Role of data science professionals in HRM

Human resource management, or HRM, is one of the important areas in which most companies invest. Without it, companies won’t be able to maintain appropriate culture and ambience for their employees or even promote thoughts of positivity, productivity, and better performance. HR management includes four major fields: recruitment and onboarding, salary and compensation, employee relations, and training and development. 

Human resource management is often perceived as a straightforward task; however, the truth is quite the opposite. HR activities are intricate, and managing them can be challenging. Making informed and well-thought-out decisions is crucial to ensure the efficacy of HR management. An uninformed decision could adversely impact employee morale and hinder the company’s progress. Therefore, it’s essential to approach HR management with careful consideration and attention to detail.

In addition, you must consider studying big data or implementing data science in HRM. 

Data science in HRM

With the growing demand for data, HRM professionals are bound to reconsider business decisions and analyze whether they are meaningful and relevant. For instance, when HR professionals decide to run a recruitment drive online without planning for employee onboarding, they fail to realize the possible chances of failure. It is primarily because the professionals do not have enough information concerning the benefits of employee onboarding, its success rate, and so on. 

This is where you may need data science and data analytics. It is the study of datasets in different ways with the sole aim of acquiring important information through visual insights. It can be employee sustenance rate expressed as bar graphs over the past 6 months or employee satisfaction percentage based on age group expressed in a pie graph. Therefore, it is easily understandable that data science can yield valuable information from various datasets and transform them into understandable and readable insights. 

It will help the HRM professionals to work on HR strategies and act accordingly. For instance, HR managers can check the visual insights to know more about employee satisfaction and experience. This will further reveal whether the existing strategies can increase employee satisfaction. Accordingly, they can improve the incompetent strategies and ensure all employees feel at ease, welcomed, and valued. After all, no company can succeed without its employees.

Following are some reasons businesses invest in data science for human resource management. 

• First, data science is crucial in obtaining insights from different datasets, such as employee feedback, cover letters, and resumes. 
• HR professionals can easily make decisions without worrying about the success rate because the decisions are based on real-time insights with accurate information. 
• It becomes easy for HR professionals to understand what the employees think before making any company changes. 
• Making appropriate strategies for digital transformation, technology adoption, and employee onboarding becomes easy with the help of data science. 

Application of data science in HR

Understanding the real-time applications of data science in human resource management and operations is important. Unless the concept is clear, it will be difficult for professionals to make appropriate decisions and changes. Thus, to help you understand the significance of data science in human resource management, we have explained four of its applications.

1. HR Data Analysis

Although HR data analytics is novel, its importance in making business employee-related decisions is impeccable. It is a process through which various data sets can be transformed into visual insights in graphs and charts and studied to gain deeper knowledge about a certain matter. 

Data analytics in HR allow professionals to make appropriate decisions, understand the impact of various strategies on overall business performance and productivity, and detect the loopholes in the existing HR management strategies.

With the help of HR data analytics, you can easily extract insights such as:

• The average employee turnover per year
• Approximate cost to retain an employee in a year
• The employees who are likely to leave the company by the end of the fiscal year
• Various departments in the business or company that might need new talent in the upcoming year

According to several studies, data analytics in HR will play a crucial role in facilitating recruitment and employee onboarding moving ahead. Businesses planning for a recruitment drive usually decide on the target audience according to the results obtained from data science and analytics. That’s why the response from the target audience towards the recruitment drive is high and prompt. Companies can also use appropriate onboarding strategies to retain as many new employees as possible by the end of the same year.

2. Talent Analytics

Another major area where data science has numerous applications is talent analytics. It is a process of understanding business requirements in depth.

For example, when a company decides to analyze the project requirements, it relies on data science. The analysis reveals the gaps in talent and skills, allowing HR professionals to decide what type of candidates they need to hire. For instance, they can easily decide if IT professionals with specializations or fresher employees would suffice. Such data-driven insights help companies make appropriate decisions based on talent analytics.

3. Predictive HR

As the name suggests, predictive HR analytics will determine future results and decisions based on past and present datasets. For instance, businesses can compare employee sustenance cost and satisfaction rate to decide whether to increase the overall budget in the upcoming year. Such decisions or changes must always depend on datasets since they provide real-time insights instead of any assumption. 

4. HR Data Visualization

Last but not least, data science helps in HR data visualization. It is a technique through which you can convert datasets into insights and make them more understandable using various visualization tools. For instance, expressing the datasets and insights in graphs and pie charts can help in comparison, sectional employee representation, etc.

Conclusion

In this article, we have explained the use of data science in HRM. Data science can help HR professionals make data-driven decisions while acquiring proper knowledge about their employees, business performance, and productivity. If you want to learn more about data science, you can complete online courses from Manipal Academy of Higher Education (MAHE) at Online Manipal. These courses come with different specializations to help you acquire in-depth knowledge of the subject. Check out our website today!

Key takeaways:

• Data science in HRM involves the study of employees, talent requirements, and employee retention. 
• HR professionals can improvise or make changes in employee relations strategies with the help of data science. 
• Data science is essential to reduce HR risks in the business, such as employee leaving, dissatisfaction, lack of productivity, and more.