A professional writer and passionate blogger, Sampurna has been lending her expertise to the online world by penning articles, guest posts and blogs on career, business and employment for a quite some time now. She also an avid reader; loves travelling and photography.

As the world progresses and technology advances, our lives change rapidly with each passing day. The domain of recruitment is no exception. Today, the overall process of hiring and recruitment has undergone substantial changes especially with technology foraying in.

Gone are the days when hiring and recruiting were largely dependent on the gut feelings of employers and they fell back on the years of experience that a candidate has. Today, analytics plays a significant role in the overall process of recruitment and has substantially redefined the practice of hiring. Let’s explore predictive analytics in this purview.

What is Predictive Analytics?

The branch of advanced analytics used to make extrapolations about the unknown future events is referred to as ‘predictive analytics’. In this case, it is about recruiters predicting for probable candidates for a vacant position. Predictive analytics implements many techniques including data mining, statistics modelling, machine learning and artificial intelligence to scrutinize existing data and make predictions about the forthcoming.

Predictive analytics in recruitment allows organizations to become proactive, advancing, anticipating outcomes and behaviors based on actual data rather than falling back on a notion of assumptions.

Predictive Analytics in Recruitment

Essentially founded on human capital-based statistics, predictive analytics is becoming more and more appealing to the HR departments across the globe. It is permitting HR branches to be more tactical in predicting about following resources and also possessing the right skills for various teams a few years down the line. According to a Daily, The Globe and Mail, “Companies investing in predictive data analytics use statistical models to identify trends and develop short-and long-term strategies for hiring, retaining and developing talent”.

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Predictive analytics in recruitment is growing rapidly in the realm of HR these days, and this increased attention is due to the following reasons:

  • The volume of data that can be consolidated online from social media posts to purchases.
  • An increasing reach of workforce analytics software and technologies that are becoming more accessible and available.
  • The capability of companies to generate algorithms from GDP, unemployment rate, and growth, turnover rate, and other workforce trends to predict their future needs for human resources.
  • Companies are becoming more proactive in their process of hiring.
  • To understand how to engage and retain employees for a long time

Benefits of Predictive Analytics in Recruitment

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The effectiveness of predictive analytics is pretty much evident, right from the pre-hiring process. It enables HR and hiring managers to make a much better recruitment that would ensure business benefits in the long run. Three main ways in which predictive analytics assist in the pre-hiring process is explained below:

1. Improves quality of hiring process

The first benefit provided by predictive analytics is it improves the quality of recruitment. By combining the recruitment process to production performance, engagement survey information, attrition data, and other data from the employee lifecycle, prototypes can be generated that will predict the potential future performance of a candidate. While substantial gains may be possible, constant adjustments to the hiring model will lead to marginal improvements in the overall hiring process. Hiring managers should also ensure that their hiring models have reliable processes and data. Some examples include engagement survey data, recruiting sources, turnover data, pre-employment assessment results, interview results and performance results.

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2. Makes sourcing more effective and efficient

Well, sourcing the right candidate for an open position is something that recruiters grapple for days together. It is where predictive analytics come to the rescue. Proper implementation of predictive analytics in recruitment, enables managers to optimise their recruitment marketing strategies and eliminate poor sources. In addition to this, the same method can be applied to evaluate in-house recruiters, job boards, third-party recruiting firms, and other sources.

3. Enhances the speed of hiring

The final benefit of predictive analytics is, it can substantially improve the rate of hiring. As the hiring model is developed, the understanding as to which candidates are the best for the company also improves essentially. The organization then will be able to deploy tools that will serve as leading indicators of potential job performance. Once a potential candidate hits on the hiring radar and fits your job models, recruiters will be able to move quickly, connect with them and eventually take things forward. Because of the confidence on the hiring model, recruiters will be able to focus on candidates who are apt for the business.

Of late, several organizations have implemented predictive analytics and reportedly performing better in the realm of recruiting and even retaining candidates. Within the domain of talent management, Google has excelled by implementing predictive analytics in recruitment, in leadership and even in retention. Other organizations that have progressed with the implementation of predictive analytics is Cisco and Sprint.

Going forward, it is estimated that predictive analytics will be adopted by most organizations globally for both, hiring external and internal candidates. Given the number of tools available in the market, it is somewhat evident that predictive analytics has become much more than just a buzzword. Shortly, every organization must leverage the power of predictive analytics in recruitment to be able to make the best hires and ensure that businesses work out to their fullest potential.

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