AI Implication and Data-Driven Decision Making for Organizational Performance

AI Implication and Data-Driven Decision Making for Organizational Performance

S. Dhana bagiyam (Christ University, Bengaluru, India), Mohammad Irfan (Christ University, Bengaluru, India), and Ratno Agriyanto (Universitas Islam Negeri Walisongo Semarang, Indonesia)
Copyright: © 2025 |Pages: 24
DOI: 10.4018/979-8-3693-6412-3.ch011
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Abstract

HR analytics, also known as people analytics, involves using data-driven decision-making in HR management to improve various aspects of business and people outcomes. It gained prominence around 2019 and offers substantial benefits to organizations. However, its adoption is not widespread, and it's still in its early stages. Data-driven HRM involves collecting and analysing data from various sources to inform HR decisions across functions like talent acquisition, performance evaluation, employee engagement, training, compensation, diversity and inclusion, compliance, and strategic planning. Implementing HR analytics requires investments in technology, analytics capabilities, and employee training while ensuring data ethics and security compliance. In essence, this study seeks to examine existing challenges and barriers related to HR analytics, with a core aim of providing recommendations to enhance its effectiveness and streamline its integration. Additionally, it intends to evaluate how well HR analytics is currently functioning within organizations.
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