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HR ANALYTICS AND ITS MODERATING FACTORS - A REVIEW IN KASIM TEXTILE MILL PRIVATE LTD, MADURAI

Authors: B. Divya Bharathi*, Dr. K. Binith Muthukrishnan** & Dr. B. Velmurugan***;

HR ANALYTICS AND ITS MODERATING FACTORS - A REVIEW IN KASIM TEXTILE MILL PRIVATE LTD, MADURAI

Abstract

This theoretical article elaborates the moderating factors of the human resources analysis (HR Analytics), considered as one of the main initiatives in human resources today. It seems that the analysis simplifies the decision-making process by proposing a more data-driven approach. Although human resource analysis is a priority in most organizations, the implementation process is slow and only a minor proportion of them even report having implemented it. HR analysis is not progressing as many academics have suggested over the last 10 years. Therefore, it seems necessary to identify the modulatory factors of HR Analytics that promote or hinder its success. The number of academic research articles dealing with this subject is very small. The impact of moderating factors on the level of human resource analysis is vague and unexplored. This paper offers potential explanations of the relationship between moderators and HR analysis and provides suggestions to organizations on how best to address these factors. In the first part of this article, the development and theoretical assumptions for a more data-driven approach to human resource decision making are developed. Then the concept of HR Analytics will be defined. The third section presents case studies and examines the importance of the practice of human resource analysis in organizations. In the following, each moderation factor will be examined in detail. Finally, the main conclusions of the subject under study are discussed and summarized.

{"references": ["1.\tBoudreau, J. W., & Ramstad, P. M. (2007). Beyond HR: The new science of human capital. Boston, MA: Harvard Business School Press. 2.\tBoudreau, J., & Lawler, E. E. (2014). Stubborn traditionalism in HRM: Causes and consequences. Human Resource Management Review, 24(3), 232\u2013244. http://doi.org/10.1016/j.hrmr.2014.03.005 3.\tDouglas, B. G., & Young, M. B. (2015). Employee Trust Seen as Essential for HR Analytics, 14(8), 14\u201316. 4.\tFecheyr-Lippens, Bruce; Schaninger, Bill; Tanner, K. (2015). Power to the new people analytics. McKinsey Quarterly, (1), 61\u201363. Retrieved from http://www.mckinsey.com/business-functions/organ ization/our-insights/power-to-thenew-people-analytics# 5.\tGardner, N., Mcgranahan, D., & Wolf, W. (2011). Question for your HR chief: Are we using our \"people data\" to create value? McKinsey Quarterly, (2), 1\u20135. 6.\tGoldstein, J. (2015). Digital technology demand is transforming HR. Workforce Solutions Review, (November), 28\u201329."]}

Keywords

HR Analytics, People Analytics, HR Metrics, Big Data, Strategic HRM.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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