Araştırma Makalesi
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HUMAN RESOURCES ANALYTICS MATURITY SCALE: A SCALE DEVELOPMENT STUDY

Yıl 2022, Cilt: 7 Sayı: 2, 459 - 489, 26.12.2022
https://doi.org/10.54452/jrb.1107177

Öz

In the early 2000s, human resources analytics (HR analytics), emerged as a savior to reveal the strategic importance of HR departments and has begun to be used by many organizations today around the world. Recently, there has been increasing interest in using HR analytics in Turkey as well. Data-based HR management is likely to gain more importance in terms of the development of organizational models shaped by new technologies and sustainable change. In that respect, HR analytics has the potential to be an important and effective tool of this agenda. The concept of HR analytics maturity focuses on the assessment of organizations’ HR analytics capability.
In this context, the aim of this research is to develop a valid and reliable measurement tool that can be used to assess HR analytics maturity of organizations operating in Turkey. A 41-item measurement tool was developed with content validity study and tested with the data obtained from 204 employees who carry out roles relating to HR analytics and HR management in 199 different organizations operating in Turkey. Exploratory factor analysis was used to evaluate the scale’s factor structure, and a three-factor structure containing 19-item obtained, explaining 71.07% of the total variance. The Cronbach’s Alpha of the scale was .958. Criterion-related validity analysis showed that the relationships between HR analytics maturity, organizational agility and perceived managerial support were significant. Consequently, the psychometric analyzes showed that the ‘‘HR Analytics Maturity Scale’’ is a valid and reliable tool to evaluate HR analytics maturity of organizations.

Kaynakça

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İNSAN KAYNAKLARI ANALİTİĞİ OLGUNLUĞU ÖLÇEĞİ (İKAOÖ): BİR ÖLÇEK GELİŞTİRME ÇALIŞMASI

Yıl 2022, Cilt: 7 Sayı: 2, 459 - 489, 26.12.2022
https://doi.org/10.54452/jrb.1107177

Öz

İnsan kaynakları (İK) bölümlerinin artan stratejik önemi ile birlikte, 2000’li yılların başlarında bir kurtarıcı olarak gündeme gelen insan kaynakları analitiği (İK analitiği), günümüz dünyasında birçok örgüt tarafından kullanılmaya başlanmıştır. Türkiye’de de son yıllarda İK analitiğini kullanan örgütlerin sayısında artış yaşanmaktadır. Yeni teknolojilerin şekillendireceği örgüt modellerinin gelişimi ve sürdürülebilir değişim açısından, veriye dayalı İK yönetiminin daha fazla gündeme geleceği ve İK analitiğinin, bu gündemin önemli ve etkili bir aracı olma potansiyeli taşıyacağı söylenebilir. İK analitiği olgunluğu ise örgütlerin İK analitiği yeteneğinin değerlendirilmesine odaklanmaktadır.
Bu bağlamda bu araştırmanın amacı, Türkiye’de faaliyet gösteren örgütlerin İK analitiği olgunluğunun değerlendirilmesinde kullanılabilecek geçerli ve güvenilir bir ölçüm aracının geliştirilmesidir. Kapsam geçerliği çalışması sonucu oluşturulan 41 maddelik ölçme aracı, Türkiye’de faaliyet gösteren 199 farklı örgütte İK analitiği ve İK yönetimi ile ilgili görevleri yürüten 204 katılımcıdan oluşan çalışma grubu üzerinde uygulanmıştır. Ölçeğin faktör yapısı açımlayıcı faktör analiziyle incelenmiş ve analiz sonucunda 19 maddeden oluşan bir ölçek elde edilmiştir. Üç faktörlü yapıdan oluşan ölçek, toplam varyansın % 71.07’sini açıklamıştır. Ölçeğin Cronbach’s Alpha katsayısı, .958 olarak tespit edilmiştir. Ölçüt-bağıntılı geçerlik analizi ise İK analitiği olgunluğu ile örgütsel çeviklik ve algılanan yönetici desteği arasındaki ilişkilerin anlamlı olduğunu göstermiştir. Sonuç olarak bu çalışma ile gerçekleştirilen psikometrik analizler, geliştirilen “İK Analitiği Olgunluğu Ölçeği”nin (İKAOÖ), Türkiye'de faaliyet gösteren örgütler tarafından İK analitiği olgunluğunu ölçmek üzere kullanılabilir nitelikte, geçerli ve güvenilir bir araç olduğunu göstermiştir.

Kaynakça

  • Akkaya, B., & Tabak, A. (2018). Örgütsel Çeviklik Ölçeğinin Türkçeye Uyarlanması: Geçerlik ve Güvenirlik Çalışması. İş ve İnsan Dergisi, 5/(2), 185-206.
  • Andersen, M. K. (2017). Human capital analytics: the winding road. Journal of Organizational Effectiveness: People and Performance, 4(2), 133-136. https://doi.org/10.1108/JOEPP-03-2017-0024.
  • Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M. (2016). HR and analytics: Why hr is set to fail the big data challenge. Human Resource Management Journal, 26(1), 1-11. https://doi.org/10.1111/1748-8583.12090.
  • Aral, S., Brynjolfsson, E., & Wu, L. (2012). Three-Way complementarities: Performance pay, human resource analytics, and information technology. Management Science, 58(5), 913-931. https://www.jstor.org/stable/41499529.
  • Aydın Göktepe, E. (2017). Algılanan Yönetici desteği ölçeği: geliştirilmesi, geçerliliği ve güvenirliliği. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 46, 31-48.
  • Bauer, T., Erdoğan, B., Caughlin, E. D., & Truxillo, D. M. (2019). Human resources management people, data and analytics. California: Sage Publications.
  • Bayram, N. (2018). Örgütlerde iş analitiği kullanımının geliştirilmiş teknoloji kabul modeli ile incelenmesi. (Yayınlanmamış Yüksek Lisans Tezi). Orta Doğu Teknik Üniversitesi, Ankara.
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  • Bersin, J. (2012, December 27). New Research: BigData in HR as Huge Opportunity. Erişim Adresi: https://joshbersin.com/2012/04/new-research-bigdata-in-hr-as-huge-opportunity/.
  • Bersin, J. (2013, February 17). Big Data in Human Resources: Talent Analytics (People Analytics) Comes of Age. Erişim Adresi: https://www.forbes.com/sites/joshbersin/2013/02/17/bigdata-in-human-resources-talent-analytics-comes-of-age/?sh=6bc9eb554cd0.
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  • Bodie, M. T., Cherry,M. A., Mccormick, M. L., & Tang, J. (2017). The law and policy of people analytics. University of Colorado Law Review, 88(4), 961-1042.
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  • Ferrar, J., & Green, D. (2021). Excellence in people analytics: How to use workforce data to create business value,(1. Baskı). London: Kogan Page Limited.
  • Field, A. (2000). Discovering statistics using SPSS for windows (1. Baskı). California: Sage Publications Ltd.
  • Fitz‐enz, J. (2009). The ROI of human capital: Measuring the economic value of employee performance (2.Baskı). New York: AMACOM.
  • Fitz-enz, J. (2010). The new hr analytics: Predicting the economic value of your company's human capital investments (1.Baskı). New York: AMACOM.
  • Fitz-enz, J., & Mattox, J. R. (2014). Predictive analytics for human resources (1.Baskı). New Jersey: John Wiley& Sons.
  • Gök, S., Karatuna, I., & Karaca, P. Ö. (2015). The role of perceived supervisor support and organizational identification in job satisfaction. Procedia-Social and Behavioral Sciences, 177, 38–42. https://doi.org/10.1016/j.sbspro.2015.02.328.
  • Green, D. (2017). The best practices to excel at people analytics. Journal of Organizational Effectiveness: People and Performance, 4(2), 137-144. https://doi.org/10.1108/JOEPP-03-2017-0027.
  • Green, D. (2018, March 19). Ethics & People Analytics My HR Future. Erişim Adresi: https://www.myhrfuture.com/blog/2018/3/19/ethics-people-analytics adresinden alındı.
  • Guenole, N., Ferrar, J., & Feinzig, S. (2017). The Power of people: Learn how successful organizations use workforce analytics to improve business performance (1.Baskı). Upple Saddle River: Pearson FT Press.
  • Güngör, D. (2016). Psikolojide ölçme araçlarının geliştirilmesi ve uyarlanması kılavuzu. Türk Psikoloji Yazıları, 19(38), 104-112.
  • Halper, F. (2020, December 6). TDWI Analytics Maturity Model Assessment Guide. Erişim Adresi: https://tdwi.org/research/2020/06/ppm-all-tdwi-analytics-maturity-model-guide.aspx.
  • Holsapple, C., Lee - Post, A., & Pakath, R. (2014). A Unified Foundation For Business Analytics. Decision Support Systems, 64, 130-141. https://doi.org/10.1016/j.dss.2014.05.013.
  • Huselid, M. A., & Becker, B. E. (2005). Improving HR’s Analytical Literacy: Lessons from Moneyball. In Ulrich, D. (Ed.), Losey, M. (Ed.), Meisinger, S. (Ed.), Future of Human Resource Management: 64 Thought Leaders Explore the Critical HR Issues of Today and Tomorrow (pp.278-284), New York: John Wiley and Sons.
  • Jamrog, J. J., & Overholt, M. H. (2004). Measuring hr and organizational effectiveness. Employment Relations Today, 31(2), 33-45. https://doi.org/10.1002/ert.20015.
  • Johnson, R. D., Carlson, K. D., & Kavanagh, M. J. (Ed.) (2020). Human resource information systems: basics, applications, and future directions (5.Baskı). California: Sage Publications.
  • Klein, P. (1994). An Easy Guide to Factor Analysis. New York: Routledge.
  • Lawler, E. E., Levenson, A., & Boudreau, J. W. (2004). HR Metrics and Analytics: Use and Impact. Human Resource Planning, 27(4), 27-35.
  • Levenson, A. (2005). Harnessing the power of hr analytics. Strategic HR Review, 4(3), 28-31.
  • Levenson, A. (2011). Using Targeted Analytics to Improve Talent Decisions. People & Strategy, 34(2), 34-43.
  • Levenson, A. (2014). The Promise of Big Data for HR. People & Strategy, 36(4), 22-26.
  • Levenson, A., Pillans, G. (2017, November). Strategic Workforce Analytics Corporate Research Forum Research Report. Erişim Adresi: https://www.crforum.co.uk/research-and-resources/research-report-strategic-workforce-analytics/.
  • Margherita, A. (2021). Human resources analytics: A systematization of research topics and directions for future research. Human Resources Management Review, 31(3), 1-13. https://doi.org/10.1016/j.hrmr.2020.100795.
  • Marler, J. H., & Boudreau, J. W. (2017). An evidence-based review of hr analytics. The International Journal of Human Resource Management, 28(1), 3-26. https://doi.org/10.1080/09585192.2016.1244699.
  • Marr, B. (2018). Data-driven hr: how to use analytics and metrics to drive performance (1. Baskı). New York: Kogan Page.
  • Marr, B. (2020, February 12). What Are The Pitfalls Of People Analytics And Data-Driven HR?. Forbes. Erişim Adresi: https://www.forbes.com/sites/bernardmarr/2020/02/12/what-are-the-pitfalls-of-people-analytics-and-data-driven-hr/#54c1b5ce3c38.
  • Mcbassi & Company (2018). 100 Questions You Can Answer with HR Analytics. Erişim Adresi: https://mcbassi.com/resources-old/featured-resources/.
  • McCartney, S., Murphy, C. & Mccarthy, J. (2020). 21st century HR: a competency model for the emerging role of HR Analysts. Personnel Review, 50(6), 1495-1513. https://doi.org/10.1108/PR-12-2019-0670.
  • 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.
  • Minbaeva, B. D. (2018). Building credible human capital analytics for organizational competitive advantage’’, Hum Resour Management, 57, 701–713. https://doi.org/10.1002/hrm.21848.
  • Mondore, S., Douthitt, S., & Carson, M. (2011). Maximizing the Impact and Effectiveness of HR Analytics to Drive Business Outcomes. People & Strategy, 34(2), 20-27.
  • Özdamar, K. (2004). Paket programlar ile istatistiksel veri analizi (Çok değişkenli analizler) (5. Baskı). Eskişehir: Kaan Kitabevi.
  • Pease, G., Byerly, B., & Fitz-enz, J. (2012). Human capital analytics How to harness the potential of your organization’s greatest asset (1.Baskı). New Jersey: John Wiley &Sons.
  • Peeters, T., Paauwe, J., & Van De Voorde, K. (2020). People analytics effectiveness: developing a framework. Journal of Organizational Effectiveness: People and Performance, 7(2), 203-219. https://doi.org/10.1108/JOEPP-04-2020-0071.
  • Ransbotham, S., Kiron, D., Prentice, P. K. (2015, March 16). Minding the analytics gap. MIT Sloan Management Review. Erişim Adresi: https://sloanreview.mit.edu/article/minding-the-analytics-gap/.
  • Rasmussen, T., & Ulrich, D. (2015). Learning from practice: How hr analytics avoids being a management fad. Organizational Dynamics, 44(3), 236-242. https://doi.org/10.1016/j.orgdyn.2015.05.008.
  • Rucci, A. J., Kirn, S. P. & Quinn, R. T. (1998, January-February). The employee-customer-profit chain at sears. Harvard Business Review. Erişim Adresi: https://hbr.org/1998/01/the-employee-customer-profit-chain-at-sears.
  • Seçer, İ. (2015). Psikolojik Test Geliştirme ve Uygulama Süreci Spss ve Lisrel Uygulamaları (1. Baskı). Ankara: Anı Yayıncılık.
  • Sharifi, H. & Zhang, Z. (1999). A Methodology For Achieving Agility In Manufacturing Organisations: An Introduction. International journal of production economics, 62(1), 7-22.
  • 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.
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  • Tabachnick, B. G., & Fidell, L. S. (2020). Çok değişkenli istatistiklerin kullanımı (6. Baskıdan Çeviri), (Çev. Ed. M. Baloğlu). Ankara: Nobel Akademik.
  • Tambe, P., Cappelli, P., & Yakubovich, V., (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15-42. https://doi.org/10.1177/0008125619867910.
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  • Tursunbayeva, A., Pagliari, C., Di Lauro, S., &Antonelli, G. (2021). The ethics of people analytics: risks, opportunities and recommendations. Personnel Review, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/PR-12-2019-0680.
  • Ulrich, D. (1997). Measuring human resources: An overview of practice and a prescription for results. Human Resource Management, 36(3), 303-320. https://doi.org/10.1002/(SICI)1099-050X(199723)36:3<303::AID-HRM3>3.0.CO;2-%23.
  • Ulrich, D., & Dulebohn, J. H. (2015). Are we there yet? What's next for HR?. Human Resource Management Review, 25(2), 188-204. https://doi.org/10.1016/j.hrmr.2015.01.004.
  • Van den Heuvel, S., & Bondarouk, T. (2017). The rise (and fall?) of HR analytics: A study into the future application, value, structure, and system support. Journal of Organizational Effectiveness: People and Performance, 4(2), 157-178. https://doi.org/10.1108/JOEPP-03-2017-0022.
  • Van Vulpen, E. (2017, 22 August). Big data, business intelligence, and HR analytics: How are they related? AIHR. ErişimAdresi: https://www.analyticsinhr.com/blog/big-data-business-intelligence-hr-analytics-related/.
  • Waters, S. D., Streets, V. N., McFarlane, L. A., & Johson-Murray R. (2018). The practical guide to HR analytics: Using data to inform, transform, and empower HR decisions. (1.Baskı), Danvers: Society For Human Resource Management.
  • Yaşlıoğlu, M. M. (2017). Sosyal Bilimlerde Faktör Analizi ve Geçerlilik: Keşfedici ve Doğrulayıcı Faktör Analizlerinin Kullanılması. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 46, 74-85.
Toplam 87 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular İşletme
Bölüm Makaleler
Yazarlar

Fatma Melisa Özkanlı 0000-0002-2360-761X

Sibel Gök 0000-0003-2755-6941

Erken Görünüm Tarihi 26 Aralık 2022
Yayımlanma Tarihi 26 Aralık 2022
Gönderilme Tarihi 21 Nisan 2022
Kabul Tarihi 2 Kasım 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 7 Sayı: 2

Kaynak Göster

APA Özkanlı, F. M., & Gök, S. (2022). İNSAN KAYNAKLARI ANALİTİĞİ OLGUNLUĞU ÖLÇEĞİ (İKAOÖ): BİR ÖLÇEK GELİŞTİRME ÇALIŞMASI. Journal of Research in Business, 7(2), 459-489. https://doi.org/10.54452/jrb.1107177