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Journals / Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty / 2026 / Volume: 12 Issue: 3

Understanding the Employee: A Qualitative Study on Human Resources Analytics Practices

Fatma Zehra Yıldız(Tarsus Üniversitesi)0000-0002-0631-6589
Pages
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Publication Date
2025-09-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

According to the results of the study, it is seen that the main aim of HR analytics practices is to obtain data about the employee, to retain and understand the employee.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, it is aimed to examine the HR analytics practices applied in different businesses by utilizing the views and experiences of HR professionals.
📊
Key Findings & Data:Within the scope of the research, semi-structured interviews were conducted with 11 people from different positions and sectors.
💡
Conclusion & Impact:According to the results of the study, it is seen that the main aim of HR analytics practices is to obtain data about the employee, to retain and understand the employee.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:HR Analytics · HR Practices · HR Metrics

Abstract

In this study, it is aimed to examine the HR analytics practices applied in different businesses by utilizing the views and experiences of HR professionals. Within the framework of this aim, the research was constructed with qualitative method. The participants of the study consist of human resources professionals who work/are working in private sector organizations in Turkey. In this research, people from different ages, genders, sectors and positions were reached through purposive sampling method. Within the scope of the research, semi-structured interviews were conducted with 11 people from different positions and sectors. The data analyzed by content analysis method are presented as themes. Maxqda Analytics Pro program was used to visualize and present the data. Retention, turnover, exit interviews, recruitment, training, performance and compensation management, employee engagement and satisfaction were identified as themes. According to the results of the study, it is seen that the main aim of HR analytics practices is to obtain data about the employee, to retain and understand the employee. It has been revealed that more descriptive HR analytics are used. It can be stated that there are many metrics developed for recruitment and different employee retention practices. It is hoped that this study will expand the discussions on HR analytics and shed light on practitioners.

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Cite This Article

Yıldız, F. Z. (2025). Understanding the Employee: A Qualitative Study on Human Resources Analytics Practices. Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty, Volume: 12 Issue: 3. https://doi.org/10.30798/makuiibf.1562349

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References (84)

  1. Abellán-Sevilla, A.-J., & Ortiz-de-Urbina-Criado, M. (2023). Smart human resource analytics for happiness management. Journal of Management Development, 42(6), 514–525. https://doi.org/10.1108/JMD-03-2023-0064
  2. Anthun, K. S., Anthun, K. S., Håland, E., & Lillefjell, M. (2024). What influences the use of HR analytics in Human Resource management in Norwegian municipal health care services? BMC Health Services Research, 24, https://doi.org/10.1186/s12913-024-11610-y
  3. Aral, A., Brynjolfsson, E., & Wu, L. (2012). Three-way complementarities: Performance pay, HR analytics and information technology. Management Science, 58(5), 913–931.
  4. Armstrong, M. (2017). Armstrong’un stratejik insan kaynakları yönetimi el kitabı (Y. D. Gürol & E. Gemici, Transl.). Nobel Kitabevi.
  5. Arora, M., Prakash, A., Mittal, A., & Singh, S. (2021 December 7-8). HR analytics and artificial intelligence: Transforming human resource management. (Conference presentation) International Conference on Decision Aid Sciences and Application, Sakheer, Bahrain. https://doi.org/10.1109/DASA53625.2021.9682325
  6. Bahuguna, P.C., Srivastava, R. & Tiwari, S. (2024). Human resources analytics: where do we go from here?. Benchmarking: An International Journal, 31(2), 640-668. https://doi.org/10.1108/BIJ-06-2022-0401
  7. Bar-Gil, O., Ron, T., & Czerniak, O. (2024). AI for the people? Embedding AI ethics in HR and people analytics projects. Technology in Society, 77, 1-12. https://doi.org/10.1016/j.techsoc.2024.102527
  8. Berg, B. L., & Lune, H. (2015). Sosyal bilimlerde nitel araştırma yöntemleri (H. Aydın, Transl.). Eğitim Kitabevi.
  9. Black, J.S. & van Esch, P. (2020), AI-enabled recruiting: what is it and how should a manager use it?. Business Horizons, 63(2), 215-226.
  10. Bondarouk, T., & Brewster, C. (2016). Conceptualising the future of HRM and technology research. The International Journal of Human Resource Management, 27(21), 2652–2671.
  11. Boudreau, J. & Cascio, W. (2017). Human capital analytics: why are we not there?. Journal of Organizational Effectiveness: People and Performance, 4(2), 119-126.
  12. Cayrat, C., & Boxall, P. (2022). Exploring the phenomenon of HR analytics: A study of challenges, risks, and impacts in 40 large companies. Journal of Organizational Effectiveness: People and Performance, 9(4), 572-590. https://doi.org/10.1108/JOEPP-08-2021-0238
  13. Charmaz, K. (2006). Constructing grounded theory: A practical guide through qualitative analysis. Sage Publications.
  14. Charmaz, K. (2015). Gömülü (Grounded) teori yapılandırması (R. Hoş, Transl.). Seçkin Yayıncılık.
  15. Chatterjee, S., Chaudhuri, R., Vrontis, D., & Siachou, E. (2022). Examining the dark side of human resource analytics: An empirical investigation using the privacy calculus approach. International Journal of Manpower, 43(1), 52-74. https://doi.org/10.1108/IJM-02-2021-0087
  16. Chalutz, B.-G. H. (2019). An ROI-based review of HR analytics: Practical implementation tools. Personnel Review, 48(6), 1429–1448. https://doi.org/10.1108/PR-11-2017-0362
  17. Creswell, J. W. (2018). Nitel araştırma yöntemleri: Beş yaklaşıma göre nitel araştırma ve araştırma deseni (M. Bütün & S. B. Demir, Transl.). Siyasal Kitabevi.
  18. Das, A. K., & Malik, P. (2024). Ascertaining factors inducing engagement and stay intention among Gen Z: A qualitative study in the Indian context. International Journal of Organizational Analysis. https://doi.org/10.1108/IJOA-09-2023-3994
  19. DeCenzo, D. A., Robbins, S. P., & Verhulst, S. L. (2017). İnsan kaynakları yönetiminin temelleri (C. Çetin & M. L. Arslan, Transl.). Nobel Kitapevi.
  20. Dahlbom, P., Siikanen, N., Sajasalo, P. & Jarvenpää, M. (2020). Big data and HR analytics in the digital era. Baltic Journal of Management, 15(1), 120-138. https://doi.org/10.1108/BJM-11-2018-0393
  21. De Oliveira, L. B., Cavazotte, F., & Dunzer, R. A. (2019). The interactive effects of organizational and leadership career management support on job satisfaction and turnover intention. International Journal of Human Resource Management, 30(10), 1583–1603. https://doi.org/10.1080/09585192.2017.1298650
  22. Dulebohn, J. H., & Johnson, R. D. (2013). Human resource metrics and decision support: A classification framework. Human Resource Management Review, 23, 71–83.
  23. Davenport, T. (2019, April 18). Is HR the most analytics driven function? Harvard Business Review. https://hbr.org/2019/04/is-hr-the-most-analytics-driven-function
  24. Erlandson, D. A., Harris, E. L., Skipper, B. L., & Allen, S. D. (1993). Doing naturalistic inquiry. Sage.
  25. Escolar-Jimenez, C. C., Matsuzaki, K., Okada, K., & Gustilo, R. C. (2019). Data-driven decisions in employee compensation utilizing a neuro-fuzzy inference system. International Journal of Emerging Trends in Engineering Research, 7(8), 163-169.
  26. Falletta, S.V. & Combs, W.L. (2021). The HR analytics cycle: a seven-step process for building evidence-based and ethical HR analytics capabilities. Journal of Work-Applied Management, 13(1), 51-68.
  27. Fernandez, V. & Gallardo-Gallardo, E. (2021), Tackling the HR digitalization challenge: key factors and barriers to HR analytics adoption. Competitiveness Review, 31(1), 162-187. https://doi.org/10.1108/CR-12-2019-0163
  28. Ferraris, A., Mazzoleni, A., Devalle, A. & Couturier, J. (2019). Big data analytics capabilities and knowledge management: impact on firm performance. Management Decision, 57(8), 1923-1936.
  29. Fitz-enz, J., & Mattox, J. II. (2014). Predictive analytics for human resources. Wiley and Sons.
  30. Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. Aldine.
  31. Green, D. (2017). The best practices to excel at people Analytics. Journal of Organizational Effectiveness: People and Performance, 4(2), 137-144.
  32. Guenole, N., Ferrar, J., & Feinzig, S. (2017). The power of people: Learn how successful organizations use workforce analytics to improve business performance, Cisco Press.
  33. Guest, G., Bunce, A.E., & Johnson, L. (2006). How many interviews are enough? Field Methods, (18), 59-82.
  34. Harris, J. G., Craig, E., & Light, D. A. (2011). Talent and analytics: New approaches, higher ROI. Journal of Business Strategy, 32(6), 4–13. https://doi.org/10.1108/02756661111180087
  35. Hom, P. W., Lee, T. W., Shaw, J. D., & Hausknecht, J. P. (2017). One hundred years of employee turnover theory and research. Journal of Applied Psychology, 102(3), 530–545. https://doi.org/10.1037/apl0000103
  36. Isson, J. P., & Harriott, J. S. (2016). People analytics in the era of big data: Changing the way you attract, acquire, develop, and retain talent. John Wiley & Sons.
  37. Jeske, D. & Calvard, T. (2020). Big data: Lessons for employers and employees. Employee Relations, 42(1), 248-261.
  38. Jiang, Y., & Akdere, M. (2022). An operational conceptualization of human resource analytics: Implications for human resource development. Industrial and Commercial Training, 54(1), 183–200. https://doi.org/10.1108/ICT-04-2021-0028
  39. Krishnan, L. R. K., Praveen, K., & Poorani, S. (2024). Artificial intelligence in human resource management: Enhancing efficiency and transforming employee experience. The Indian Journal of Industrial Relations, 59(4), 589–605.
  40. Levenson, A. & Fink, A. (2017). Human capital analytics: too much data and analysis, not enough models and business insights. Journal of Organizational Effectiveness, 4(2), 145-156.
  41. Levenson, A. (2011) Using targeted analytics to improve talent decisions. People & Strategy, 34(2), 34–43.
  42. Malik, A., Thevisuthan, P. & De Sliva, T. (2022). Artificial intelligence, employee engagement, experience, and HRM. In Malik, A. (Ed.), Strategic Human Resource Management and Employment Relations: an International Perspective. Springer International Publishing, pp. 171–184. https://doi.org/10.1007/978-3-030-90955-0_16
  43. Margherita, A. (2022). Human resources analytics: A systematization of research topics and directions for future research. Human Resource Management Review, 32(2), https://doi.org/10.1016/j.hrmr.2020.100795
  44. Marler, J.H. & Boudreau, J.W. (2017). An evidence-based review of HR Analytics. International Journal of Human Resource Management, 28(1), 3-26.
  45. McCartney, S., & Fu, N. (2022). Promise versus reality: a systematic review of the ongoing debates in people analytics. Journal of Organizational Effectiveness: People and Performance, 9 (2), 281-311.
  46. McIver, D., Lengnick-Hall, M. L., & Lengnick-Hall, C. A. (2018). A strategic approach to workforce analytics: Integrating science and agility. Business Horizons, 61(3), 397-407. https://doi.org/10.1016/j.bushor.2018.01.005
  47. Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. Sage.
  48. Merriam, S. B. (2015). Nitel araştırma: Desen ve uygulama için bir rehber (S. Turan, Transl.). Nobel Kitap.
  49. Mishra, S. N., Lama, D. R., & Pal, Y. (2016). Human resource predictive analytics (HRPA) for HR management in organizations. International Journal of Scientific and Technology Research, 5(5), 33–35.
  50. Mouton, J. (2001). How to succeed in your master’s and doctoral studies: A South African guide and resource book. Van Schaik Publishers.
  51. University of Oxford. (2021, December, 2). Informed consent. Research Support. https://researchsupport.admin.ox.ac.uk/governance/ethics/resources/consent#collapse281096
  52. Özçelik, B. (2017, June 9). İK'nın geleceği büyük veride. Hürriyet İK. https://www.hurriyet.com.tr/ik-yeni-ekonomi/iknin-gelecegi-buyuk-veride-40423034
  53. Patton, M. Q. (2018). Nitel araştırma ve değerlendirme yöntemleri (M. Bütün & S. B. Demir, Transl.). Pegem Akademi.
  54. Peeters, T., Paauwe, J. & Van De Voorde, K. (2020). People analytics effectiveness: developing a framework. Journal of Organizational Effectiveness, 7(2), 203-219.
  55. Pillai, R., & Sivathanu, B. (2022). Measure what matters: descriptive and predictive metrics of HRM-pathway toward organizational performance. International Journal of Productivity and Performance Management, 71(7), 3009-3029. https://doi.org/10.1108/IJPPM-10-2020-0509
  56. Prentice, C., Wong, I. A. & Lin, Z. (2023). Artificial intelligence as a boundary-crossing object for employee engagement and performance. Journal of Retailing and Consumer Services, 73, 1-8. https://doi.org/10.1016/j.jretconser.2023.103376
  57. Protsiuk, O. (2024). The mediation effect of supervisor support and total rewards on the relationship between flexible work arrangements and turnover intentions in Gen Z. International Journal of Organizational Analysis. https://doi.org/10.1108/IJOA-04-2024-4418
  58. Punch, K. F. (2016). Sosyal araştırmalara giriş: Nicel ve nitel yaklaşımlar (D. Bayrak, H. B. Arslan, & Z. Akyüz, Transl.). Siyasal Kitapevi.
  59. Ramamurthy, K., Singh, M., Yu, Y., Aspis, J., Iames, M., Peran, M. & Held, Q. (2015 19-21 October). A talent management tool using propensity to leave analytics. (Conference presentation) 2015 IEEE International Conference on Data Science and Advanced Analytics, Paris, France. https://ieeexplore.ieee.org/document/7344853
  60. Saxena, M., & Mishra, D. K. (2023). Artificial intelligence: The way ahead for employee engagement in corporate India. Global Knowledge, Memory and Communication. https://doi.org/10.1108/GKMC-09-2022-0215
  61. Santoro, G., Fiano, F., Bertoldi, B., & Ciampi, F. (2019). Big data for business management in the retail industry. Management Decision, 57(8), 1980-1992.
  62. Saldaña, J. (2019). Nitel araştırmacılar için kodlama el kitabı (A. T. Akcan, & S. N. Şad, Transl.). Pegem Akademi.
  63. Serhan, C., Nasr, N., Cheikh, G., & Nachar, G. (2024). Retaining young employees in the hospitality and tourism sector: The role of workplace context and management practices. EuroMed Journal of Business. https://doi.org/10.1108/EMJB-01-2024-0009
  64. Sharma, A., & Sharma, T. (2017). HR analytics and performance appraisal system: A conceptual framework for employee performance improvement. Management Research Review, 40(6), 684–697. https://doi.org/10.1108/MRR-04-2016-0084
  65. Shrivastava, S., Nagdev, K. & Rajesh, A. (2018). Redefining HR using people analytics: the case of Google. Human Resource Management International Digest, 26(2) 3-6. https://doi.org/10.1108/HRMID-06-2017-0112
  66. Singh, R., Sharma, P., Foropon, C., & Belal, H. M. (2022). The role of big data and predictive analytics in employee retention: A resource-based view. International Journal of Manpower, 43(2), 411-447. https://doi.org/10.1108/IJM-03-2021-0197
  67. Singh, S., & Muduli, A. (2021). Factors influencing information sharing intention for human resource analytics. Economic Studies Journal, 3, 115–133.
  68. Storm, M., & Borgman, H. P. (2020 January 7). Understanding challenges and success factors in creating a data-driven culture. (Conference presentation) Proceedings of the 53rd Hawaii International Conference on System Sciences, Manoa. https://doi.org/10.24251/HICSS.2020.620
  69. Stone, D. L., Lukaszewski, K. M. & Johnson, R. D. (2024). Will artificial intelligence radically change human resource management processes?, Organizational Dynamics, 53(1), https://doi.org/10.1016/j.orgdyn.2024.101034
  70. Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques (2th ed.). SAGE.
  71. Sweeney, J. (2010). United Health Group leverages predictive analytics for enhanced staffing and retention. In J. Fitz-enz (Eds.), The new HR analytics: Predicting the economic value of your company’s human capital investments (pp. 265–270). AMACOM.
  72. Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review. https://doi.org/10.1177/0008125619867910
  73. Thakral, P., Srivastava, P. R., Dash, S. S., Jasimuddin, S. M., & Zhang, Z. J. (2023). Trends in the thematic landscape of HR analytics research: A structural topic modeling approach. Management Decision, 61(12), 3665-3690. https://doi.org/10.1108/MD-01-2023-0080
  74. Thakur, S. J., Bhatnagar, J., Farndale, E., & Aeron, P. (2024). How do human resources analytics create value for organizations? A qualitative investigation. Journal of Organizational Effectiveness: People and Performance. https://doi.org/10.1108/JOEPP-10-2022-0303
  75. Tursunbayeva, A., Di Lauro, S., & Pagliari, C. (2018). People analytics—a scoping review of conceptual boundaries and value propositions. International Journal of Information Management, 43, 224-247.
  76. Tüzüner, L. (2011). İnsan kaynakları yönetiminde ölçme ve değerlendirme. Beta Yayınları.
  77. Ulrich, D., & Dulebohn, J.H. (2015). Are we there yet? What’s next for HR?. Human Resource Management Review, 25(2),188-204.
  78. Ulrich, D., Allen, J., Brockbank, W., Younger, J., & Nyman, M. (2012). İK dönüşümü: İnsan kaynaklarını dışarıdan içeriye doğru inşa etmek (E. Eren, Tansl.). Hümanist Kitap Yayıncılık.
  79. Ünlü, M., & Bayraktar, O. (2017). İnsan kaynakları işlevlerinin etkinliğinin değerlendirilmesi. Ekonomi İşletme ve Yönetim Dergisi, 1(2), 78-96.
  80. Verghese, N., & Green, D. (2023, November 29). The İmportance of ethics in people analytics for leading companies. myHRfuture. https://www.myhrfuture.com/blog/the-importance-of-ethics-in-people-analytics-for-leading-companies
  81. Wang, L., Zhou, Y., Sanders, K., & Marler, J. H. (2024). Determinants of effective HR analytics implementation: An in-depth review and a dynamic framework for future research. Journal of Business Research, 170. https://doi.org/10.1016/j.jbusres.2023.114312
  82. Wilkinson, S., & Haar, J. (2023). Smart device use in a COVID-19 world: Exploring work–family conflict and turnover intentions. Asia Pacific Journal of Human Resources, 61(4), 981-1007. https://doi.org/10.1111/1744-7941.12370
  83. Willig, C. (2008). Introducing qualitative research in Psychology. Open University Press. Yıldırım, A., & Şimşek, H. (2018). Sosyal bilimlerde nitel araştırma yöntemleri (11th ed.). Seçkin Yayıncılık.
  84. Zel, S., & Kongar, E. (2020 21-25 September). Transforming digital employee experience with artificial intelligence. (Conference presentation) 2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G), Geneva, Switzerland. https://ieeexplore.ieee.org/document/9311088