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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM38159
Volume:
8 |
10 |
Oct 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The utilization of HR analytics has become essential for enhancing decision-making in HR management. Organizations can utilize data from different HR functions to make well-informed decisions, resulting in improved workforce management and alignment with business objectives. This research delves into the significance of HR analytics in decision-making, with a focus on its requirements and advantages. Several important factors contribute to the necessity of utilizing HR analytics in decision-making. Complexity of Workforce Management: Managing large, diverse workforces is becoming increasingly complex, making traditional intuition-based decision-making inadequate. The use of HR analytics is necessary to introduce organization and data-driven insights into intricate HR functions like recruitment, employee retention, and performance management. Data-Driven Business Environment: Organizations need to embrace HR analytics due to the increasing emphasis on data-driven decision-making in all areas of business, including HR. Aligning HR strategies with overall business goals and basing HR decisions on data has become crucial in this context. Optimizing Human Capital Investments: HR analytics are crucial for organizations to measure the ROI of their human capital. Robust data is needed to make informed decisions about training, development, and employee engagement in order to allocate resources efficiently and effectively. Predictive Workforce Trends: Anticipating future workforce trends, like turnover or skill gaps, requires the implementation of predictive analytics in HR. This proactive strategy assists companies in maintaining their competitiveness by preparing for potential challenges in advance.
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Publication Date
10/24/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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