Role of Human Resource Data Analytics
Human Resource Management was an administrative function for
many years until it evolved as more data driven and analytical to produce
strategic contributions to organizational goals. Now, HRM is no more just an
administrative operation but largely a strategic contributor in terms of
managing the people of the organization at all levels in the best possible
manner.
What is Human Resource Analytics
HR analytics, also referred to as people
analytics, workforce analytics, or talent analytics, involves gathering
together, analyzing, and reporting HR data. It enables your organization to
measure the impact of a range of HR metrics on overall business performance and
make decisions based on data. In other words, HR analytics is a
data-driven approach toward Human Resources Management
For more clarity, let me take you through an example;
A supermarket chain experiences a high staff turnover in the
customer service unit, the supermarket is unable to operation at his its best
and do not offer the best customer service due to lack of staffing. The
management has to invest lot of time and money in creating a brand name for
their supermarket chain to attract job seekers and uplift the productivity
level of customer service staff.
As a solution, HR analytics offers a data driven contribution to
identify the core reasons for high turnover and the reasons why the existing
staff are still interested to continue their roles. The management will be able
to differentiate the few positives as to why a set of employees remain
interested in their jobs and numerous negatives as to why a set of staff are
leaving their jobs.
Eventually, it helps the management to know their strengths to
build on it and their weaknesses to make improvement plans for better
productivity and customer service
Use of HR Analytics
Analysing and
reporting human capital data to top management and line managers leads to
informed decision-making about what needs to be done to improve business
results, the ability to recognize problems and take action to deal with them,
and the scope to demonstrate the effectiveness of HR solutions and thus support
the business case for greater investment in HR practices. Data must be
accompanied by analysis and explanation
Some
benefits of HR Analytic in light of the above:
- Collection and
analyzing past data on turnover to identify trends and patterns indicating
why employees quit.
- Collection of data on
employee behavior, such as productivity and engagement, to better
understand the status of current employees.
- Development of strategies and making of decisions that will improve the work environment and
engagement levels.
- Identifying patterns of employee engagement, employee
satisfaction and performance.
- Enabling fast,
automated collection of candidate data for recruitment from multiple
sources.
- Gaining deep
insight into candidates by considering extensive variables, like
developmental opportunities and cultural fit.
- Identifying candidates with attributes that are comparable to the top-performing
employees in the organization.
- Avoiding habitual
bias and ensure equal opportunity for all candidates; with a data-driven
approach to recruiting, the viewpoint and opinion of one person can no
longer impact the consideration of applicants.
- Providing metrics
on how long it takes to complete HR process (eg: hiring process) and enabling other departments to be more prepared and informed.
- Providing historical data pertaining to periods of over-hiring and under-hiring,
enabling organizations to develop better long-term hiring plans.
Data-driven
evidences give organizations the hint to focus on making the necessary
improvements and plan for future initiatives.
https://youtu.be/BdKZVaiVNhI
Collection of Data - It is necessary to collect and organize data from various operations and departments within the organization for successfully implementing analytics in HR. Data has to be acquired, sanitized, unified, and analyzed from multiple departments as well as from multiple business functions, including payroll and financeSolution – Allocate adequate time and acquire services from experts who can not only analyze the data but also gather and organize the right data. Form a committee of multiple existing employees/ senior managers along with the data expert/s in order to make sure at least some of the existing employees know how the data was collected and their knowledge can be utilised for future developments.
Lack of Data Analytics Skills - Though organizations promote the implementation of analytics in HR functions, the hard truth is that the analytics skills of most HR professionals are limited. This makes the successful implementation of HR analytics a hard task.
Solution - Provide adequate training
to become well versed with the art of converting data into meaningful insights.
Hire an expert to do a shadowing role for sufficient number of months and try
to build on that to move forward. Have identified firms who can do professional
data analysis in case of an urgent situation.
Privacy and Compliance - Analytics requires an adequate amount of data to be collected from various reliable sources to produce the desired results. While gathering data about an employee or a potential employee, especially from external sources, the HR professionals must consider privacy.
Solution – Request only the required information and establish good communication with the employees. Be ready to explain the necessity and advantages of collecting such data from the employees. Maintain high credibility level and ensure integrity within the Human Resource Unit.
Insufficient IT Resources - The implementation of analytics in HR is an IT-heavy process. Not all companies will have the resources to implement the required IT structure.
Solution – Outsource the services from reliable IT firms and use their services only when necessary. This will reduce cost and time spent in developing your own IT structure.
Employee Resistance - Organizations face resistance from HR professionals or
responsible employees for relying on technology to carry out HR functions, like
application tracking system, report generation without human intervention. The
entry of technology and computerized systems eliminate the human intellectual. There
are also chances that the analytics systems might not always be accurate in
predicting the right outcomes.
Solution – Engage HR professionals and relevant stake holders of the organization from step one to final step in implementing HR analytics. Address resistance at the beginning and value the human intellectual capacity as it could produce many more innovative ideas to uplift the process and procedures.
Conclusion
The HR Analytics is a modern concept and its value is fabulous
in the context of data-driven, organized structured and business friendly HR
decisions. The benefits outlined above are very much realistic and provides a
great sense of accuracy and consistency. When strategic HR decisions are evidence-based,
contradicting opinions and resistance from employees largely reduces. The
challenges in HR Analytics are also realistic but solvable with innovation and creativity
in this modern era.
References
Taylor, M.
A. &., 2014. Armstrong's Handbook of Human Resource Management
Practice. 13 ed. London: www.koganpage.com.
Velaikaran.
2017. [Film] Directed by Mohan
Raja. South India: 24am Studios.
This blog is very informative and useful for any person who wants to know about HRM data analysis's . It very clearly explains how Incorporating data analysis into your overall business strategy helps create a productive environment.
ReplyDeleteThanks Lasitha for your view. This is a modern HR concept and takes HRM to another level.
DeleteThis is excellent article. What are the four different types of human resources analyses?
ReplyDeleteHuman resources (HR) can better comprehend what is occurring in the organization by using data-supported patterns and evidence, such as employee engagement, general wellbeing, and the amount of training each team has received.
Descriptive analytics, which are made up of reports and observations, are crucial since they include studying the workplace to have a general understanding of what's happening.
To further analyze the findings and determine the why and the cause, diagnostic analytics is used. Although it may be obvious that employees are dissatisfied, it is crucial to determine why.
Although it is employed less frequently than the other types, predictive analytics allows businesses to foresee potential improvements and test them.
The next step, known as prescriptive analytics, considers the underlying cause of the problem and uses the data to suggest a course of action for resolving it. To achieve the best results, prescriptive analytics depends on the other three types of analytics.
Thanks for the insights and I wanted the article to be reader friendly. Hence, did not bring in a lot of literature but tried to bring in some examples for more clarify.
DeleteThe article provides a great introduction to human resource analytics. The example provided of a supermarket chain experiencing high staff turnover was a great demonstration on how HR analytics can be used to identify the reasons for high turnover and to make data-driven decisions to improve employee engagement and productivity. However, I believe that HR analytics should not be used in isolation and should be accompanied by analysis and explanation.
ReplyDeleteThanks Chandri for your encouraging comment. I agree with you. HR Data without analysis and interpretation is of no use. To meet the objectivity of HR Analytics, it has to be paired with organizational policies, data analysis and critical thinking of HR Professionals.
DeleteThis is a good article to get an idea on how to start an HR Analytics process while outlining the challenges of implementing such as process.
ReplyDeleteThanks for the positive comment and hope you were enlightened. The challenges are unavoidable but very much manageable.
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