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Quantifying human resource management: a literature review

Open access
Coron, Clotilde·2022·Personnel Review
DOI 10.1108/pr-05-2020-0322
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Abstract

Purpose: With a focus on the evolution of human resource management (HRM) quantification over 2000–2020, this study addresses the following questions: (1) What are the data sources used to quantify HRM? (2) What are the methods used to quantify HRM? (3) What are the objectives of HRM quantification? (4) What are the representations of quantification in HRM? Design/methodology/approach: This study is based on an integrative synthesis of 94 published peer-reviewed empirical and non-empirical articles on the use of quantification in HRM. It uses the theoretical framework of the sociology of quantification. Findings: The analysis shows that there have been several changes in HRM quantification over 2000–2020 in terms of data sources, methods and objectives. Meanwhile, representations of quantification have evolved relatively little; it is still considered as a tool, and this ignores the possible conflicts and subjectivity associated with the use of quantification. Originality/value: This literature review addresses the use of quantification in HRM in general and is thus larger in scope than previous reviews. Notably, it brings forth new insights on possible differences between the main uses of quantification in HRM, as well as on artificial intelligence and algorithms in HRM.

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  • HR analytics contributes to organizational evidence creation through acquiring and translating high-quality workforce data into information, resulting in critical organizational insights.

    “At the same time, HR analytics contributes to organizational evidence creation through acquiring and translating high-quality workforce data into information, resulting in critical organizational insights (Marler and Boudreau, 2017;Minbaeva, 2018;Coron, 2021).”

    From Bridging the gap: why, how and when HR analytics can impact organizational performance (2022) · cites this paper as Coron, 2021

    The Data sources used in HRM quantification section (page unavailable) describes workforce-related data used in the literature, and the Categorization section (page unavailable) identifies improving decision-making as a use of quantification results. The copy does not establish the claimed sequence of acquiring high-quality workforce data, translating it into information, and thereby creating critical organizational insights. (LLM, conf=0.78)

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Cites

Flagged first, then by citations

Research works printed but not linked: 35

  1. 2011, Raging debates in HR analytics, People and Strategy, 34, 14
  2. 2001, The HR Scorecard: Linking People, Strategy, and Performance
  3. 2016, The evolution of ‘transparency’ in management, People and Strategy, 39, 9
  4. 2016, The role of scientific findings in evidence-based HR, People and Strategy, 39, 16
  5. 2017, There's No such thing as big data in HR, Harvard Business Review
  6. 2011, Connecting people investments and business outcomes at Lowe's, People and Strategy, 34, 28
  7. 2016, Technology drives the well-being of people, People and Strategy, 39, 12
  8. 2016, Applying AI, People and Strategy, 39, 11
  9. 2019, Is HR the most analytics-driven function?, Harvard Business Review, 2
  10. 2010, Competing on talent analytics, Harvard Business Review, 1
  11. 1993, La Politique des grands nombres. Histoire de la raison statistique
  12. 2008, I. Pour une sociologie historique de la quantification. L'Argument statistique I
  13. 2008, II. Gouverner par les nombres. L'argument statistique II
  14. 2019, Prouver et gouverner
  15. 2011, Measuring and managing financial performance of the human capital investment, People and Strategy, 34, 44
  16. 2016, Sears holdings datafies and democratizes ratingless performance management, People and Strategy, 39, 13
  17. 2014, In search of HR intelligence: evidence-based HR analytics practices in high performing companies, People and Strategy, 36, 28
  18. 2010, New trends in human capital research and analytics, People and Strategy, 33, 14
  19. 2017, Getting results with talent analytics, People and Strategy, 40, 36
  20. 2002, How to Measure Human Resources Management
  21. 2014, Struggling at the (computer) games of life, Harvard Business Review, 2
  22. 2019, Point: the rise of people analytics, People and Strategy, 42, 2
  23. 2019, Counterpoint: the case for agile workforce planning, People and Strategy, 42, 10
  24. 2011, Using targeted analytics to improve talent decisions, People and Strategy, 34, 34
  25. 2014, The promise of big data for HR, People and Strategy, 36, 22
  26. 2018, Counterpoint: people analytics is finally here and we have a lot to celebrate, People and Strategy, 41, 54
  27. 2017, Patagonia's journey into a new regenerative performance approach, People and Strategy, 40, 30
  28. 2012, Big data: the management revolution, Harvard Business Review, 3
  29. 2011, Maximizing the impact and effectiveness of HR analytics to drive business outcomes, People and Strategy, 34, 20
  30. 2016, Science and HR, People and Strategy, 39, 62
  31. 2019, Counterpoint: three ways to increase the impact of people analytics, People and Strategy, 42, 5
  32. 2019, Evolving the strategic workforce planning strategy at PepsiCo, People and Strategy, 42, 36
  33. 2016, The transparency paradox at work, People and Strategy, 39, 8
  34. 2004, Current approaches to HR strategies: inside-out versus outside-in, Human Resource Planning, 36
  35. 2017, How artificial intelligence will change HR, People and Strategy, 40, 42

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Authors
Coron, C.
Affiliations
IAE Paris - Sorbonne Business School (FR)
Corresponding author
Coron, Clotilde
ORCID
Coron, Clotilde
Venue
Personnel Review
Publisher
Emerald
Published
2021-05-18
Volume
51
Issue
4
Pages
1386-1409
ISSN
0048-3486 (ISSN-L)
DOI
10.1108/pr-05-2020-0322
OpenAlex
W3160879343
Semantic Scholar
160e565c962b33358d951cdfaf807e3d60e8379d
Cited by
40
References
90
Citations by year
2026: 5 · 2025: 10 · 2024: 7 · 2023: 12 · 2022: 5 · 2021: 1
FWCI
1.06
Type
journal article
Language
en
Open access
Licence
Locations
  • Personnel Review (publishedVersion)
  • RePEc: Research Papers in Economics (acceptedVersion)
  • HAL (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Oskar-Bordeaux (Universite de Bordeaux) (submittedVersion)
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
human resource management, quantification, sociology of quantification, data sources, measurement methods, artificial intelligence in human resource management

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