International Journal of Human Capital in Urban Management
Quarterly Publication

Human resource analytics: a novel approach to bridge the gap between human resource functions and organizational performance

https://doi.org/10.22034/IJHCUM.2024.02.06
Volume 9, Issue 2 - Serial Number 34
Spring 2024
Pages 267-278
International Journal of Human Capital in Urban Management

Document Type : ORIGINAL RESEARCH ARTICLE

Authors

A. Malik 1
N.A. Khan 2
A.A. Khan 2

1 Department of Human Resource Management College of Business Administration, Prince Sattam Bin Abdulaziz University, Kingdom of Saudi Arabia

2 Department of Commerce and Business Management, Integral University, Lucknow Uttar Pradesh, India

Abstract
BACKGROUND AND OBJECTIVES: Human resource analytics played a vital role in human resource practices like training, selection and performance management and other function of human resource management. The objective of this study is to identify the major challenges by understanding when, how and why human resource analytics leads to enhancement of performance of organization and unveil the methods that increase organization performances. The aim of stud is identifying the types of human resource decisions that can benefit from analytics and understanding the challenges and opportunities associated with incorporating data into decision-making. Impact on human resource functions: examine the specific areas within human resource management where analytics can have a significant impact. This may involve studying talent acquisition, employee engagement, performance management, training and development, and other human resource functions to assess how data-driven approaches can enhance efficiency and effectiveness.
METHODS: The present study is mainly based on the primary data which is collected from human resource management personal of top 10 private life insurance company is considered for data collection of research. The data were collected from 194 employees of the human resource department. Quantitative methods are used to examine primary data gathered from the companies. The data is collected through a questionnaire-based survey. The questionnaires were distributed to the target population, it is a closed questionnaire. Multiple regression analysis and t-test were applied to analyze the data. The statistical package for the social sciences software was used to process the data. Validity and reliability test along with one sample t-test, independent sample t-test are conducted in this research.
FINDINGS: The study found that the benefits of human resource analytics such as quick and reliable information processing, helping managers to draw meaningful patterns in the data, deeper insights in the employee data. Human resource analytics on organizational performance, multiple regressions were applied. The study found that the model explained 59% of the variance (R square = .593). The digitalization of human resource functions refers to the process of leveraging technology and digital tools to automate, streamline, and enhance various human resource processes and activities. It involves using digital platforms, software applications, and data-driven approaches to improve efficiency, accuracy, and effectiveness in managing human resources. Digitizing human resource processes reduces complexity within the department while also improving administrative quality and human resource flexibility.
CONCLUSION: The results demonstrated the importance of these fast decision making, better and improvement in the quality of decision-making significantly affects the human resource organizational performance and human resource functions. The study is helpful for human resource professionals to concentrate more on duties that are relevant to their work. In terms of efficiency, it is found that digitizing human resource procedures leads to an increase in administrative quality and human resource flexibility, as well as a decrease in bureaucracy within the function. Digitalization is a tool that speeds up the communication process while lowering costs, allowing companies to be more productive and perform more effectively and efficiently.

Keywords

Human resource analytics
Human resource function
Human resource management
Organizational performance
Subjects
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  • Receive Date 18 October 2023
  • Accept Date 30 November 2023

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