| Autor: |
Hamieddine, Chaymae, Tigani, Smail, Akioud, Malika, Saadane, Rachid, Chehri, Abdelah |
| Předmět: |
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| Zdroj: |
Procedia Computer Science; 2024, Vol. 246, p4901-4908, 8p |
| Abstrakt: |
This research paper presents a novel formal framework designed for piloting human resources performance and fostering agile HR management within organizations. The framework facilitates the systematic collection of HR data, enabling the computation of sensitive Key Performance Indicators (KPIs) essential for predictive analytics and data-driven decision-making. Through this framework, top management gains a clear understanding of recruitment and training strategies, as well as the ability to distinguish between easily-replaceable and critical resources. The framework empowers organizations to optimize resource allocation, enhance operational efficiency, and mitigate risks associated with human capital management. The integration of predictive analytics enables the development of comprehensive dashboards, providing actionable insights to guide strategic HR initiatives and ensure organizational success in dynamic environments. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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