Integrating Data-Driven Analytics into Human Resource Management to Improve Decision-Making and Organizational Effectiveness

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@article{1706749,
      author = {Richard Okon, Chinekwu Somtochukwu Odionu, Bernadette Bristol-Alagbariya},
      title = {Integrating Data-Driven Analytics into Human Resource Management to Improve Decision-Making and Organizational Effectiveness},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {6},
      pages = {574-596},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706749.pdf},
      abstract = {This review paper examines the integration of data-driven analytics into Human Resource Management (HRM) and its role in enhancing decision-making and organizational effectiveness. The primary objective is to synthesize existing research on the strategies for leveraging data analytics to optimize key HR functions such as talent acquisition, performance management, employee retention, and workforce planning. By analyzing a wide range of academic and industry literature, the paper provides a comprehensive overview of how data-driven insights can transform HR practices. The findings suggest that organizations incorporating data analytics into HRM processes achieve improved decision-making accuracy, reduced biases, and enhanced predictive capabilities regarding workforce trends. The review highlights the positive impact of data-driven HRM on employee engagement, talent alignment with organizational goals, and overall organizational agility in responding to market dynamics. The paper also explores the strategic implications of this integration, including the necessity for HR professionals to develop data literacy skills and the ethical challenges related to data privacy and algorithmic decision-making. Additionally, the review identifies potential barriers to the adoption of analytics in HRM, such as technological infrastructure and cultural resistance within organizations. The paper underscores the significant opportunities presented by data-driven HRM in driving organizational success. It further discusses future prospects, including the growing influence of artificial intelligence in HR analytics and the potential for more customized employee experiences, signaling a shift toward more data-centric HR practices.},
      keywords = {Data-Driven Analytics, Human Resource Management (HRM), Predictive Modeling, Scenario Planning, Real-Time Data Monitoring, Continuous Improvement, Workforce Management, Organizational Performance, Strategic Alignment, Employee Engagement, Personalized Employee Experiences, Data Quality, Ethical HR Practices, Proactive Decision-Making, HR Strategies.},
      month = {December},
  }