June 17, 2019 – 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 that 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, this according to a new report by Cornerstone International Group.
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, said the search firm. “Businesses collect a ton of data on their past and present employees, along with their successes within the company,” said the new report. “The trick is bringing it all together and finding the right analytical tools to transform the data into useful insights.”
Cornerstone International Group
Cornerstone International Group provides executive search and leadership development services to global roster of clients. Both before (with psychometric assessment) and after (onboarding) its search process, the organization ensures the highest possible chance of success in filling talent needs, the firm said. Cornerstone has 66 experienced member firms in both developed and emerging markets worldwide.
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, said Cornerstone.
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 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, said the report.
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?
How Predictive Analytics Promotes Better Decision Making and Efficiency
CHROs are vital in helping to place the right people in leadership roles at their companies, but these days they also serve a critical strategic function. Those responsibilities seldom play out on a bigger corporate stage than at Johnson & Johnson, where Peter Fasolo serves as CHRO.
“Organizations have a huge amount of data about their employees: their personal details, education, family background and so on,” said Aditya Narayan Mishra, director and CEO of CIEL HR Services. “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,” the Cornerstone report said. “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,” said Cornerstone. “For candidates, it builds a better hiring experience, leaving a positive impression that will factor into their offer acceptance decision.”
Cornerstone presented three ways that 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 use 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,” the Cornerstone report said. “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.”
For Executive Search Firms, Analytics Can be a Game Changer
Big data is rewriting the script for how companies around the world do business. The market for big data and business analytics is expected to grow to $203 billion in the next three years, according to the International Data Corporation. It only makes sense that analytics should become an increasingly vital component of the executive search process.
“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,” she said. “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.
Contributed by Scott A. Scanlon, Editor-in-Chief; Dale M. Zupsansky, Managing Editor; Stephen Sawicki, Managing Editor; and Andrew W. Mitchell, Managing Editor – Hunt Scanlon Media