According to The New York Times, a growing number of entrepreneurs are applying big data to human resources and the search for talent, creating a field called workforce science.
Big data is transforming the information world at an alarming rate. It’s no surprise that the data being collected, sliced, sorted, and sold is being used to help businesses make better hiring decisions. The data part of the equation is collecting all of the digital imprints that a worker or job seeker has left in the course of web browsing, emailing, instant messaging, or posting on social media. The “science” part evaluating and measuring the data is the tricky part. Silicon Valley start-ups are developing analytics and algorithms to put this data to work for recruiters and employers.
Using data in human resources is not a totally new concept. Human resources personnel have begun to use more tools to analyze employee performance, the effect of raises on attrition, and more. A study by Deloitte found that 60% of companies are investing in big data in some form. But its uses are varied, and implementing change based on what the data shows can be a challenge. In another survey by talent analytics software company SHL, 77% of HR professionals surveyed are unable to tell how their workforce potential is affecting the bottom line. Only 44% use objective data regarding employees’ performance to guide business decisions.
How Big Data aids Recruiting Procedures?
Big data, or people analytics, as it is known when applied to recruiting, is the monumental volume of data that recruiters have access to and analyze, to help them with their quest to find the ideal employee. Big data recruiting is more than merely screening resumes for keywords or social media data mining. It is a way to create a 360-degree picture of a candidate before they have even stepped foot in the building for their first interview.
Our entire lives now are pretty much played out online: all of our personal data is ready and available GDPR permitting for all and sundry to access, and it is a goldmine of information for recruiters to dig down into. In this day and age, a resume is just too one-dimensional. You want the complete picture of a candidate, warts and all, in order to assess them accordingly, and that is just what big data affords you. Sure, use the keywords of applicant tracking software to guide your search, but don’t let them define it. Look beyond the keyword and into semantic analytics: extract all the information from a candidate and then analyze the data. Because that is the point of big data – to analyze, understand and interpret it in order to give you a full a picture as possible about a candidate.
Big Data Helps in Finding the Best of the Resources
Sourcing via job boards requires sifting through a lot of data. This prevents you from being able to access an aggregate view of your job performance. But we are now at the point where AI recruiting tools can do the work for you and eliminate data silos, as they sift through information across whichever sites you prefer to bring you the right people, from the right places with the right credentials. The more information that’s out there, the more fuel there is to feed AI technologies in order to pinpoint the exact candidates you seek for open positions.
And the more big data there is, the more accurate AI-enabled algorithms can be. After the predictive algorithms are set and fine-tuned, data is the fuel that drives AI to update these algorithms for environmental factors such as supply/demand and job seasonality. The manual process is thus eliminated and you can focus your resources on other things. The best part is we are just beginning to see its potential. Your team can use AI tools to seek out the exact traits and skills you want in a hire-big data plus smart tech will yield big smart data that saves you time and money. For recruitment industries that will mean more effective, efficient and smarter recruiting.
Chances are, the next hire you will make is checking their mobile device, using a wireless network, or running social media software-right now. For you, that means constant streams of information you can use in order to find and hire the best candidates for your open positions. Over the past decade, companies have seized on big data analytics to create efficiencies across all industries. For recruiting, there’s still further to go; the rise of the internet led to the rise of job boards, while later social media and advanced tracking technology has led to not only reaching more candidates but also finding better, more reliable hires.
Big Data Creates Specific Ads to Attract the Passive Candidates
So how can you find those quality candidates using social media on their smartphones right now? They need to see and apply for your job opening-and you need to be able to find the resumes and get the attention of passive candidates who may not be actively searching for jobs. This is where AI technology combined with big data can be particularly helpful. Using the latest algorithms of Big Data, more than 199 billion data points have been analyzed across 5.4 billion individual historical job ad campaigns to determine the scientific formula and key attributes that predict job ad performance. What this means is predictive algorithms will use mass amounts of data to predict job performance across your ad campaigns.
While it is true that businesses have used data to creative predictive models for quite some time, only now are we seeing AI update these predictive models for environmental factors. Vast amounts of historical data allow us to make the best ad placement decisions using these AI controlled algorithms -which can then, in turn, create insights and recommendations for better ad performance.
So, for example, if you’re planning a new job ad campaign, big data analytics is key to figuring out which job ad vendors to use or which sources you want to use to consolidate your data while simultaneously figuring out which sites will perform and which will be an unnecessary dent in your recruitment budget.
Meanwhile, a business can use data, and the ability of AI to analyze that data, not only to create predictive models but also to try out different approaches and learn quickly what works and what doesn’t. While businesses always try to replicate successes and learn from failures, AI can help learn quicker and use predictive analytics to make every campaign successful.
What Kind of Data Recruiters collect with the help of Big Data?
It can be expensive and time-consuming trying to find those employees who will not only perform well but who will stay too. Because it is too restrictive and inflexible in its elimination approach. So much information is available about the potential candidates, from sources such as:
- Social media profiles like LinkedIn and G+
- Resume databases
- Performance reviews
- Business cards
- Political associations
- Online behavior, such as shopping and reading preferences
Data can be collected from many sources to provide information about a candidate’s prior experience, achievements, skills, warning signs, etc.
Some of the most common data that recruiters collect are:
- Data from resumes- Resumes remain vital in the recruitment process because they are the stepping stone from which big data can be used to verify the information they contain.
- You could even uncover some gems that would normally be filtered out, people who might not necessarily have the paper qualifications that you are looking for but have the skills and expertise to do the job and outstrip anyone with an actual qualification at 100 yards.
- Data from pre-employment assessments – Pre-employment tests are as old as hiring itself. Usually, applicants are invited to take a skills test, a personality test, or both. The skills tests are used to corroborate the skills listed on the resume, but also can be used to test those not listed, such as soft skills or situational judgment. The personality tests are also used to assess a candidate’s fit with the firm’s culture. Based on the scores, a recruiter can see whether a candidate matches the requirements for the vacancy.
- Data from social media profiles – Special emphasis can be placed on those candidates who demonstrate their expertise on social media channels like Facebook, Twitter, LinkedIn, even Quora, by sharing advice, thought leadership, and interesting industry insights.
Besides all this, data can also be collected and analyzed to keep up with, and ahead of, job market trends.
Big data recruiting can help you recognize patterns and identify great candidates faster and in a more cost-efficient way than you currently have. However, you can’t solely rely on the information it provides to give you all the answers you’re looking for, it can only guide you. Recruitment experts still need to correctly interpret the results to make the best decision. The full potential of big data recruiting can be unlocked with people understanding its principles. Despite the risks, algorithm-driven approaches to recruiting are here to stay and the advancement of big data has expedited the rate of development in machine learning. (Machine learning is the design and study of learning algorithms that, essentially, help a computer process and understand data better).
Machine learning will be the next evolution of recruitment as technology continues to evolve, creating more accurate algorithm-based recruitment tools. But for now, while big data drives hiring decision making, it shouldn’t be done without human engagement.
cFIRST Think Tank is the team that researches and produces content for cFirst. This team comprises of seasoned content and digital design professionals and background screening industry veterans. Together we produce insightful blogs, infographics and reports meant for HR and background screening professionals.