The process of hiring a suitable candidate is arduous. A recruiter has to flip through thousands of resumes to shortlist the best ones. With manual screening, the process becomes cumbersome, error-prone, and time-consuming. For this reason, having a recruitment analytics system in place can save you a lot of headache as an employer.
Recruitment-as a process is data-driven. The use of data and effective analytical processes can be powerful tools for a recruiter. It not only saves precious time in screening the resumes but also aid in quicker and better decision-making. The insights generated can significantly help human resources (HR) to gauge how successful an employee would be in an organization.
In this article, we list you the benefits of embracing data analytics in the talent acquisition and retention process.
Candidates' data can be tabulated into various parameters such as years of experience, age, qualification, etc. This data can be consolidated and ranked based on the need of the profile. Recruiters can also blend candidate's public data from social media platforms to add value to their profiles. This would yield better returns in the form of right hires which can improve the overall quality of the organization. However, recruiters need to keep in mind that overpopulating the date with unnecessary attributes might complicate the selection process.
Once the data is collected, it needs to be cleaned to feed it to different models. This is the most important step where a small error might skew the overall result. A lot of tools have advanced options to slice a large volume of data. The incidents of resumes with exaggerated facts and false statements are increasing every day. By identifying such profiles at this step, recruiters would be able to select right candidates for the profiles they are searching for.
B using analytics, recruiters can determine whether new recruits meet expected performance levels to contribute to the success of the organization. With parameters like candidates' achievements, stints at previous organizations, employers would get a clear indication of whom to hire for the job. Predictive modeling help employers to match the right candidate to the right job by identifying the traits that distinguish high performers. Potential candidates can be analyzed against a list of predictors from the current employee data to know if they would accept the offer.
Candidate records often go untouched once they apply for the role or after the job posting is closed. Analytics allows organizations to re-engage a targeted group of candidates to determine their interest level for other available position in the organization. It can also help to reflect new positions, work experiences or skills that might have acquired by the candidates since the last time they were engaged.
Machine learning can be used to build models to know the expected employee attrition rate in the coming time. It uses parameter such as age, income, satisfaction level, years at the company and other important factors to know how many employees are on a lookout for a change. This analysis can be used to take preventive measures and retain valuable employees in the organization.
Analytics can help recruiters find a broader range of candidates they would not find using traditional search methods. It can help them find the best cost per recruit, and also optimize their job postings response. This enables organizations to achieve better responses to their jobs postings based on different factors including duration, location, occupation, and industry.
Predictive analytics can be used to analyze the future job market based on historical demand, market growth, and current economic situation. This would help organizations to plan and allocate budget and workforce in the times ahead. It would further help businesses remain flexible and realign with changing needs.
Analytics promises an exciting opportunity to revolutionize the current hiring and retention process while securing the right candidates and improving overall company growth. A survey by MIT and IBM reported that organizations with the high level of analytics had 8% higher sales growth, 24% higher operating income and 58% higher sales per employee.
Analytics allows for enhanced processes that improve human aptitude and efficiency. People are vital to the success of any organization. With the right use of analytics, organizations would be able to attract right competencies, manage talent, utilize capacity, and retain employees for long-term success.
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