Topic: HR Analytics
Author: Anushri Pappu
1.Importance of Analytics in HR Management:
Nair, M. (2023) says that HR should be able to do better by starting with the fundamentals and then working up its way. This can be done through useful analytics. As HR departments become increasingly reliant on the numbers they produce and on advanced technologies, they will start experiencing the need for new skillsets. Also, the technological obstacles related to business data will have to be overcome for HRA to create an impact on HR practices, which would mean both organizational redesign as well as a cultural change at the same time
2.Harmonizing HR Analytics: Addressing Legislative, Regulatory, Data Privacy Requirements, and Fraud Prevention.
Mittapally, B. (2023) saysthat incorporating fraud prevention measures into HR analytics strategies is crucial for organizations to proactively address fraudulent activities within HR processes. Organizations can detect and prevent fraud effectively by leveraging data-driven insights, enhancing internal controls, fostering collaboration, and promoting a culture of trust and accountability. This integration protects the organization’s resources, ensures the integrity of HR processes, and cultivates a secure and ethical work environment. By harmonizing legislative, regulatory, data privacy requirements, and fraud prevention efforts, organizations can navigate the complexities of HR analytics while upholding ethical practices and compliance standards.
- Human Resources Analytics for Public Personnel Management
Cho, W., Choi, S., & Choi, H. (2023) This study is based on early observations with only anecdotal evidence available, as the use of HR analytics in the public sector is still in the early stages. This means that more research is needed to fully understand the nature and challenges of HR analytics in the public sector. Future research should aim to collect rich empirical evidence from different cases to assess the success factors of new technology adoption. This could include a variety of research methods such as case studies, surveys, and experiments. Additionally, it would be useful to consider a range of different public sector organizations to gain a more comprehensive understanding of the potential benefits and challenges of HR analytics in this context.
- Human Resource Analytics: Key to Digital Transformation.
Anam, & Israrul Haque, M. (2022) says that aligning the HR function activities with HR analytics can help it to perform transactional tasks quickly. Hence, HR leaders can effectively focus on their strategicactivities (Bhattacharyya, 2017). HR analytics will develop more in an ever-changingfield and business context if used and applied accurately. Although adopting HR analytics requires great effort, it can advance the profession of HR and be a win-win opportunity for the organization (Bassi, 2011). Thus, HR analytics is essential for providing accurate and real-time information to have more power over competitors. This study is relevant in today’s emerging era of data and analytics. The study provides different perspectives, essential to handling various organizations’ challenges, especially the HR departments. The study shows practical solutions to the everyday problems faced by the organizations, such as high recruitment costs, talent management, declining sales, voluntary turnover, etc. Also, the study proves that adopting and using analytics would result in better performance overall.
- Turnover Analytics & Forecasting Hiring Demand: HR Domain
Valluru, S. (2018) says In this study we presented an approach to predict the employee turnover for the next quarter using machine learning technique Support Vector Machine (SVM). Along with SVM,we tried alternate classification model Random Forest (RF),SVM gave better results. By considering predicted attrition results as leading indicator, forecasted hiring demand using ARIMAX for the next quarter with reasonable accuracy. It helps human resources in predicting employee turnover in advance and provides reasonable time to identify alternate resources orto recruit new resources to avoid project execution problems.This model also helps human resources in recruitment by estimating the total number of resources required for specific skill, location and experience. This optimizes the resource demand and availability of readily deployable resource for smooth execution of business.
- 6. Bridging the gap: why, how and when HR analytics can impact organizational performance.
McCartney, S., & Fu, N. (2022) says, HR analytics serves as a vital tool for organizations looking to enhance their performance by leveraging data-driven insights into human resources management. By analyzing data related to workforce demographics, performance metrics, recruitment, and employee engagement, HR professionals can make informed decisions that optimize talent acquisition, development, and retention strategies. Through the application of advanced analytics techniques, such as predictive modeling and machine learning, organizations can anticipate future trends and proactively address challenges. Integrating HR analytics into strategic decision-making processes enables organizations to align their human capital strategies with broader business objectives, ultimately driving productivity, efficiency, and organizational success. Therefore, by bridging the gap between data and decision-making, HR analytics emerges as a cornerstone for driving sustainable performance and competitiveness in today’s dynamic business landscape.
- HR analytics is crucial for IT companies in Delhi NCR to:
SINHA, D.; SINHA, S.; CHAUDHARY, U says that HR analytics is indispensable for IT companies operating in the dynamic market of Delhi NCR. By leveraging data-driven insights, organizations can optimize talent acquisition and retention strategies, bridge skills gaps, foster diversity and inclusion, enhance employee performance and productivity, and mitigate risks associated with attrition. Strategic workforce planning and predictive analytics enable companies to stay agile and adapt to changing market conditions, while continuous improvement initiatives ensure a culture of innovation and excellence. Ultimately, the integration of HR analytics across various aspects of human resource management is essential for driving organizational success, maintaining competitiveness, and achieving sustainable growth in the highly competitive IT sector of Delhi NCR.
- HR Analytics in the Commercial Aviation Sector: A Literature Review.
de Brito, A. P., & Sousa, M. J. (2023) says HR analytics in the commercial aviation sector involves leveraging data-driven insights across various aspects of human resources management within airlines and related organizations. This includes talent acquisition, performance management, crew scheduling, training and development, workforce planning, and employee engagementThrough the systematic collection, processing, and analysis of data, airlines can optimize recruitment strategies, identify top performers, improve crew scheduling efficiency, tailor training programs, forecast workforce needs, and enhance employee satisfaction and retention. By making informed decisions based on data analysis, airlines can achieve operational excellence, improve safety standards, and ultimately deliver a superior passenger experience.In conclusion, HR analytics plays a crucial role in enabling airlines to strategically manage their human capital, drive efficiency, and maintain competitiveness in the dynamic commercial aviation industry.
- Can HRM predict mental health crises? Using HR analytics to unpack the link between employment and suicidal thoughts and behaviors.
Hastuti, R., & Timming, A. R. (2023) says Human Resource Management (HRM) harnesses HR analytics to deeply analyze various data points within the workplace to identify potential indicators of mental health issues among employees. These data include patterns in absenteeism and leave, fluctuations in performance metrics, turnover rates, insights from employee surveys, and healthcare claims data related to mental health services. By examining these factors collectively, HR professionals can uncover trends and risk factors associated with mental health challenges in the workplace. This comprehensive approach enables organizations to implement targeted interventions and support mechanisms to promote employee well-being and mitigate the risk of mental health crises. However, it’s imperative to approach the use of HR analytics in mental health with sensitivity, ensuring employee privacy, confidentiality, and ethical considerations. Additionally, HR analytics should complement personalized support and interventions, emphasizing the importance of a supportive work environment in fostering mental health resilience among employees.
10.Bringing HR and Finance together with Analytics
Higgins, J. (2014) says Bringing HR and Finance together with analytics entails a multifaceted approach that involves integrating data sources, employing advanced analytics techniques, and aligning strategic initiatives. By combining datasets from HR and Finance departments, organizations can create a unified data infrastructure that facilitates comprehensive analysis. Leveraging tools such as predictive modeling, machine learning algorithms, and data visualization enables the extraction of actionable insights from integrated data sets. In conclusion, bringing HR and Finance together with analytics empowers organizations to make data-driven decisions that optimize resource allocation, enhance operational efficiency, and drive sustainable growth. By integrating technical capabilities with strategic vision, businesses can unlock the full potential of their human capital and financial resources to achieve long-term success in today’s competitive landscape.
Research summary:
The project “Enhancing Organizational Performance through Integrated HR Analytics: A Multi-Sectoral Approach” is an in-depth exploration of how HR Analytics can strategically impact various industries, such as Information Technology (IT) and commercial aviation. It begins with a thorough review of existing literature to understand the theoretical foundations and practical applications of HR Analytics. Through the analysis of real-world case studies from different sectors, the project examines how organizations utilize HR Analytics to optimize workforce management, enhance productivity, and drive business success.
Furthermore, the project employs advanced data analysis techniques to extract insights from HR and financial data sets. By integrating HR and financial analytics, organizations can gain a holistic understanding of their human capital investments and make data-driven decisions to allocate resources effectively. This integration enables organizations to align HR strategies with broader business objectives, maximize return on investment, and foster a culture of innovation and continuous improvement. One significant aspect of the project is its investigation into the predictive capabilities of HR Analytics in addressing mental health challenges in the workplace. By analyzing employee data and identifying early warning signs of stress, burnout, or other mental health issues, organizations can proactively implement interventions to support employee well-being and mitigate risks to organizational performance Overall, the project aims to provide actionable insights and recommendations for organizations seeking to leverage HR Analytics to enhance their competitiveness and success in today’s rapidly evolving business landscape. By embracing data-driven decision-making and strategic integration of HR and financial analytics, organizations can unlock new opportunities for growth, innovation, and organizational excellence.
References:
Nair, M. (2023). Status and Importance of Analytics in HR Management: A Systematic Literature Review. IUP Journal of Management Research, 22(2), 28–48.
Mittapally, B. (2023). Harmonizing HR Analytics: Addressing Legislative, Regulatory, Data Privacy Requirements, and Fraud Prevention. Workforce Solutions Review, 31–34.
Cho, W., Choi, S., & Choi, H. (2023). Human Resources Analytics for Public Personnel Management: Concepts, Cases, and Caveats. Administrative Sciences (2076-3387), 13(2), 41. https://doi.org/10.3390/admsci13020041
Anam, & Israrul Haque, M. (2022). Human Resource Analytics: Key to Digital Transformation. IUP Journal of Management Research, 21(3), 38–54.
Valluru, S. (2018). Turnover Analytics & Forecasting Hiring Demand: HR Domain. International Journal of Business Insights & Transformation, 12(1), 3–5.
McCartney, S., & Fu, N. (2022). Bridging the gap: why, how and when HR analytics can impact organizational performance. Management Decision, 60(13), 25–47. https://doi.org/10.1108/MD-12-2020-1581
SINHA, D.; SINHA, S.; CHAUDHARY, U. Study of the Importance of HR Analytics in the IT Sector, Delhi-NCR. BVIMSR Journal of Management Research, [s. l.], v. 15, n. 1, p. 9–16, 2023. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=5a938460-dd3e-36b1-a869-1f4f5552514c. Acesso em: 26 fev. 2024.
de Brito, A. P., & Sousa, M. J. (2023). HR Analytics in the Commercial Aviation Sector: A Literature Review. Proceedings of the European Conference on Management, Leadership & Governance, 512–519.
Hastuti, R., & Timming, A. R. (2023). Can HRM predict mental health crises? Using HR analytics to unpack the link between employment and suicidal thoughts and behaviors. Personnel Review, 52(6), 1728–1746. https://doi.org/10.1108/PR-05-2021-0343
Higgins, J. (2014). Bringing HR and Finance Together with Analytics. Workforce Solutions Review, 5(2), 11–13.