A Two-Tier Solution to Converge People Analytics into HR Practices
Abstract
Last few years have seen an overwhelming increase in the application of People Analytics, as an HR practice globally. Organizations have formed specialized teams and software companies, are designing newest predictive systems to help HR with data extraction and understanding People Analytics. However, there are still a number of limitations reported in numerous studies, such as: data privacy and perception limitations hindering effective convergence of People Analytics into HR practices. This study holistically approaches the topic by critically reviewing and synthesizing the existing literature; by comparing region-wise business performance indicators to understand the role of People Analytics, performs content analysis on selected reports to identify perception level limitations of People Analytics, and finally generates correlated qualitative themes to address convergence limitations of People Analytics into HR practices. The study provides a Two-Tier solution validated through Content Analysis performed in the Nvivo. Data analysis shows emergence of two broad correlated themes - 1) limitations at functional level and 2) limitations at normative (psychological) level. The study provides specific guidelines to HR practitioners and business researchers on how to overcome application limitations related to People Analytics within their organizations.
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Use of AI for monitoring can boost employee retention by analyzing social media data to identify employees interested in leaving and introducing interventions to prevent them from leaving.
“The use of AI for monitoring can also boost employee retention by analyzing social media data to identify employees interested on leaving and introducing interventions to prevent them from leaving the company (Gaur and Riaz, 2019)”
From Unlocking the value of artificial intelligence in human resource management through AI capability framework (2023) · cites this paper as Gaur and Riaz, 2019
AI can be useful for monitoring, performance measurement and tracking employee morale.
“Additionally, AI can be useful for monitoring, performance measurement and tracking employee morale (Gaur and Riaz, 2019).”
From Unlocking the value of artificial intelligence in human resource management through AI capability framework (2023) · cites this paper as Gaur and Riaz, 2019
Cites
HR and analytics: Why HR is set to fail the big data challenge
Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M. (2016) · Human Resource Management Journal · doi:10.1111/1748-8583.12090 · Cited by 633 · cited 1× · see citing works
“Research on People Analytics has been extensively carried out for past 15 years, however availability of Big Data has enabled HR departments to gather better insights on employee processes for making important business decisions [5] [6].”
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Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023) · Human Resource Management Review · doi:10.1016/j.hrmr.2022.100899 · Cited by 927 · see citing works
- Authors
- Gaur, B., & Riaz, S.
- Affiliations
- Amity University (AE)
- Venue
- 2019 4th International Conference on Information Systems and Computer Networks (ISCON)
- Publisher
- IEEE
- Published
- 2019-11
- Pages
- 167-173
- OpenAlex
- W3011939819
- Cited by
- 16
- References
- 1
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 1 · 2020: 1
- FWCI
- 4.62
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Conference on Information Systems and Computer Networks (ISCON) (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employer Branding and e-HRM
- Keywords
- HR analytics, human resource management practices, data privacy, business performance indicators, HR professionals
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