How to Use Analytics to Improve Hiring Decisions

Recruitment has come a long way since the times when companies would make job advertisements in newspapers. In today’s world, we’ve not stopped seeing many businesses turning to technology to ensure the process is further optimized. Actually, if statistics are anything to go by, Yahoo Finance projected that the global digital recruitment market would reach $58 billion by 2032, growing at a CAGR of 6.4%.

In another place, a LinkedIn poll revealed that 77% of recruitment firms used analytics to organize their workforce. This trend has become common in Fortune 500 companies like Google and Cisco as they seek to minimize the chances of mishaps during talent acquisition. If you are intrigued by how tech and data analytics improve onboarding, this article is for you.

How Data has Become Increasingly Important in the Hiring Process

Everyone can agree that the proliferation of the Internet has worked wonders, not just in the recruitment industry but in other sectors as well. For instance, in the music industry, you can discover millions of songs conveniently using platforms like Spotify and Apple Music. At the same time, digital recruitment agencies have made it easy for companies to find top-cream talent who can drive revenue and company growth. Surprisingly, even startup businesses have benefited from this trend.

Now, amid this widespread internet adoption, it’s become easy to access enormous amounts of data that can offer crucial insights about prospects. A considerable amount of recruiters who use AI-powered candidate matching stated that using analytics can actually reduce the cost per hire by up to three times. By implementing sophisticated machine learning algorithms to crunch the enormous candidate data, recruiters are now using less time to hire while improving the quality of hires.

With predictive analytics, it’s now possible for human resource experts to offer even better experiences during the whole process. This can increase the possibility of a potential employee accepting the job offer – 76% of applicants believe that how a company values its employees will be seen by how it treats individuals during the hiring process. Undoubtedly, if you shorten the time you take to fill positions, you might experience better business outcomes.

The Benefits of Using Predictive Analytics in Hiring

Companies with a global appeal often receive thousands upon thousands of applications when they announce a vacancy. This is a major challenge, especially if you have to ensure that the hiring process isn’t flawed. But, with data analytics, you can scour large amounts of data from various sources, such as professional networks and job boards, to identify the most suited candidate.

This also comes in handy when you want to ensure that the candidate you’re hiring perfectly fits your company’s culture. You don’t just want to fill the vacant position with someone who has the needed skillset; the individual should also be able to add to the long-term success of your company. With predictive analytics, you can assess whether an individual’s culture aligns with your organization by assessing their online presence and communication style.

As we have already mentioned, with many people applying for jobs in different companies, ensuring no bias can sometimes be difficult. However, since predictive analytics are designed to assess applicants based on their merits, they can help reduce hiring bias. A good example is a system that ignores gender, age or race-related information to allow for a more equitable recruitment process. This is without mentioning that the system ought to be regularly trained to minimize the chances of unconscious bias creeping in.

What are some of The Best Practices for Applying Data-Driven Recruitment?

It’s difficult to remember the world in 2024 without analytics. And that means that if you are turning to recruitment analytics to make data-informed recruitment decisions, then you are headed in the right direction. But this will not require just any metrics – you have to choose the right metrics to ensure that you’re tracking candidates that perfectly align with your organisation’s unique values and objectives.

Another part of using recruitment analytics is to ensure that you know which data to collect and how to put it to work. As statistician Edward Tufte mentioned, statistics will only be boring if you have the wrong numbers. This is not only limited to having the right data but having as much of it to work with.

Your recruitment process will need improving as more data becomes available. And this is actually the whole idea of collecting candidate data – to better your recruitment process. If, for example, you discover that your candidate quality is low, you might consider rewriting your job postings to ensure that the job requirements are more clearly stated. Or, if your new hire turnover rate is high, consider implementing a more effective onboarding process.

From this presentation, you can agree that as more recruiters incorporate tech into their talent acquisition, the process will most likely yield better outcomes. Companies will be able to find candidates that are more aligned with their unique goals and objectives. Applicants will also be more confident that the process is less flawed, leading to more enjoyable recruitment procedures.