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Publication: IIP Proceedings Year: 2022, Month: November Page No: 103-110, ISSN/ISBN: 978-93-95632-62-1, DOI/Link: https://www.rsquarel.org/assets/docupload/rsl2023073EB9F4AAC515C.pdf
PREDICTIVE HR ANALYTICS - A GAME CHANGER
Area/Stream: Management, Authors: D. Sandhya, Chaithra N Keywords: Predictive Analytics, Employee Performance, Future of Organizations, Decision Support Book Name /series: Futuristic Trends in Management, Volume 2, Book 8, Part 1, Chapter 11Publication: IIP Proceedings Year: 2022, Month: November Page No: 103-110, ISSN/ISBN: 978-93-95632-62-1, DOI/Link: https://www.rsquarel.org/assets/docupload/rsl2023073EB9F4AAC515C.pdf
Abstract:
Predictive Analytics is a new trend in HR. It is HR’s new normal. In the present scenario Business organizations are facing some issues and challenges such as gross margin falls, Employee turnover, rise in turnover, increased absenteeism, etc., Organisations can collect the employee’s data to forecast their future behavior to take different decisions regarding the employees to increase the performance of the company. Predictive Analytics helps to forecast the future by estimating current and historical data. The future events and behavior of employees can be predicted by various techniques and models of Predictive analytics. The Predictive Analytics model gives a score for every event. The highest score implies the higher likelihood of occurrence of an event and the lowest score implies the lower likelihood of occurrence of an event. Transactional and historical data are considered by these models to estimate the solutions for various issues in business related to human resources. These models help identify the opportunities and risk of each employee and helps concern individual customer, or manager of a company. The Predictive Analytics models have dominated in the field of HR due to increased attention toward decision support solutions.
Cite this: D. Sandhya, Chaithra N,"PREDICTIVE HR ANALYTICS - A GAME CHANGER", Futuristic Trends in Management, Volume 2, Book 8, Part 1, Chapter 11, November, 2022, 103-110, 978-93-95632-62-1, https://www.rsquarel.org/assets/docupload/rsl2023073EB9F4AAC515C.pdf
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