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HR and analytics: why HR is set to fail the big data challenge
Open accessAbstract
The HR world is abuzz with talk of big data and the transformative potential of HR analytics. This article takes issue with optimistic accounts, which hail HR analytics as a ‘must have’ capability that will ensure HR's future as a strategic management function while transforming organisational performance for the better. It argues that unless the HR profession wises up to both the potential and drawbacks of this emerging field and engages operationally and strategically to develop better methods and approaches, it is unlikely that existing practices of HR analytics will deliver transformational change. Indeed, it is possible that current trends will seal the exclusion of HR from strategic, board‐level influence while doing little to benefit organisations and actively damaging the interests of employees.
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“AI-driven algorithmic monitoring thus allows to collect and record a vast array of new information and metrics, such as emotions (Chan, 2018;Pinheiro, Ramos, Donizete, Picanço, & De Oliveira, 2017), movements, sleep time, physical and health condition, social media activity, internet browser history (Angrave, Charlwood, Kirkpatrick, Lawrence, & Stuart, 2016;Leicht-Deobald et al., 2019)”
From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Angrave et al., 2016
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In the citing paper
“Descriptive algorithms are likely to reinvent the world of performance management (PM) in multiplying the metrics available to precisely quantify various facets of employees' actions, emotions, performance, behaviors, attitudes and physical state (Angrave et al., 2016;Tambe et al., 2019), but also customer-related information such as satisfaction and traffic (Evans & Kitchin, 2018;Levy & Barocas,”
From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Angrave et al., 2016
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“Moreover, predictive artificial intelligence algorithms, like the famous IBM Watson, are also used to forecast the future performance of employees based on multiple data sources such as past performance, existing and potential projects, and recent and future training opportunities (Angrave et al., 2016;Edwards & Edwards, 2019;Greenfield, 2018;Kirimi & Moturi, 2016;Sajjadiani, Sojourner, Kammeyer-M”
From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Angrave et al., 2016
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“This forecasted performance is often used as the basis to set future goals or expectations (Angrave et al., 2016;Edwards & Edwards, 2019), to estimate the training needs (Horesh, Varshney, & Yi, 2016), to determine pay raise (Greenfield, 2018) or to promote employees to managerial positions (Mallafi & Widyantoro, 2016).”
From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Angrave et al., 2016
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Hota, J. (2021) · Vision The Journal of Business Perspective · doi:10.1177/09722629211029007 · Cited by 19
“People analytics can improve employee experience, satisfaction and efficiency, enhancing the competitive strength of organizations (Angrave et al., 2016).”
BackgroundStrategic management of human resources in modern conditions: a case study
Tolstyakova, O. V., & Batyrova, N. (2020) · Entrepreneurship and Sustainability Issues · doi:10.9770/jesi.2020.8.2(22 · Cited by 12
Di Lauro, S., Tursunbayeva, A., Antonelli, G., & Moschera, L. (2025) · Personnel Review · doi:10.1108/pr-11-2023-0927 · Cited by 12
“This has led to the emergence of PA, also known as HR Analytics, Talent Management Analytics, Human Capital Analytics, Workforce Analytics or Talent Analytics, which has gained popularity (Isson and Harriott, 2016; Angrave et al. , 2016).”
BackgroundMateen, A. U., Nisar, Q. A., Jamshed, S., Rehman, S., & Ali, M. A. M. (2024) · Journal of the Knowledge Economy · doi:10.1007/s13132-024-02216-0 · Cited by 15
“The extant literature indicates that HRM can fail at the adoption of big data analytics unless HRM enhances its competencies (Angrave et al., 2016).”
Narzary, S., Makhecha, U. P., Budhwar, P., Malik, A., & Kumar, S. (2024) · Person-centered review · doi:10.1108/pr-04-2023-0296 · Cited by 11
Empowering undergraduates through machine learning
Urtasun, A. (2022) · Industry and Higher Education · doi:10.1177/09504222221124498 · Cited by 12
“Analytical skills are considered a ‘must have’ capability (Angrave et al., 2016; Huselid, 2018).”
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“According to Angrave et al. (2016), the future HRM activities might be questioned unless they are strategically and operationally involved to develop methods to combat any apocalyptic situation.”
Empowering employees: the other side of electronic performance monitoring
Sherif, K., Jewesimi, O., & El-Masri, M. (2020) · Journal of Information Communication and Ethics in Society · doi:10.1108/jices-04-2020-0038 · Cited by 19
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Identifying Critical Issues in Smart City Big Data Project Implementation
Barham, H., & Daim, T. (2018) · Proceedings of the 1st ACM/EIGSCC Symposium on Smart Cities and Communities · doi:10.1145/3236461.3241967 · Cited by 11
“[4, 9, 59, 69, 71].”
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Shet, S. V. (2025) · Person-centered review · doi:10.1108/pr-01-2024-0009 · Cited by 10
O’Brien, C., Li, Z., Adotey, P. B., & Yohuno, G. (2025) · Current Psychology · doi:10.1007/s12144-025-08064-8 · Cited by 21
“4 Themes and factorial analysis increasing reliance on AI-based talent acquisition, employee monitoring, and predictive workforce analytics, signaling a paradigm shift from intuition-based HR decision-making to algorithmic and data-driven insights (Angrave et al., 2016; Cappelli & Rogovsky, 2023).”
Liu, N., Winne, S. D., Cooman, R. D., Smet, M., & Lattanzi, N. (2025) · The International Journal of Human Resource Management · doi:10.1080/09585192.2025.2509777 · Cited by 9
“Fully automated management remains rare, as human managers play a key role in interpersonal and empathetic leadership, an area requiring further exploration (Angrave et al., 2016; De Cremer, 2020; Duggan et al., 2020).”
Navigating the digital evolution of HRM: an integrative review
Bhardwaj, S., Chopra, R., & Pandita, D. (2025) · The International Journal of Organizational Analysis · doi:10.1108/ijoa-10-2024-4895 · Cited by 10
Is it necessary? A framework for assessing the utility of A.I. in HRM practices
Sohani, S. S., Pandey, J., Varma, A., & Ray, P. (2025) · Acta Psychologica · doi:10.1016/j.actpsy.2025.104816 · Cited by 13
Kaaria, A. G. (2024) · East African Journal of Business and Economics · doi:10.37284/eajbe.7.1.1976 · Cited by 10
“Understanding the strategic value of HR initiatives enables organizations to align their HR strategies with broader business objectives, fostering sustainable growth and competitive advantage (Angrave et al., 2016).”
BackgroundMethodOrganizational Adoption Factors of HR Analytics: A Practitioner’s Perspective
Dasari, S. R., & Devi, V. R. (2024) · Management and Labour Studies · doi:10.1177/0258042x241249244 · Cited by 21
“…(KSAOs) for performing analytics is another factor that is termed both a success factor and a barrier (Respondent 1, Respondent 3 and Respondent 7) to adopting HRA (Angrave et al., 2016; Dahlbom et al., 2020; Green, 2017; Marler & Boudreau, 2017; Molefe, 2013; Peeters et al., 2020; PwC, 2015).”
How managers approach data analytics: a typology through a Resource Orchestration perspective
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HR analytics: what’s holding users back?
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“[29] also argues that talent management plays a critical role in the digital”
BackgroundA Network Data Science Approach to People Analytics
Wang, N., & Katsamakas, E. G. (2019) · Information Resources Management Journal · doi:10.4018/irmj.2019040102 · Cited by 17
Edwards, M. R. (2012) · e-HRM · doi:10.4324/9781315172729-6 · Cited by 10
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“In the early stages, HR systems were primarily manual, paper-based, and limited to basic administrative tasks such as payroll processing and record-keeping (Angrave et al., 2016).”
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Vrabcová, P., & Urbancová, H. (2021) · Agricultural Economics (Zemědělská ekonomika) · doi:10.17221/452/2020-agricecon · Cited by 12
“In connection with the complexity of systems, their acquisition costs, lack of support from top management, HR knowledge (Nagendra and Deshpande 2014), and with duplication of some functions (Angrave et al. 2016), companies often do not implement the staff information system as a whole but acquire some of its modules.”
BackgroundMethodResultInfluentialHRM 4.0 and the Shifting Landscape of Employer Branding
Thomas, S., Kureshi, S., Suggala, S., & Mendonca, V. (2020) · doi:10.1108/978-1-83867-223-220201003 · Cited by 9
Integrating Social Scientific Perspectives on the Quantified Employee Self
Calvard, T. (2019) · The social science · doi:10.3390/socsci8090262 · Cited by 9
“Human resource (HR) functions may lack the various capabilities needed to manage all data analytic interactions and interests between employers and employees (Angrave et al. 2016).”
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Coron, C. (2021) · Employee Relations: The International Journal · doi:10.1108/er-07-2020-0316 · Cited by 8
Espegren, Y. (2024) · Personnel Review · doi:10.1108/pr-03-2024-0219 · Cited by 13
How to do HRM with numbers? A performative lens on HR metrics, HR analytics and HR algorithms
Coron, C., Scheibmayr, I., & Lescoat, P. (2024) · New Technology Work and Employment · doi:10.1111/ntwe.12306 · Cited by 13
The evolution of HRM practices: big data, data analytics, and new forms of work
Yang, Y., Shamim, S., Herath, D. B., Secchi, D., & Homberg, F. (2023) · Reviews of Management Sciences · doi:10.1007/s11846-023-00648-7 · Cited by 8
“Many firms have introduced analytics based on big data to increase efficiency and quality of their decisions (Angrave et al. 2016; Shamim et al. 2021), enable change and enhance agility.”
BackgroundDeterminants of voluntary turnover: A data-driven analysis for blue and white collar workers
Rombaut, E., & Guerry, M. (2021) · Work · doi:10.3233/wor-213538 · Cited by 8
“This can largely be attributed to the gap between academia and industry where HR professionals lack know-how of current developments on data analytics [14].”
Lacroux, A., & Martin‐Lacroux, C. (2021) · Management & Avenir · doi:10.3917/mav.122.0121 · Cited by 32
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Human Resource Analytics: Implications for Strategy Realization and Organizational Performance
Lydgate, X. (2018) · doi:10.15760/honors.513 · Cited by 13
“Source Type Alharthey & Rasil (2011) Scholarly journal Angrave et al. (2016) Scholarly journal Barrette (2015) Practitioner journal Barton & Court (2012) Practitioner journal Bassi (2011) Practitioner journal Bates (2001) Practitioner journal Bates (2003) Popular magazine Bauer & Caughlin (2017) Blog Beatty (2005) Whi…”
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“This skill comes in handy when things aren’t going as planned and you need to be able to quickly adapt and act on talented people in the future to stay ahead of the competition (Fink & Sturman, 2017; Angrave et al., 2016).”
Analisis Peramalan Kebutuhan SDM dalam Mendukung Perencanaan SDM Strategis: Literature Review
Aulia, N., Kurotaayun, H., Rizky, E., & Aulia, R. (2026) · Journal of Business Economics and Management | E-ISSN : 3063-8968 · doi:10.62379/jbem.v3i1.1898 · Cited by 7
“Angrave et al. (2016) menunjukkan bahwa kemampuan organisasi dalam memanfaatkan data untuk kebutuhan SDM tidak hanya ditentukan oleh keberadaan teknologi, tetapi juga oleh kemampuan analitis dan kesiapan organisasi dalam mengelola informasi.”
Chen, Z. (2026) · Humanities and Social Sciences Communications · doi:10.1057/s41599-026-06989-4 · Cited by 12
Algorithmic Management in Limbo: Task‐Driven Interweaving of Hierarchy and Market Management
Robinson, A. P., Jarrahi, M. H., Keegan, A. E., & Meijerink, J. (2025) · Human Resource Management · doi:10.1002/hrm.70019 · Cited by 9
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Gestión del talento humano en contextos de trabajo remoto y flexible
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Huynh, P., Le, P., & Nguyen, T. T. (2025) · Benchmarking : An International Journal · doi:10.1108/bij-09-2024-0735 · Cited by 7
HR Management Transformation in Indonesia MSMEs: The Role of AI in SOP Making and Recruitment
Wulandari, A., & Diko, M. (2024) · Journal of Ecohumanism · doi:10.62754/joe.v3i7.4641 · Cited by 7
“Additionally, the use of AI for HRM decision-making raises ethical questions about transparency and accountability (Angrave et al., 2016; Marler & Parry, 2016).”
MethodEmployees’ Experiences of Accepting and Adopting HR Analytics: A Phenomenology Study
Saxena, M., Bagga, T., Gupta, S., & Mittal, A. (2022) · The Open Psychology Journal · doi:10.2174/18743501-v15-e2208040 · Cited by 11
Nagpal, T., & Mishra, M. (2021) · Materials Today: Proceedings · doi:10.1016/j.matpr.2020.12.460 · Cited by 6
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Bauwens, R., & Batistič, S. (2025) · BRQ Business Research Quarterly · doi:10.1177/23409444251341326 · Cited by 10
“Most of these documents focus on topics such as HR analytics (Angrave et al., 2016; Kellogg et al., 2020; Marler & Boudreau, 2017), human-AI interaction (Arslan et al., 2022; Gombolay et al., 2015), and the future of work.”
Diefenhardt, F. (2025) · The International Journal of Human Resource Management · doi:10.1080/09585192.2025.2470302 · Cited by 11
“Discussions on the use of data analytics in HRM often overlook the fact that quantitative data capture and analysis for personnel management has existed for over 100 years (Angrave et al., 2016; Marler & Boudreau, 2017; for an exception, see Roth-Kirkegaard, 2022).”
AlGhunaimi, H., & AlGhenaimi, S. (2024) · Journal of Ecohumanism · doi:10.62754/joe.v3i6.4057 · Cited by 6
“For instance, according to Angrave et al. (2016), understanding and measuring relevant data can be quite complex for HR to implement.”
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Thakur, S. J., Bhatnagar, J., Farndale, E., & Aeron, P. (2024) · Journal of Organizational Effectiveness People and Performance · doi:10.1108/joepp-10-2022-0303 · Cited by 12
Masputra, H., Nilasari, B. M., & Nisfiannoor, M. (2023) · Return Study of Management Economic and Bussines · doi:10.57096/return.v3i04.91 · Cited by 5
“Despite the recent prevalence of big data analysis, small data analysis still plays a dominant and indispensable role in HRM research (Angrave et al., 2016).”
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Big Data: neuroscience at the service of management
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“Another example of BD application, although not exempt from criticisms (Angrave et al., 2016) and ethical issues (Illingworth, 2015), is in the personnel selection process (Hausknecht & Li, 2015; Landers & Schmidt, 2016), to the management of training and knowledge management, and to the reduction…”
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Fabbri, T., Scapolan, A. C., Bertolotti, F., & Canali, C. (2019) · Emerald Group Publishing Limited eBooks · doi:10.1108/s1877-636120190000023012 · Cited by 6
Knowledge Management: (Potential) Future Research Directions
Hislop, D., Murray, P., Shrestha, A., Syed, J., & Mouzughi, Y. (2018) · Springer eBooks · doi:10.1007/978-3-319-71434-9_28 · Cited by 6
A Technology-driven Overview on Blockchain-based Academic Certificate Handling
Rodrigues, B., Franco, M., Scheid, E. J., Kanhere, S., & Stiller, B. (2020) · doi:10.4018/978-1-5225-9478-9.ch010 · Cited by 6
Quantitative Approach in Enhancing Decision Making Through Big Data as An Advanced Technology
Yousuf, H. (2020) · Advances in Science Technology and Engineering Systems Journal · doi:10.25046/aj050515 · Cited by 6
“Big Data use also requires skills involved in data cleaning and visualization, which suggests that organizations need to nurture key talents The acknowledgment by [26] that HR experts and expertise play in a Big Data setting, who are able to speak the market language and therefore make it easy for leaders to devise st…”
BackgroundRisk-Based Manpower Planning: A Tractable Multi-Period ModelPreprint
Jaillet, P., Loke, G. G., & Sim, M. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3168168 · Cited by 13
From data to knowledge in four decades: a systematic literature review of human resource analytics
Ioakeimidou, D., Symeonidis, S., Chatzoudes, D., & Chatzoglou, P. (2025) · Journal of Management Analytics · doi:10.1080/23270012.2025.2465236 · Cited by 7
MCDM Approach Combining DEA and AHP Methods in Sustainable Tourism: Case of Serbia
Langović, Z., Pažun, B., Grujčić, Ž., Nikolić, M., Milićević, A. L., & Ugrinov, D. (2025) · Journal of Scientific & Industrial Research · doi:10.56042/jsir.v84i02.8163 · Cited by 5
“14,15 Their application already exists and the given methods are also used in other business processes of the tourism system, e.g. in the process of offer definition, then in decision making related to the management of the so-called green hotels.”
Human resource analytics adoption: a framework-based analysis, fuzzy Delphi method and fuzzy SWARA
malekinezhad, M. K., Rahimnia, F., Eslami, G., & Farahi, M. M. (2025) · Journal of Advances in Management Research · doi:10.1108/jamr-05-2024-0181 · Cited by 14
On the road to HR legitimacy in SMEs: the signalling power of HR metrics
Cayrat, C., Guerrero, S., & Cossette, M. (2024) · The International Journal of Human Resource Management · doi:10.1080/09585192.2024.2420212 · Cited by 8
“…by demonstrating how the HR function contributes to efficiency goals and the competitive advantage of the firm, they may also bring little benefits to managers if not approached ‘from a strategic HR perspective’ that focuses on how human capital drives business value (Angrave et al., 2016, p. 5).”
InfluentialHR analytics between ambition and reality
Gerber, M., Krause, A., Probst, J., & Heimann, M. (2024) · Gruppe Interaktion Organisation Zeitschrift für Angewandte Organisationspsychologie (GIO) · doi:10.1007/s11612-024-00743-7 · Cited by 10
“The lack of these skills within HR, along with a lack of business understanding and a general reluctance to take action on numbers, is evident in other research as well (Angrave et al. 2016; Dahlbom et al. 2019).”
Predictive Video Analytics in Online Courses: A Systematic Literature Review
Yürüm, O. R., Taşkaya-Temizel, T., & Yıldırım, S. (2023) · Technology, Knowledge and Learning · doi:10.1007/s10758-023-09697-z · Cited by 5
“…a few studies collected data from courses over more than one year’s duration, indicating the need for longitudinal studies that would provide researchers with a greater volume of data to build efficient models on predictive video analytics in online courses (Angrave et al., 2016; Ratten, 2020).”
HR ANALYTICS: A Conceptual Study on Decision Making
Sharma, P., Jha, S., & Dash, S. (2022) · YMER Digital · doi:10.37896/ymer21.07/49 · Cited by 5
Descriptive statistics are powerful tools for organizational research practitioners
Acosta, J., & Brooks, S. (2021) · Industrial and Organizational Psychology · doi:10.1017/iop.2021.116 · Cited by 5
“With experience, practitioners learn how to properly clean and use the HR system fields, but often analysts don’t have a high degree of familiarity with the nuances of the data, especially given the trend of HR departments outsourcing their analytics to centralized data science teams or vendors (Angrave et al., 2016).”
BackgroundWork Datafication and Digital Work Behavior Analysis as a Source of HRM Insights
Fabbri, T., Scapolan, A., Bertolotti, F., Mandreoli, F., & Martoglia, R. (2021) · Lecture Notes in Information Systems and Organisation · doi:10.1007/978-3-030-83321-3_4 · Cited by 5
Renkema, M. (2021) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-80071-298-020211011 · Cited by 14
Abuzaid, A. (2024) · International Journal of Data and Network Science · doi:10.5267/j.ijdns.2024.4.001 · Cited by 5
“It is necessary to have a good knowledge of IT to leverage analytic software tools and ultimately interpret organizational measures (Angrave et al., 2016).”
BackgroundPeople Analytics: Augmenting Horizon from Predictive Analytics to Prescriptive Analytics
Singh, A., Singh, H., & Singh, A. (2022) · Decision Intelligence Analytics and the Implementation of Strategic Business Management · doi:10.1007/978-3-030-82763-2_13 · Cited by 5
Measures in organizational behavior: why don’t we use big data and analytics?
Balaniuk, R. D. M., & Borges‐Andrade, J. E. (2020) · Estudos de Psicologia (Campinas) · doi:10.1590/1982-0275202138e180157 · Cited by 2
Social and Ethical Problems of Digital Technologies Application in Human Resource Management
Konovalova, V., & Mitrofanova, A. (2020) · Lecture notes in networks and systems · doi:10.1007/978-3-030-47458-4_85 · Cited by 5
HR Value Proposition Using Predictive Analytics: An Overview
Likhitkar, P., & Verma, P. (2019) · Advances in Intelligent Systems and Computing · doi:10.1007/978-981-13-9330-3_15 · Cited by 5
Data-driven decision making in human resources to optimize talent acquisition and retention
Odionu, C. S., Bristol-Alagbariya, B., & Okon, R. (2024) · International Journal of Scholarly Research and Reviews · doi:10.56781/ijsrr.2024.5.2.0051 · Cited by 4
“The collection and analysis of employee data raise significant concerns about the confidentiality and ethical use of personal information (Angrave et al., 2016).”
Chang, Y.-L. (2026) · Journal of Organizational Effectiveness People and Performance · doi:10.1108/joepp-09-2025-0781 · Cited by 4
Karami, M. (2025) · Strategic HR Review · doi:10.1108/shr-11-2025-0119 · Cited by 6
Linking HRM Digitalization to Employee Thriving at Work: A Signaling Theory Perspective
Zhou, Y., Liu, Z., Zhu, H., & Zhao, L. (2025) · Asia Pacific Journal of Human Resources · doi:10.1111/1744-7941.70052 · Cited by 4
Human Resource Analytics: A Hybrid Review
Goswami, T. G., & Mansi (2025) · South Asian Journal of Human Resources Management · doi:10.1177/23220937251322236 · Cited by 5
Peran Strategic HR Analytics dalam Meningkatkan Efektivitas Pengelolaan Sumber Daya Manusia
Yanuarty, R. (2025) · Jurnal Ekonomi dan Bisnis · doi:10.56145/ekobis.v5i1.300 · Cited by 4
“Menurut Angrave et al. (2016), organisasi yang memiliki budaya seperti ini lebih mampu mengadopsi SHRA secara efektif dan mencapai manfaat jangka panjang.”
Sattar, S., Bukhari, M., Saleem, S., Ijaz, S., Ejaz, S., & Abbas, J. (2024) · Journal of excellence in management sciences. · doi:10.69565/jems.v3i3.343 · Cited by 6
“A positive and prompt attitude towards learning and adopting HRA is crucial for a smooth transition (Angrave et al., 2016; Shrivastava, 2024).”
BackgroundKusmin, K.-L., Normak, P., & Ley, T. (2024) · Frontiers Artif. Intell. · doi:10.3389/frai.2024.1424924 · Cited by 4
Data-driven internal mobility: Similarity regularization gets the job done
Vos, S. D., Smedt, J. D., Verbruggen, M., & Verbeke, W. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.111824 · Cited by 10
Neuro Management and Leadership
Kouravand, N. (2024) · International journal of new findings in health and educational sciences (IJHES). · doi:10.63053/ijhes.68 · Cited by 8
“Brain Based Learning (BBL) is derived from the theory of cognitive neuroscience, the theory comes from studies of how the brain works function by neuroscience (Angrave et al., 2016).”
BackgroundExploring the Adoption of Human Resource Analytics among Human Resource Professionals
Kalvakolanu, S., Madhavaiah, C., & Kamruddin, S. (2023) · International Journal of Organizational Leadership · doi:10.33844/ijol.2023.60387 · Cited by 8
“Angrave et al. (2016) argued that HR practitioners must integrate analytics to play the most strategic HR role.”
BackgroundEthnicity, Race, and National Identity in Management and Organization Studies
Laer, K. V., & Zanoni, P. (2020) · doi:10.1002/9781119430452.ch29 · Cited by 4
Big Data Informatization Applied to Optimization of Human Resource Performance Management
Li, K., Chen, J.-C., & Wang, Y.-X. (2019) · International Conference Information Management and Management Sciences · doi:10.1145/3357292.3357302 · Cited by 4
Knowledge Hubs in Competence Analytics: With a Case Study in Recruitment and Selection
Caron, E., & Batistič, S. (2019) · International Conference on Software and Data Technologies · doi:10.5220/0008117805850594 · Cited by 4
Staff Employment Platform (StEP) Using Job Profiling Analytics
Kamaru-Zaman, E. A., Kamal, A., Mohamed, A., Ahmad, A., & Zamri, R. A. Z. R. M. (2018) · International Conference on Soft Computing in Data Science · doi:10.1007/978-981-13-3441-2_30 · Cited by 4
Contested Transparency: Digital Monitoring Technologies and Worker Voice
Belloc, F., Burdín, G., Dughera, S., & Landini, F. (2023) · Social Science Research Network · doi:10.2139/ssrn.4528975 · Cited by 4
Quantitative Analysis of Salary Data in the Big Data Era
Li, B.-Q. (2021) · Journal of Physics, Conference Series · doi:10.1088/1742-6596/1881/3/032022 · Cited by 4
HR Analytics, Fad or Fashion for Organizational Sustainability
Qureshi, T. (2020) · doi:10.1007/978-3-030-32922-8_9 · Cited by 4
Construction of a Person–Job Temporal Knowledge Graph Using Large Language Models
Zhang, Z., Wang, J., Li, B., Lin, X., & Liu, M.-Y. (2025) · Big Data and Cognitive Computing · doi:10.3390/bdcc9110287 · Cited by 3
“As a core asset in human resource management, person–job data encompasses multidimensional information, including job descriptions, position requirements, candidate skills, performance records, and bidirectional interaction behaviors [1].”
From Human Intuition to Data Intelligence: Rethinking Talent Management through HR Analytics
Koirala, A., Bhaumik, A., Ojha, S. K., & Mishra, A. (2025) · Journal of Multidisciplinary Research for SMET (JMR-SMET) · doi:10.64297/jmrsmet.v1i2.31 · Cited by 2
“…limitations, it causes disparities in impact among organizations such as skill deficits and problem framing, pivotal reviews highlight the increasing integration of statistical modeling and AI/ML in hiring, performance, and retention decisions (Marler & Boudreau, 2017; Angrave et al., 2016).”
Deep Learning Approach for Prediction Employee Attrition for HR Analytics
Ramya, T., & Sanjay, B. (2025) · 2025 6th International Conference for Emerging Technology (INCET) · doi:10.1109/incet64471.2025.11140331 · Cited by 3
“Angrave et al. (2016) emphasized the challenges HR departments face in using big data effectively, calling for strategic alignment between HR practices and analytics.”
InfluentialHukkeri, P., & Pol, S. (2025) · International Journal of Innovative Science and Research Technology · doi:10.38124/ijisrt/25may671 · Cited by 5
Saxena, M., Bagga, T., Gupta, S., & Rameshwar, R. (2025) · SAGE Open · doi:10.1177/21582440251328078 · Cited by 6
“HR executives started to make use of data to form strategies and create a competitive edge in their work (Angrave et al., 2016).”
InfluentialBudak, M. C., & Soyer, A. (2025) · International Journal of Intelligent Computing and Cybernetics · doi:10.1108/ijicc-10-2024-0535 · Cited by 3
Role of workforce analytics in fulfillment experience of employees through work volition
Asadullah, M. A., Malik, A., Haq, M. Z. U., & Khalifa, A. H. (2024) · European journal of training and development · doi:10.1108/ejtd-05-2024-0064 · Cited by 3
Digital Human Resource Transformation - A Bibliometric Analysis
Kavya, M., Sowdamini, T., & Pande, A. (2023) · Acta Universitatis Bohemiae Meridionalis · doi:10.32725/acta.2023.011 · Cited by 6
Norena-Chávez, D., & Thalassinos, E. I. (2023) · Journal of Infrastructure Policy and Development · doi:10.24294/jipd.v7i3.2583 · Cited by 14
“With a significant focus on psychological factors that impact project success (PS) (Angrave et al., 2016), there is a significantly limited focus on technological factors that can affect project success.”
Background
Metadata
- Authors
- Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M.
- Affiliations
- University of Sheffield (GB)
- Loughborough University (GB)
- University of Leeds (GB)
- Independent Strategic HR Analytics Consultant
- Corresponding author
- Charlwood, Andy
- Venue
- Human Resource Management Journal
- Publisher
- Wiley
- Published
- 2016-01
- Volume
- 26
- Issue
- 1
- Pages
- 1-11
- ISSN
- 0954-5395 (ISSN-L)
- 1748-8583
- OpenAlex
- W2222612072
- Cited by
- 633
- References
- 0
- Citations by year
- 2026: 71 · 2025: 74 · 2024: 77 · 2023: 87 · 2022: 77 · 2021: 79 · 2020: 61 · 2019: 48 · 2018: 24 · 2017: 19 · 2016: 14
- FWCI
- 68.00
- Type
- journal article
- Language
- en
- Open access
- green
- dspace.lboro.ac.uk
- Licence
- Locations
- Human Resource Management Journal (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- Loughborough University Institutional Repository (Loughborough University) (submittedVersion, cc-by-nc-nd)
- Loughborough University Research Repository (Loughborough University) (submittedVersion, cc-by-nc-nd)
- 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 › Management Information Systems › Big Data and Business Intelligence
- Keywords
- HR analytics, big data, human resource management, strategic management, organizational performance, transformative change, employee interests
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