Overcoming barriers to the adoption of human resource analytics in emerging economies: Evidence from Pakistan’s banking sector
Organizations are realizing that their employees are the most valuable assets and effectively managing teams is essential for building a successful and competitive business. Existing studies mostly build on frameworks that have been developed in a digitally mature environment and offer little insight into the institutional, organizational, and technological barriers experienced by developing economies. Despite the global recognition of HR analytics as a cornerstone for data-driven decision-making, its integration within emerging economies, such as Pakistan, remains difficult. This study investigates the critical barriers that slow down the adoption of HR analytics within Pakistan’s banking sector, an industry characterized by rapid digital change and significant regulatory evolution. A qualitative study was designed to explore this issue using a constructivist grounded theory. Data were collected from human resources professionals working in 15 banks and examined through in-depth interviews. The analysis identified five interconnected barriers: obsolete technological infrastructure, HR capability gaps, resistance to change, strategic governance weakness, and compliance and ethics concerns. Based on these findings identified five interconnected barriers proposes Five-Pillar Roadmap: Technological modernization, Capability enhancement, Cultural and change management, strategic governance, and compliance localization aligned with the Technology-Organization-Environment framework. This study offers an empirically grounded framework that highlights context-specific barriers to HR analytics adoption in Pakistan’s banking sector and extends perspectives on technology adoption in emerging economies.
Authors
- Farah Pervaiz
- Ghulam Muhammad (ORCID: https://orcid.org/0000-0002-6110-5119)
Institutions
- Iqra University (PK)
- Department of Commerce (AU)
Publication Details
- Journal
- Istanbul Business Research
- Published
- 2026-09-04
- DOI
- https://doi.org/10.26650/ibr.2026.55.1804503
- Primary Topic
- AI and HR Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00