HR Analytics as an Organizational Learning Capability: Dynamic Capabilities, Absorptive Capacity, And Double-Loop Learning
DOI:
https://doi.org/10.65150/EP-jmrr/V2E7/2026-08Keywords:
HR analytics, dynamic capabilities, absorptive capacity, organisational learning, double-loop learning, evidence-based HRMAbstract
Objective: This article reconceptualises HR analytics from a decision-support tool to an organisational learning capability by integrating three theoretical traditions that have not been jointly mobilised in the HR analytics literature: dynamic capabilities theory, absorptive capacity, and organisational learning theory.
Design/methodology: A theoretical integrative review (Torraco, 2005) synthesizes three bodies of literature through a structured analytical protocol. Published empirical findings from prior studies are reinterpreted under the integrated theoretical lens as secondary empirical anchoring.
Findings: HR analytics maturity activates dynamic HR capabilities (sensing, seizing, reconfiguring) that produce organisational learning only when absorptive capacity mediates the conversion of analytical outputs into actionable knowledge. Learning depth, from single-loop correction to double-loop reconfiguration, determines the strategic quality of human capital decisions. Eight propositions and four contextual moderators are formalised.
Implications: This article offers a novel application, among the first in the HR analytics domain, of the dynamic capabilities-absorptive capacity-organizational learning nexus, shifting the field’s guiding question from “What can HR analytics do?” to “How does an organisation learn through HR analytics?”
References
1) 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
2) Arend, R.J., & Bromiley, P. (2009). Assessing the dynamic capabilities view: Spare change, everyone? Strategic Organization, 7(1), 75–90. https://doi.org/10.1177/1476127008100132
3) Argyris, C. (1990). Overcoming organizational defenses: Facilitating organizational learning. Allyn and Bacon.
4) Argyris, C., & Schön, D.A. (1978). Organizational learning: A theory of action perspective. Addison-Wesley.
5) Barreto, I. (2010). Dynamic capabilities: A review of past research and an agenda for the future. Journal of Management, 36(1), 256–280. https://doi.org/10.1177/0149206309350776
6) Belizón, M.J., Majarín, D., & Aguado, D. (2024). Human resources analytics in practice: A knowledge discovery process. European Management Review, 21(3), 659–677. https://doi.org/10.1111/emre.12605
7) Bersin, J. (2021). HR technology market 2021. The Josh Bersin Company.
8) Boudreau, J.W., & Ramstad, P.M. (2003). Strategic HRM measurement in the 21st century. In M. Goldsmith et al. (Eds.), Human resource management in the 21st century. Wiley.
9) Boudreau, J.W., & Ramstad, P.M. (2007). Beyond HR: The new science of human capital. Harvard Business School Press.
10) Charlwood, A., & Guenole, N. (2022). Can HR adapt to the paradoxes of artificial intelligence? Human Resource Management Journal, 32(4), 729–742. https://doi.org/10.1111/1748-8583.12433
11) Cohen, W.M., & Levinthal, D.A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152. https://doi.org/10.2307/2393553
12) Crossan, M.M., Lane, H.W., & White, R.E. (1999). An organizational learning framework: From intuition to institution. Academy of Management Review, 24(3), 522–537. https://doi.org/10.5465/amr.1999.2202135
13) Dahlbom, P., Siikanen, N., Sajasalo, P., & Järvenpää, M. (2019). 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
14) Davenport, T.H., Harris, J., & Shapiro, J. (2010). Competing on talent analytics. Harvard Business Review, 88(10), 52–58.
15) Fainshmidt, S., Pezeshkan, A., Lance Frazier, M., Nair, A., & Markowski, E. (2016). Dynamic capabilities and organizational performance: A meta-analytic evaluation and extension. Journal of Management Studies, 53(8), 1348–1380. https://doi.org/10.1111/joms.12213
16) Falletta, S.V., & Combs, W.L. (2020). The HR analytics cycle. Journal of Work-Applied Management, 13(1), 51–68. https://doi.org/10.1108/JWAM-03-2020-0020
17) 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
18) Fitz-Enz, J. (1980). Quantifying the human resources function. Personnel, 57(3), 41–52.
19) Flatten, T.C., Engelen, A., Zahra, S.A., & Brettel, M. (2011). A measure of absorptive capacity: Scale development and validation. European Management Journal, 29(2), 98–116. https://doi.org/10.1016/j.emj.2010.11.002
20) Gioia, D.A., Corley, K.G., & Hamilton, A.L. (2013). Seeking qualitative rigor in inductive research. Organizational Research Methods, 16(1), 15–31. https://doi.org/10.1177/1094428112452151
21) Hair, J.F., Risher, J.J., Sarstedt, M., & Ringle, C.M. (2019). When to use and how to report PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
22) Helfat, C.E., & Peteraf, M.A. (2003). The dynamic resource-based view: Capability lifecycles. Strategic Management Journal, 24(10), 997–1010. https://doi.org/10.1002/smj.332
23) Huber, G.P. (1991). Organizational learning: The contributing processes and the literatures. Organization Science, 2(1), 88–115. https://doi.org/10.1287/orsc.2.1.88
24) Kamoche, K. (2011). Contemporary developments in the management of human resources in Africa. Journal of World Business, 46(1), 1–4. https://doi.org/10.1016/j.jwb.2010.05.011
25) Lane, P.J., Koka, B.R., & Pathak, S. (2006). The reification of absorptive capacity: A critical review and rejuvenation of the construct. Academy of Management Review, 31(4), 833–863. https://doi.org/10.5465/amr.2006.22527456
26) Levenson, A. (2018). Using workforce analytics to improve strategy execution. Human Resource Management, 57(3), 685–700. https://doi.org/10.1002/hrm.21850
27) March, J.G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. https://doi.org/10.1287/orsc.2.1.71
28) Margherita, A. (2022). Human resources analytics: A systematization of research topics and directions for future research. Human Resource Management Review, 32(2), 100795. https://doi.org/10.1016/j.hrmr.2020.100795
29) Marler, J.H., & Boudreau, J.W. (2017). An evidence-based review of HR analytics. International Journal of Human Resource Management, 28(1), 3–26. https://doi.org/10.1080/09585192.2016.1244699
30) McCartney, S., & Fu, N. (2022). Bridging the gap: Why, how, and when HR analytics can impact organizational performance. Management Decision, 60(13), 25–47. https://doi.org/10.1108/MD-12-2020-1581
31) Minbaeva, D. (2018). Building credible human capital analytics. Human Resource Management, 57(3), 701–713. https://doi.org/10.1002/hrm.21848
32) Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company. Oxford University Press.
33) Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation-augmentation paradox. Academy of Management Review, 46(1), 192–210. https://doi.org/10.5465/amr.2018.0072
34) Rousseau, D.M. (2006). Is there such a thing as “evidence-based management”? Academy of Management Review, 31(2), 256–269. https://doi.org/10.5465/amr.2006.20208679
35) Schilke, O., Hu, S., & Helfat, C.E. (2018). Quo vadis, dynamic capabilities? A content-analytic review of the current state of knowledge and recommendations for future research. Academy of Management Annals, 12(1), 390–439. https://doi.org/10.5465/annals.2016.0014
36) Teece, D.J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350. https://doi.org/10.1002/smj.640
37) Teece, D.J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. https://doi.org/10.1002/(SICI)1097-0266(199708)18:7<509::AID-SMJ882>3.0.CO;2-Z
38) Torraco, R.J. (2005). Writing integrative literature reviews: Guidelines and examples. Human Resource Development Review, 4(3), 356–367. https://doi.org/10.1177/1534484305278283
39) 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. https://doi.org/10.1016/j.ijinfomgt.2018.08.002
40) Volberda, H.W., Foss, N.J., & Lyles, M.A. (2010). Absorbing the concept of absorptive capacity: How to realize its potential in the organization science field. Organization Science, 21(4), 931–951. https://doi.org/10.1287/orsc.1090.0503
41) Whetten, D.A. (1989). What constitutes a theoretical contribution? Academy of Management Review, 14(4), 490–495. https://doi.org/10.5465/amr.1989.4308371
42) Wilden, R., Gudergan, S.P., Nielsen, B.B., & Lings, I. (2013). Dynamic capabilities and performance: Strategy, structure and environment. Long Range Planning, 46(1–2), 72–96. https://doi.org/10.1016/j.lrp.2012.12.001
43) Winter, S.G. (2003). Understanding dynamic capabilities. Strategic Management Journal, 24(10), 991–995. https://doi.org/10.1002/smj.318
44) Yin, R.K. (2018). Case study research and applications (6th ed.). Sage.
45) Zahra, S.A., & George, G. (2002). Absorptive capacity: A review, reconceptualization, and extension. Academy of Management Review, 27(2), 185–203. https://doi.org/10.5465/amr.2002.6587995
46) Zollo, M., & Winter, S.G. (2002). Deliberate learning and the evolution of dynamic capabilities. Organization Science, 13(3), 339–351. https://doi.org/10.1287/orsc.13.3.339.2780
Downloads
Published
Issue
Section
License
Copyright (c) 2026 BELINGA BESSALA Jacob Patrick (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.









