A study on “Human resource analytics for decision making in international business machine in India and United States”
Keywords:
HR analytics, decision making, IBM, artificial intelligence, ethics.Abstract
For any organization, human resources (HR) are important. It brings with it, in addition to experience, the capacity and technical skills that are essential for any organization's long-term success. Organizations have often had trouble determining the efficiency, status, and opportunities of their human resources. Organizations are looking for even more intelligent choices, from attracting the right talent to maintaining the best talent. HR-analytics has been mostly used in the Western IT industry, but it is now making inroads in the Indian IT market as well. HR analytics has a lot of potential in the Indian IT industry, but HR systems, teams, and people skills have a lot of flaws. This research explores the advantages and disadvantages of HR analytics, as well as the role of HR analytics in decision-making at IBM, a major player in the global IT industry. HR engagement, ethics in analytics, and artificial intelligence in HR and analytics are the main factors in IBM's better use of HR analytics in better business decisions, according to the study's findings.
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References
Afzal, M. (2019). HR ANALYTICS: CHALLENGES AND PROSPECTS OF INDIAN IT SECTOR.
International Journal of Management, IT & Engineering .
Barrientos, M.-p. (2014). Unlock the people equation: Using workforce analytics to drive business results.
IBM corporation, produced in USA .
Brahim Jabir, N. F. (2019). HR analytics a roadmap for decision making: case study. Indonesian Journal of Electrical Engineering and Computer Science , 979-990.
Dr. Nigel Guenole & Jonathan Ferrar. (2014). Active employee participation in workforce analytics.
Thought Leadership Whitepaper, IBM Corporation .
Dr. P. Raghunatha Reddy “‘Hr Analytics’ - An Effective Evidence Based HRM Tool." International Journal of Business and Management Invention (IJBMI) 6.7 (2017): 23-34.
Dr. Abdul Quddus Mohammed, HR Analytics: A Modern Tool in HR for Predictive Decision Making, Journal of Management, 6(3), 2019, pp. 51-63.
ETHICAL DILEMMAS IN HR ANALYTICS: Perspectives from the global workforce. (2018). IBM Corporation, Software Group Produced in the United States of America .
Jiang, Fengzhu, "Data Analytics Helps Business Decision Making" (2017). Student Theses, Papers and Projects (Computer Science). 3.
Lakshmikeerthi, D. P. (2017). ‘Hr Analytics’ - An Effective Evidence Based HRM Tool. International Journal of Business and Management Invention , 23-34.
Malhotra, T. S. (2020). Workforce Analytics: Increasing Managerial Efficiency In Human Resource. INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 01, JANUARY 2020 .
Nagabhushanam, M. M. (2015). UNDERSTANDING THE ADOPTION OF HR ANALYTICS IN INDIAN CORPORATIONS : A CASE STUDY ON SELECTED INDIAN PRIVATE
MULTINATIONAL COMPANY. International Journal of Business and Administration Research Review , 262-268.
Nigel Guenole, P. &. (2018). The Business Case for AI in HR: With Insights and Tips on Getting Started.
IBM corporation, produced in USA .
NIGEL GUENOLE, P. S. (2018). ETHICAL DILEMMAS IN HR ANALYTICS: Perspectives from the
global workforce. IBM Corporation, Software Group Produced in the United States of America .
Nigel Guenole, S. F. (2017). HR analytics readiness: How does Europe compare to the rest of the world?
IBM corporation .
Nigel Guenole, S. F. (2015). Starting the workforce: Analytical journey- The first 100 days. IBM corporation .
Sousa, M. J. (2019). Decision-Making based on Big Data Analytics for People Management in Healthcare Organizations. Journal of Medical Systems .
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