A Study on HR Analytics for Attendance Patterns and Organizational Insights

Abstract

In today’s corporate world, managing employee attendance effectively plays a key role in helping organizations succeed. This research takes a closer look at attendance patterns using HR analytics, based on anonymized attendance data from the year 2022–2023. By applying data analysis techniques, the study identifies important trends in attendance, patterns of absenteeism, and possible reasons that influence whether employees are at work. These insights can help HR teams plan better, improve attendance, and increase overall productivity. The research also shows how HR analytics can support smarter decision-making around employee engagement and attendance. Finally, the study offers practical, data-based recommendations that organizations can use to improve their HR practices and create a more efficient and supportive work environment.

Introduction

Employee attendance is crucial for organizational productivity, operational continuity, and workforce morale. High absenteeism increases costs and disrupts teamwork and project timelines. The rise of HR Analytics enables organizations to use data-driven approaches to analyze attendance patterns, predict trends, and identify causes of absenteeism, allowing targeted interventions to improve workforce reliability.

This study analyzed anonymized employee attendance data from 2022–2023 using HR analytics tools like Excel, Power BI, and Power Query. Key metrics such as presence rate, work-from-home (WFH) percentage, and sick leave (SL) were examined. Findings showed generally high attendance rates, low sick leave, and active use of hybrid work arrangements, especially in digital teams. Some fluctuations in absenteeism correlated with holidays, seasonal changes, and possible weekend extensions.

Department-level analysis revealed variations in attendance and WFH use, informing team-specific HR policies. Visualization tools enhanced real-time insights, while partial-day leave use reflected flexible HR practices. The study highlighted the importance of continuous monitoring and proactive management of attendance to boost employee engagement and organizational performance.

Conclusion

The effective management of employee attendance is fundamental to ensuring organizational efficiency, workforce stability, and overall productivity. Through the application of HR Analytics on real-world attendance data from the financial year 2022–2023, this study successfully identified critical attendance patterns, leave trends, and underlying behavioural insights within the workforce. The findings highlighted that while most employees maintained consistent attendance, periodic peaks in absenteeism corresponded with seasonal changes and organizational events. Flexible work options like Work from Home (WFH) and employee-friendly leave policies such as Birthday Leave (BL) and Floating Festival Leave (FFL) were observed to contribute positively towards employee engagement and satisfaction. This research demonstrates that HR Analytics serves as a powerful tool for organizations to move beyond traditional attendance tracking towards proactive and strategic workforce management. By continuously monitoring attendance patterns, identifying risk factors, and implementing targeted interventions, organizations can not only reduce absenteeism but also enhance employee morale and operational resilience. For future research, expanding the analysis to include employee demographics, departmental data, and performance metrics could offer even deeper insights. Furthermore, integrating predictive analytics models could assist HR teams in forecasting absenteeism risks and planning preventive strategies more effectively.

Copyright

Copyright © 2025 T. Neelima, Dr. T. S. Poorna Chandrika. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.