Human Analytics in Human Resource Management

Human Analytics in Human Resource Management

In recent years, the human resource management field has changed in the wake of
changes in the business environment, mainly driven by technological changes. The area has
evolved from a simple placement function to a state where data and algorithms are utilized to
spearhead cutting-edge business solutions. Indeed, research undertaken by Deloitte in 2015
showed that an estimated 35 percent of companies listed in the survey have considered the role
of data analytics contribution to the human resource function (Lengnick-Hall et al.,2018). Data
analytics is concerned with interpreting data patterns in the organization aimed at smoothening
decision-making and guiding performance. More importantly, the people-oriented nature of
human resource function in the organization has also underpinned the role of analytics in human
resource management (Hamilton, & Sodeman, 2020). Aspects of human resource management
such as retention rate, time to hire, and employee performance can easily be assessed with data
analytics capabilities. In the context of the Australian Public Sector, the role of data analytics is
even significant.
Value of Data Analytics for HR professional
The human resource managers of the 21 st century have become reliant on technological
innovations, especially the use of data of employees, which was not permissible in the decades
that have passed. Thus, the application of data has revolutionized how human resources
processes for the public sector in Australia are undertaken by professionals (Hamilton, &
Sodeman, 2020). Human resource professionals are hence able to capture data on employees as
technologies continue to evolve. Human resource analytics also presents myriad capabilities of

capturing, organizing, measuring information collected on human resource platforms and
frameworks to develop valuable insights for the organization.
Human resource professionals have also been able to leverage analytics' benefits in
promoting data-driven decision-making, which is slowly emerging as a standard measure in
several human resource processes. The data collected by HR professionals can be leveraged to
boost the process of decision-making concerning recruitments, the performance of respective
employees, and the operational quality of human resource software (Hamilton, & Sodeman,
2020). Equally, the HR professional can drive improved business strategies by leveraging the
capabilities of HR analytics to development. Thus, fundamental tenets where HR analytics create
value to the HR professional work is based on;
Performance and Efficiency
The human resource function success in the organization is measured along with human
resources processes based on efficiency and output of employees. Therefore, HR analytics
provide the metrics which enable the HR professional to have insights into the overall
functioning of the processes. For example, to track the overall retention rate of new employees
hired, the HR professional can collect data to examine the efficacy and reliability of sources'
influence on the quality of hires. In essence, using the capabilities of human resource analytics,
the professional can ascertain that internal referrals tend to result in a better retention rate than
sources such as LinkedIn or other public authorities (Hamilton, & Sodeman, 2020).
Therefore, with the realization of the capability of HR analytics, the organization can
reorganize the workflows in a manner that prioritizes internal referrals against other sources,
which provide more preliminary result. As a result, the hiring process is improved. Similarly, the

organization can apply the elements of HR analytics in tracking metrics such as hiring duration,
applications, hiring effectiveness, employee satisfaction rate, applicants per opening,
applications, and hired sources. Also, the organization can prioritize the application of resources
on areas that lead to a more significant impact.
Improving recruitment and hiring processes
Additionally, HR analytics helps the organization save money and time involved in
filling vacant positions. A report carried out by Talent Acquisition Benchmarking Report in 2017
revealed that it takes on average 36 days for businesses to fill a vacant position which translates
to over $4500 per hire. Armed with the data, it is critical to use data analytics components to aid
in cost savings. In effect, the organization can use data to help HR professionals accurately
choose who shall be the best fit for a given role in the Australian Public Sector that aligns with
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