniques. Results demonstrate a dramatic increase in forecasting precision and employee resource utilization. The research concludes that AI-powered time management systems empower HR executives to dynamically match workforce availability to business requirements and minimize absenteeism-linked risks.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-04-30
- DOI
- https://doi.org/10.5281/zenodo.15387284
- Primary Topic
- AI and HR Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00