5 Massive Ways That Big Data Changes Talent Acquisition

5 Massive Ways That Big Data Changes Talent Acquisition

Can Big Data bring BIG changes in the recruitment sector? Let's find out in this article!

There's no doubt that the success of any company is directly linked to its people. Over 71% of CEOs think so, according to a report from Harvard Business Review. More precisely, the report has found that CEOs view human capital as the top factor for the sustainable economic value of their business. What's more, 43% of them agreed that investing in their employees is a top priority. 

So, it's no wonder, then, that employers and recruiters are continuously working on improving their strategies of finding, hiring, and retaining top talent. This is where Big Data shines! 

Big Data can do more than just tell you about your current workforce's performance. It can also use predictive analytics to help your HR specialist build and manage a pipeline of top talented candidates. If you think about it, hiring managers have always relied on data to make hiring decisions, but, fast-forward to 2022, they can use Big Data to make better decisions. 

This article explores the five massive ways in which Big Data is changing talent acquisition. 

1. Predictive analytics leads to better decisions 

You can guess that a candidate is "the one." But what if you can predict that you're interviewing the right? This would be a lot more certain, right? Well, that's the main difference between guesses and predictions. 

Sure, instincts are necessary and helpful most of the time. Yet, they don't compare to predictions of how a decision will play out. This is where Big Data brings this difference.

Predictive analytics make the data you have actionable, allowing you to make smarter decisions about anything related to attracting top talent to your company, including sourcing and hiring. Besides that, it can also help you predict when or whether an employee might leave you for another job. 

Latest technological advancements allow companies to extract meaningful and valuable data that offers insights into the job at hand, no matter the industry or the nature of the job. For example, if you're planning to spend some money on job ads, predictive data will use market data and data from your own previous experiences to give you a clear idea of how your ad will perform. This significantly improves your ability to get the most out of your recruiting budget by making better and more informed decisions, resulting in fewer mistakes. 

2.Big Data improves the quality of new hires 

Think about all costs associated with getting a new employee on board. There are costs for job ads, hiring services, training, and so on. Now, imagine that your company pays all that money only to realize that you've made a bad hire that won't work out the way you've hoped it would. You don't want to make this hiring mistake, right? Thankfully, big data can help you avoid it. 

One way in which big data helps you hire quality candidates is by allowing you to find the ideal person much easier. With data from online databases and publicly available information, your hiring managers can identify the right people more accurately and efficiently. Big data can be sorted using certain key performance metrics, allowing your company to identify those candidates who best suit your top requirements. 

Say, for example, you are looking for the ideal candidate with a certain skill set, from soft skills like communication to teamwork to hard skills like technical know-how. Big data and the right metrics can help you identify only those candidates who possess all these things. This not only makes the job of hiring managers easier in terms of screening but also minimizes your risk of hiring the wrong person. 

3. The hiring process is streamlined 

Besides allowing companies to make smarter recruitment decisions and avoid mistakes that can cost them, Big Data also helps streamline the entire hiring process. 

Not only that hiring managers can identify and screen candidates more easily, but they can also make use of all that data in the future. With the emergence of Big data in the HR sector, gathering and examining all the data collected before, during, and after the process of hiring has become a lot easier. 

In addition to this, recruiting managers can also monitor and track the efficiency of recruitment efforts in a more accurate manner. This also allows HR teams to identify new and highly efficient recruitment strategies that attract top-tier candidates. 

4. Over-and under-hiring are prevented 

Hiring too many employees or too little are not good news for companies. While hiring too many candidates can create additional costs, hiring fewer people than needed can make the company's overall productivity take a significant hit. So, a balance must be found here. Here, again, Big Data can help. 

Using Big Data, HR experts and recruiters can develop data-driven hiring plans that are up-to-date with the company's needs and forecasts based on different metrics related to recruitment, such as attrition, lateral movement, promotions, and the quality of the hires. Offering accurate predictions, Big data helps remove human errors that may lead to having too many employees or too few people. 

5. HR processes automation 

As the experts from Timesheet Portal explain, "Talent acquisition is a very long and complex process- from the moment you craft a job ad and post it to the moment you get to the onboarding step." So, it's clear that no HR professional would mind handing over some of the most mundane HR management tasks to someone or something that doesn't mind doing the job and also does it extremely well. 

This is also where process automation and machine learning make a wonderful team. Instead of wasting a lot of time and energy to update employee files, send emails, or post and respond on social media, technology does it for you. Some HR processes that can be automated include sending emails to job candidates, generating quests for candidate screenings, time tracking, onboarding, offboarding, and even vacation and leave requests. 

Related Stories

No stories found.
Analytics Insight