Over the recently passed decade , HR analytics has emerged as a major buzz word. Knowing its meaning and importance , may help us in taking benefits of its numerous advantages for the betterment of our organizations.
1.0 Contents of this blog
The author proposes to discuss the following aspects of Human Resource analytics in this blog.
– Different types of analytics
– Challenges before HR analytics
– Future of HR analytics
2.1 Definition of analytics
Wikipedia defines the analytics as the following.
Analytics is the systematic computational analysis of data or statistics .It is used for the discovery ,interpretation and communication of meaningful patterns in data. It also entails applying data patterns towards effective decision making. Organizations may apply analytics to improve business performance.
Other experts have defined the analytics as the interpretation of data patterns that aid decision making, and performance improvement.
2.2 Definition of HR analytics
Wikipedia defines the Human Resource analytics as the following.
HR analytics is an area in the field of analytics that refers to analytics processes to human resource department of an organization. It is supposed to improve employee performance and ,therefore , giving a better return on investment.
On the other hand , definitions given by other experts are.
– HR analytics is the application of statistics, modelling and
employee related factors to improve business
-HR analytics is the science and technology of gathering, organising and analysing data related to HR functions like recruitment, talent management, employee management , performance improvement and retention to ensure better decision making.( naukrirms.com)
– HR analytics involves using analytics to optimise the HR functions in a way, that aligns with the organisation strategic goals. (mhranalytics .com)
3.0 Different types of analytics to deal with HR issues
The experts usually adopt following four types of analytics to get an insight into human resource issues of an organisation. Each furnishes a different perspective on an organisation data. Each has its pros and cons, but build upon each other.
3.1 Descriptive analytics
We may define descriptive analytics as a primary basic type of analytics, which takes historical data and summarizes it into something , that is understandable. Thus, it describes the current status of things and or past events. In other words, it enunciates what is happening in the organisation and what happened in the past.
3.2 Diagnostic analytics
Diagnostic analytics present the reasons or causes of the events revealed by descriptive analytics.
If one knows the causes or reasons , then one also definitely knows, where to focus efforts to mitigate the problem.
3.3 Predictive analytics
Predictive analytics may also be termed as forecast analytics. In that sense, it predicts what is going to happen in future. If we know what is going to happen in future, we may be alert and take corrective actions.
Predictive analytics is usually carried out by modelling of data , taking help of machine learning and artificial intelligence.
3.4 Prescriptive analytics
Prescriptive analytics may be defined as the solution or prescriptions , which we my like to recommend for addressing the problem. It may suggest the following.
– Intelligent decisions based on the scientific analysis of data available with you.
– Actions required to be taken.
– Skill enhancement initiatives , if they are found lacking
The most beautiful aspect of prescriptive analytics is the total absence of illogical human biases and prejudices. This is owing to the fact that entire analytics is woven around correct and quality data and processed by software programs.
4.0 Advantages of HR analytics
HR analytics provides enumerable advantages , which , we have tried to entail below.
4.1 Better human resource decisions
Since these decisions emerge after scientific analysis of data, after applying machine learning, artificial intelligence and software programs, they are free from personal biases and prejudices.
4.2 Increased Return on Investment (ROI)
ROI may improve significantly due to following reasons.
– Better hiring through application of business analytics
– Improved retention
It is to be noted here that the cost of replacing an employee maybe 200% of their annual salary. True cost may be even higher. HR analytics may help improve retention through chum analysis.
– Automation of tasks
– Process improvements
– Improved employee experience
– More productive workforce
– Improved workforce planning through talent development
– Total transformation of HR functions, as a result of workforce analytics
4.3 Improves HR alignment to business strategy
HR functions are specially tuned to the business strategy. The ultimate aim of HR analytics is to improve business .
4.4 Reduction in HR Related Costs
Automation and application of software reduces the HR costs substantially.
4.5 Helps in building a better workplace
HR analytics helps in building a better workplace due to the following.
-It strengthens recruitment
– HR analytics helps in streamlining the hiring
– Turnover of employees is reduced
-Employee engagement is in the upward direction
– It identifies the behaviour of individuals. Also larger patterns of employee behaviour are known, which , management may utilise to their advantage in building a better workplace.
4.6 Reduced talent scarcity
Predictive analytics for succession planning helps in reducing the talent scarcity.
5.0 Disadvantages of HR analytics
We must bear it in mind that HR analytics is proving to be a boon in the field of human resource. However, it may prove to be disadvantageous too , because of the following reasons.
5.1 Enormity and sensitivity of HR data
The past and present data available with HR professionals is simply huge. It involves sensitivity, confidentiality, privacy and security to prevent any pilferage or mis-utilization.
5.2 Stringent requirements of a fool-proof HR analytics system
An HR analytics systems must be designed ,which is totally fool proof. It must contain multiple layers of access. A provision should also be made for constant and continuous monitoring to ensure security and safety of data.
5.3 Huge costs involved
An adequately designed HR analytics system requires lot of sophisticated acquisitions and software programs, which are expensive. Hence, smaller companies may find it economically unviable.
5.4 High level of expertise required
Operating sophisticated HR analytics tools requires special expertise. This may lead to additional training and acquisition costs.
6.0 Challenges before HR analytics
HR analytics is facing the following challenges in the modern day world.
6.1 Identifying the best HR technology to handle and track data
Though ,lot of progress has been made in this direction ,yet ,identifying the best technology to handle and track data is still a difficult proposition.
6.2 Intense and appropriate data gathering, cleansing and analysis.
This may consist of data analysis through sophisticated tools. In fact, gathering of correct and high-quality data is in itself an onerous task. Finding the right people with data mining and data analysis expertise is another challenge.
Tuning it to the business strategy of the organization and being able to deliver actionable HR insights before leadership is another challenge.
However, the speed of learning is very rapid in the field of HR analytics. A day may come soon, when all the challenges may be overcome.
7.0 Future of HR analytics
Monumental changes are being experienced in the field of human resource. HR analytics is helping us immensely in making decisions for effective functioning of human resource aspects across the organizations.
In spite of the above, the need for further refining HR analytics and making it advanced, fool proof, the following technologies/ aspects may play a major role.
7.1 Machine learning
Machine learning accelerates business through automation.
7.2 Artificial intelligence
Artificial Intelligence helps eliminate human errors. It may also transform the future of HR analytics by adopting the following ways.
-As per IBM, artificial intelligence may be integrated in employees on boarding programs, which will improve HR analytics.
-Artificial intelligence recruiters may help to automate interview scheduling for providing real time feed back to employees. This may also improve the handling of big data HR analytics.
-It may also identify the employees on the way out.
– AI can remove biases in the organization
– It may improve efficiency and insight in candidate assessment.
7.3 Organizational Psychology
Principles of organizational psychology may be applied in HR analytics with a view to improve productivity. For this, overall well-being of employees must be kept in view, along with the strategic goals and objectives of the organization.
If you are looking to upgrade your skills in HR Analytics, you might want to consider a certification in HR Analytics by CHRMP. To learn more click here.