In our new study "Artificial Intelligence for Recruiting Success," we discussed ways that new technology can save us time and effort while attracting a better pool of job candidates. In this article, we'll explore the benefits and uses of predictive analytics.
Basically, predictive analytics is the process of looking at past data in order to determine what will happen in the future. Machine learning automates much of this activity, freeing up recruiting professionals for higher level work of in-person interviews, decision making, and so on.
Programmed with your data on production performance and behaviors, attrition, employee life cycle, engagement surveys and any other metrics you choose, predictive analytics software can be "trained" to look for your ideal employee. It can scan all the available candidate sources, as well as discovering overlooked talent in your existing applicant database.
The longer you use it, the better it works, as it learns from its own historic data of which candidates hired, resulted in the best productivity and retention. That information is incorporated in its screening of future candidates.
Optimizing Job Postings
Using factors such as occupation, industry, and location, along with your company's requirements, predictive analytics can help you create job advertisements that precisely target your desired talent pool. The result is a greater response from desirable candidates and fewer responses from those who aren't qualified for the position.
The same software can be used to identify the best media for reaching your target audience and eliminate those with poor ROI. For example, you might allocate your recruiting budget primarily to online job boards, third-party recruiting firms, professional networks or social media, depending on what type of position you're hiring for.
Because they are purely data-driven, these automated tools look in places you may not have thought of, helping to eliminate unconscious biases and allow for an even playing field. As a result, they draw on a wider talent pool, increasing the effectiveness of your hiring process.
Screening and Ranking Resumes
A task that used to take HR many hours to do manually is done in minutes by predictive analytics. You'll be presented with a list of the candidates most likely to be worth taking to the next stage in the recruitment funnel.
Reducing the Time to Hire
The fact that it takes an average of 27 days to acquire a new hire is a major pain point for both employers and job seekers. One of the best aspects of incorporating predictive analytics in your hiring model is the ability to rapidly select the best candidates for the job.
Predictive Analytics Providers
A number of solutions specifically tailored to HR's needs are available. Here's a selection of platforms that integrate with HR's existing software.
It's important to remember that — as with every other implementation of data analysis — the quality, security, and privacy of the data must be safeguarded. It might be best to phase in the new analytics, restricting the first steps to leveraging only the data you know is accurate. With time, though, you'll be able to reap the rewards of a more efficient and effective recruiting process.
Integrity Staffing Solutions is a full-service staffing agency and ranks in the top 2% of agencies across the country for quality service based on Clearly Rated’s Best of Staffing client survey. To learn more about Integrity or for help with your hiring needs, visit Integritystaffing.com or call 888.458.TEMP.
"Analytics in Recruitment" by Neelie Verlinden, Digital HR Tech
"The Power of Predictive Analytics in Staffing" by Jean-Paul Isson, Monster Worldwide
"3 Ways Predictive Analytics is Changing Recruitment Practices" by Chiradeep BasuMallick, HR Technologist
"Recruitment Statistics – Challenges, Trends And Insights For Better Hiring" by Sonika Sharma, empxtrack.com
"People Analytics: Building a Data-Driven HR Function" by Perla Sierra, HR Technologist