Historical data can be an authoritative source of intel for a company looking to make smarter and faster decisions. When efficiencies are possible, it’s best to use the tools available to achieve them. Today’s recruiters need a more efficient workflow, which is driving the advancements being made in hiring tools, including the introduction of predictive analytics. In recent years, predictive analytics have become an essential tool for any recruiter looking to acquire top talent.
Defining Predictive Analytics
Predictive analytics (PA) is the use of historical data to make better decisions for the future using artificial intelligence (AI) and machine learning (ML). The information used in this process can be sourced from internal databases and statistical algorithms accessed via AI’s automated processes. Though PA has been around for decades, it’s use has become more prevalent in recent years as more organizations rely on its proven capabilities. This recent adoption is mainly due to the advancement in technologies that make data collection and analysis easier.
Predictive Analytics in Recruiting
Through this adoption and reliance, many companies have implemented PA into their recruitment strategies. Once a predictive cycle of collecting and analyzing data is defined, it becomes an easily repeatable process. From that process, companies can use it to assist recruiters with their jobs well into the future.
This new-aged method of thinking is changing the game for recruiters by assisting them in hiring top-tier talent much faster. According to Ideal, using PA in the recruitment process can save a company upwards of 23 hours in productivity a week.
By using predictive analytics as a recruitment tool, companies will have a higher chance of standing out in today’s competitive hiring environment. An increase in the reliance on data for a human resources department can mean the difference between intuition-based decisions and decisions backed by facts.
With the data a company has acquired over the years from employees, they are better able to identify the skills, background and personality traits they desire most in a candidate. Once they’ve identified these qualities, they can input that information into third-party tools such as applicant tracking systems and job boards. From there, these systems can automatically sift through applications to present recruiters with candidates who are the best fit for the position. These candidates are then moved to the top of the list. This advanced process helps improve the overall quality of a company’s initial screening process.
Some companies are even beginning to implement AI systems with more advanced capabilities to screen potential candidates. One of the more unique pieces of emerging technology in this field is an AI face-scanning system. This fast scanning system assesses candidates by seeing how well they answer a set of questions that the machine asks them. The ideal candidate will best match the answers, personality and body language that the company wishes to track against. From this machine, an incredible source of data can be created and used in all future hiring decisions.
After establishing top candidates, a cloud-based talent management software can assist with keeping these prospective employees and their data well-organized. This program will help ensure every step of the candidate-to-hire process will operate smoothly and efficiently throughout all stages.
Sourcing for a position that needs an immediate turnaround can be a stressful process for any recruiter. Though finding the right applicants is a top priority during these times, sourcing can often take a great deal of time. Using predictive analytics can lead to smarter sourcing, reducing time spent manually sifting through potential candidates.
With predictive analytics, a recruiting team can eliminate any third-party sourcing methods previously deemed a waste of time. Being selective with this process allows the team to decide and focus on those job sites, keywords and other factors of posting a position that has historically brought the best candidates to the company.
Speed of Hiring
Predictive analytics have also been proven to significantly increase the speed of hiring by cutting out inefficiencies in processes. Knowing what current statistics show, you can see the timeline of past decisions and where you may be able to reduce time in the future. Improving the speed of hiring can be invaluable in cases where employee scarcity exists.
Analyzing past recruitment data is a significant undertaking, particularly for large businesses with several positions to fill. However, as the industry continues to rely more heavily on data as a recruitment tool, more intelligent technology is beginning to emerge to assist recruiters with this task.