The HR analytics cycle: a seven-step process for building evidence-based and ethical HR analytics capabilities
Open accessAbstract
Purpose The purpose of the paper is to explore the meaning of Human Resources (HR) analytics and introduce the HR analytics cycle as a proactive and systematic process for ethically gathering, analyzing, communicating and using evidence-based HR research and analytical insights to help organizations achieve their strategic objectives. Design/methodology/approach Conceptual review of the current state and meaning of HR analytics. Using the HR analytics cycle as a framework, the authors describe a seven-step process for building evidence-based and ethical HR analytics capabilities. Findings HR analytics is a nascent discipline and there are a multitude of monikers and competing definitions. With few exceptions, these definitions lack emphasis on evidence-based practice (i.e. the use of scientific research findings in adopting HR practices), ethical practice (i.e. ethically gathering and using HR data and insights) and the role of broader HR research and experimentation. More importantly, there are no practical models or frameworks available to help guide HR leaders and practitioners in doing HR analytics work. Practical implications The HR analytics cycle encompasses a broader range of HR analytics practices and data sources including HR research and experimentation in the context of social, behavioral and organizational science. Originality/value This paper introduces the HR analytics cycle as a practical seven-step approach for making HR analytics work in organizations.
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HR analytics is its own stand-alone practice, meaning no available alternatives or substitutes can gain similar insights.
“Finally, HR analytics is its own stand-alone practice, meaning no available alternatives or substitutes can gain similar insights (Falletta and Combs, 2020).”
From Bridging the gap: why, how and when HR analytics can impact organizational performance (2022) · cites this paper as Falletta and Combs, 2020
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Bridging the gap: why, how and when HR analytics can impact organizational performance
McCartney, S., & Fu, N. (2022) · Management Decision · doi:10.1108/md-12-2020-1581 · Cited by 173 · see citing works
Help me help you: How HR analytics forecasts foster organizational creativity
Di Prima, C., Cepel, M., Kotaskova, A., & Ferraris, A. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2024.123540 · Cited by 46 · see citing works
Cayrat, C., & Boxall, P. (2022) · Journal of Organizational Effectiveness: People and Performance · doi:10.1108/joepp-08-2021-0238 · Cited by 41 · see citing works
McCartney, S., Minbaeva, D., Crean, S., & Fahy, A. (2026) · Human Resource Management Review · doi:10.1016/j.hrmr.2026.101147
- Authors
- Falletta, S. V., & Combs, W. L.
- Affiliations
- Drexel University (US)
- Corresponding author
- Falletta, Salvatore V.
- Venue
- Journal of Work-Applied Management
- Publisher
- Emerald
- Published
- 2020-07-14
- Volume
- 13
- Issue
- 1
- Pages
- 51-68
- ISSN
- 2205-149X (ISSN-L)
- 2205-2062
- OpenAlex
- W3043109987
- Cited by
- 110
- References
- 5
- Citations by year
- 2026: 20 · 2025: 25 · 2024: 21 · 2023: 24 · 2022: 14 · 2021: 5 · 2020: 1
- FWCI
- 11.89
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Journal of Work-Applied Management (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Human Resource and Talent Management
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employer Branding and e-HRM
- Keywords
- HR analytics, evidence-based practice, data ethics
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