How Big Data Analytics Can Make the Recruitment Process More Effective
Organizations around the world are now learning about the power of big data. They are learning about the advantages of leveraging the big data in everything they do, from formatting policies for workers to planning the next move to the market. So, big data analytics can provide a completely new insight into processes or procedures being followed in the company.
There is one common process followed in every organization, regardless of their nature of work. It’s the recruitment of candidates. Can big data make it more efficient and help organizations find the best of talents? Of course, it can.
· A 2015’s report by Deloitte found many companies interested in using big data in their recruitment process. A recently conducted survey shows that more than 40% of companies have either adopted or started to adopt cognitive technology and data-driven analytics tools.
· Forbes finds out that an increase of as low as 10% in the accessibility of the data could increase the income by over US$65 million of those companies which fall in the usual Fortune 100 companies’ list. Right now, only 0.5% data collected from various resources is actually analyzed.
This is how organizations can make better use of big data in talent recruitment process
1. Analyzing past Data –
Organizations can use data analytics to find historical hiring patterns and trends based on data collected from past hires. They can track the progress made by employees hired in the last couple of years. You can also review their skills sets, experience levels, and then the same data points can be used for hiring future talents.
2. Screening possible Talent – The information created by analyzing the past data, HRs can make smarter decisions during the hiring process and screening new candidates. Data points created by using the past data can help you choose the exact skills, education and experience that matter the most to the organization.
3. Predicting Gaps in Recruitment– What if HRs can also predict that there would be gaps in the sourcing and the organization would require filling (a) vacant potion(s). HR data analytics can predict potential openings in an organization so that unnecessary scrambling to fill vacant a position can be avoided.
4. Identifying hiring obstructions – Big data analytics also helps the HR department of a company to spot a segment in the hiring cycle where candidates are dropped out of the pipelines. The Data lets you easily figure why it happens and then improvements can be made so faults can be corrected.
5. Reducing time - The big difference an organization instantly notices between hiring big data analytics based hiring and conventional HR hiring is that the time-to-hire reduced to a great extent. The system helps easily tracking, filtering, and pre-screening application so that only the best of the candidates can remain in the final process of hiring.
6. Understanding measurable Data – Big data analytics provides the evidence-based information, which can effectively be tracked and measured to identify results.
Wrapping up…
So, this is how big data analytics can help organizations and recruiters speed up the talent acquisition process and rapidly fill the vacant positions. Big data & analytics can help the HR department of a company to learn from past trends and apply the accumulated data on the next hires. The data will also help recruiters review their hiring process and improving it as several places to make the hiring free of obstacles. Big data analytics can also predict when there would be the need for new hiring. It can also help you rapidly hire talents from the best ones, not from the crowds…
Let’s see how companies use big data analytics in talent in hiring in the future.
This article is written by Sofia Coppol is a digital marketing expert in Rapidsoft Technologies, a leading Big Data App Development Company which provides Software for Education, Automation, Construction and Finance across the global. He loves to write about latest mobile trends, mobile technologies, startups and enterprises.
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