Big Data in Industrial-Organizational Psychology and Human Resource Management: Forward Progress for Organizational Research and Practice

Abstract

Big data and artificial intelligence (AI) have become quite compelling—and relevant, ideally—to organizations and the consulting services that help manage them. Researchers and practitioners in industrial-organizational psychology (IOP) and human resource management (HRM) can add significant value to big data and AI by offering their substantive expertise in how workforce-relevant data are measured and analyzed and how big data results are professionally, legally, and ethically interpreted and implemented by organizational decision makers, employees, policymakers, and other stakeholders in the employment arena. This article provides a perspective and framework for big data relevant to IOP and HRM that include both micro issues (e.g., linking data sources, decisions about which data to include, big data analytics) and macro issues (e.g., changing nature of big data, developing big data teams, educating professionals and graduate students, ethical and legal considerations). Ultimately, we strongly believe that IOP and HRM researchers and practitioners will become increasingly valuable for their contributions to the substance, technologies, algorithms, and communities that address big data, AI, and machine learning problems and applications in organizations relevant to their expertise.