Human Capital Management 2.0: Cloud-Driven Innovations for Workforce Optimization

Dr. Emily, Harris and Oliver, Bennett (2022) Human Capital Management 2.0: Cloud-Driven Innovations for Workforce Optimization. International Journal of Trend in Scientific Research and Development, 6 (6). pp. 2361-2377. ISSN 2456-6470

Text 291 Human Capital Management 2.0 Cloud-Driven Innovations for Workforce Optimization.pdf Download (2MB)

Abstract

In today's rapidly evolving business landscape, the effective management of human capital has become a critical factor in ensuring organizational success. Traditional approaches to Human Capital Management (HCM) are being outpaced by the transformative power of cloud-driven technologies, ushering in a new era of Human Capital Management 2.0. This article explores the innovative capabilities of cloud computing in revolutionizing workforce optimization, offering a comprehensive overview of how cloud-based solutions are reshaping the ways organizations recruit, manage, and develop their workforce. By leveraging advanced cloud tools, organizations can enhance their talent acquisition processes, streamline performance management, and drive employee engagement, all while fostering a culture of continuous learning and development. The article delves into the integration of Artificial Intelligence (AI) and machine learning within cloud platforms to offer predictive analytics for talent management, real-time feedback systems, and personalized career development paths. Furthermore, it discusses how cloud-driven innovations facilitate remote workforce management, enhance collaboration, and ensure data security in a globally connected environment. Ultimately, the article emphasizes the importance of adopting Human Capital Management 2.0 strategies to achieve workforce optimization, improve organizational agility, and maintain a competitive edge in the digital age. By embracing these advancements, businesses can unlock the full potential of their workforce, driving both productivity and innovation.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	20 Nov 2024 11:16
Last Modified:	20 Nov 2024 11:16
URI:	http://eprints.umsida.ac.id/id/eprint/14649

Actions (login required)

View Item