The Role of Behavioral Data Analytics in Human Resource Performance Management
Keywords:
Behavioral data analytics, performance management, human resources, artificial intelligence, data-driven decision-making, organizational cultureAbstract
Objective: This study aims to examine the impact of behavioral data analytics on improving human resource performance management and to identify its key dimensions in organizations.
Methods and Materials: This research is a qualitative review based on the analysis of 12 selected articles published in the field of behavioral data analytics and human resource performance management. Data were collected through a systematic review and qualitative content analysis until theoretical saturation was achieved. Nvivo 14 software was used to organize and analyze the data, with codes categorized into main themes and subthemes.
Findings: The findings revealed three main dimensions of behavioral data analytics: “enhancing employee performance,” “role of technology and data infrastructure,” and “organizational outcomes.” Behavioral analysis enables the identification of performance patterns, prediction of high-risk behaviors, and provision of personalized feedback. Data-driven technologies, including HRIS, artificial intelligence, and big data, facilitate the processing and analysis of large volumes of data. Organizational outcomes include improved HR decision-making, increased employee motivation and engagement, human capital development, and enhanced organizational transparency and trust. Implementation also requires careful attention to ethical considerations, data privacy, and data quality.
Conclusion: Behavioral data analytics is an effective tool for enhancing human resource performance management, strengthening evidence-based decision-making, and fostering a data-driven culture in organizations. However, the success of this approach depends on robust technological infrastructure, ethical frameworks, and managerial training in data interpretation.
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