Historically, recruiting has been primarily dependent upon the instincts of the employer. Whether he or she felt a particular candidate was fit for a given position was based primarily on the resume, indicating the candidate’s previous experience, qualifications, and job history.
Today, it is widely accepted that organizations which base decisions on data consistently outperform organizations that don’t. Decisions that are based on data are usually more consistent, less risky, and often lead to more desirable outcomes.
A study conducted by the MIT Sloan School of Management indicated that companies that are mostly data-driven had four percent higher productivity rates and six percent higher profits
So why hasn’t this principle become widely accepted in the recruiting process?
The data your organization needs to make more informed decisions already exists. Businesses collect a ton of data on their past and present employees, along with their successes within the company. The trick is bringing it all together and finding the right analytical tools to transform the data into useful insights.
Predictive analytics, a technology backed by machine learning, allows organizations to use their own data, as well as data from outside and third-party sources, in their decision-making process. Recruiting professionals can now use the power of this data to make predictions about candidates and drive efficiencies throughout the entire talent-acquisition process.
What is Predictive Analytics?
Predictive analytics is a type of data analysis that uses data to find patterns and generates models to predict future performance. Predictive analytics can’t tell you exactly what will happen, but it shows what is likely to happen based on past trends. It’s as close as organizations can get to predicting the future.
What if you had access to forward-looking insight on your current workforce that could help you take early action to find top talent that also fits the needs of your organization? As Aditya Narayan Mishra from CIEL HR Services states:
“Organizations have a huge amount of data about their employees: their personal details, education, family background and so on. They also have data about employees’ performance and behaviors. Hence, they can correlate all these three dimensions to determine the typical profile of an employee who is likely to be successful with them. That’s the power of predictive analytics!”
Tech-savvy HR tools, like human capital management systems, have begun to incorporate predictive analytics into their offerings, enabling HR teams to utilize this data-fueled tactic in their talent recruiting strategies. Experts estimate that predictive analytics will be adopted among a majority of firms across the globe for hiring and managing of job applicants. According to the Deloitte Human Capital Trends report, 38 percent of companies use AI, and 62 percent expect to do so by the end of this year.
For employers, this results in decreased time to hire and increased quality of hire. For candidates, it builds a better hiring experience, leaving a positive impression that will factor into their offer acceptance decision.
Here are three ways predictive analytics can benefit your talent acquisition strategy:
1. Improve the talent quality
Using predictive analytics helps recruiters link employer behavior, activities, traits, and performance to desired business outcomes. Many organizations that utilize a predictive model customize their strategy by using attribute and performance data collected from the company’s top performers. From this, they can create a profile that represents an “ideal match.”
When candidates first enter the recruiting process, they create their own profile through assessments that create a psychological or emotional profile, score leadership and collaboration skills, and/or determine a degree of fit within the company culture. Predictive analytics can then compare the two to determine a best-fit candidate.
2. Create a more efficient recruitment funnel
In addition to improving the quality of hires, predictive analytics can be used to improve efficiencies in the recruitment funnel. The recruitment funnel is all of the steps between when a candidate applies for a position and when the candidate is hired. Predictive analytics can analyze resumes and applications to help sift through a large pool of candidates, or as Sarah Brennan, owner of Accelir, an HR technology consulting firm, calls it, “candidate shortlisting.” She says:
“This technology will take a look at your applicants and narrow down or prioritize them based on your past candidates that have made it onto your shortlist. It utilizes your previous decisions to determine a more favorable outcome in future decisions.”
3. Facilitate a better candidate experience
According to Talent Board’s Candidate Experience Research Report, many recruiters are still failing to provide a friendly and straightforward candidate experience. Candidates included in the report cited some of their largest reasons for withdrawing themselves from a recruiting process as: the process took too long, job description difference at interview, company culture not a fit, and poor communication with the hiring manager.
Using predictive analytics can help identify stages of the recruitment funnel that can be streamlined to improve the candidate experience. Determining how many applicants are at each stage of the recruiting pipeline and how long each stage is taking helps discover where applicants are stagnating in the recruiting pipeline.
Keeping things moving prevents good candidates from exiting the recruiting funnel prematurely and can leave a good impression with your top choice.