Use of Data Science in Human Resource Management

Posted on: April 16 2019, By : Shubham Naskar
Use of Data Science in Human Resource Management
Data Science is the scientific approach used to derive knowledge and insight from big and raw data to provide support for decision making. It is the application of various technological tools such as algorithms and artificial intelligence to derive meaning out of huge amount of data which cannot be explored or analyzed by mere use of human intellect or basic technological software. The use of data science and its necessity in HR field is due to the fact that everyday huge amount of data is being generated, which is unstructured. HR departments are generating more than ever before but at the same time they often struggle to turn their data into valuable insights.  

 
With the advancement of technology and networks used by the organizations, the input of data and information has been of a huge load. Practical HR training in Navi Mumbai gives in hand experience to use data for better decision making. This resulted in necessity of enhancing management. The extraction and organization of data for decision making or recruitment has been of severe difficulty. Data science has been really essential in different fields of management as it has the potential to assist in the prediction of employee behavior, support the analysis of the workforce and talent, provides evidence-based solutions for HR planning and overall business strategy. HR consultancy in Mumbai provides robust solution on how to manage workforce.

 
Nowadays Data science is a necessity to enhance the overall HR process. It increases the quality of new hires as it allows the recruiters to be more analytical and to base their strategic thinking on evidences derived and inferred from the big data. Placement Agency in Navi Mumbai makes data driven decision.  It improves the training and employee performances as data science provides accurate measurement of the effectiveness of a particular training.  Also, big data can support in understanding organizational phenomena such as employee engagement and retention. Data science gives the HR practitioner the ability to analyze real time information, get insight upon what is really happening within the organizational framework, and produce a robust manner to track employee performances and address matters to increase the engagement. Job consultancy in Mumbai use data to provide the best manpower for an organization.

 
Some of the basic trends data science incorporates to be a valid and necessary are:

 
·         Algorithms: These are well defined computational procedure that takes some values or set of values as input to produce a value or set of values as output.

 
·         Predictive Analytics: It can assist in the forecasting of trends in the Human Resource industry. The application of predictive analytics can lead the recruiter to forecast the creativity of a particular candidate at the workplace based on the personality dimensions of the individuals.

 
·         Artificial intelligence & Machine Learning: The algorithms incorporated in the design of an artificial intelligence program are design to allow the machine to learn from its own mistakes and experiences.

 
Data science facilitates and ensures the selection of the most appropriate employees for the organization; the implementation of data science trends mentioned above will support the selection of the best fit candidate for the organization (Manpower agency inNavi Mumbai). IT also facilitates the analysis of thousands resume in a really short amount of time. The accuracy of selection is enhanced through the incorporation of algorithms and machine learning techniques. Tracking employee engagement, assessing organizational needs, or appraising the employee performance will come to be enhanced and be highly accurate with the incorporation of data science trends in the HR field. The HR field, being sensitive to change, data science provides a robust and resilient support for the strategic design within the organization.
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