You might say that we are now in the third stage of our technological evolution. At least when it comes to finding and hiring employees.
The first stage was what you might call the “good old days.” Life was simpler. You drafted up a job description, posted an ad, accepted a pile of resumes, brought in some applicants for interviews, and eventually offered someone a job.
Then, about 20 years ago, the second stage began – and things got more complicated.
Job boards exploded. We started developing candidate profiles, entered resumes into applicant tracking software, and beefed up the selection process with multiple layers of interviews and job assessments. We looked for tools and tricks to save us time; to let technology shortlist a list of candidates so that we didn’t have to.
The third and latest incarnation of this evolution is happening right now – and it’s characterized by one very popular term: Big Data.
What exactly is Big Data and how can it work for you?
“In the past, the classic way was to work through informal networks to find employees or to use advertising. Big data has changed that,” says Matt Stevenson, a partner at global consulting firm Mercer.
Stevenson defines Big Data as any data source that can accessed and understood by computers. But possessing the data in machine-readable format isn’t enough. You need a way to transform that data into meaningful information. To quote Daniel Keys Moran, “You can have data without information, but you cannot have information without data.”
These days, big companies can use various sources of Big Data to improve their hiring process.
Some options are external. With LinkedIn, for example, recruiters can pay to have it “scrape” its database and return a list of potential candidates based on a number of criteria.
“But that’s only for a small part of the workforce,” Stevenson says. “The highly educated part.”
Meaning, if your mission is to find hundreds of skilled workers for a specific location, you’re going to need an entirely different set of data. “You can combine data sets, either publicly available, commercially available or proprietary,” he says.
For example: an employer could use Big Data to search by postal code and learn who works where, what the employment rate is, what they get paid, and other demographic information.
A strong believer in this particular bucket of Big Data is Jimmy Taylor, a former founding partner of Novotus, a recruitment process outsourcing firm in Austin (now called Orion Novotus).
In fact, this kind of info is one of the first things that Novotus looks at when beginning the recruitment process with a client. “What does the supply and demand look like in the specific market we are targeting?” Taylor asks. “How many candidates are active in the market we are considering and how many other companies are looking for the same talent?”
The answers to these questions are just the beginning of big data’s influence, but it can produce profound changes. “We had two clients who used our data to help select office locations where recruiting might be easier for the skill sets they needed.”
Meanwhile, Stevenson has also seen highly valuable data emerge from companies’ internal sources, too.
“Very sophisticated HR systems capture everything about an employee, which is a rich source of data for predictions,” he says. “[Data that] predicts people staying, leaving, getting promoted. It can be used at an individual level but also to predict what the workforce will look like over time.”
How it can make a big difference
Currently, one of the most valuable forms of big data comes from assessment testing. Of course, assessment tests are as old as hiring itself – maybe older. But the sheer number of completed tests we have access to, and the way we can manipulate the data they generate, has changed enormously.
Thanks to the internet and the ubiquity of digital devices, assessment tests can be completed online, from almost anywhere.
They can also be very sophisticated. You can create tests and implement them as cheaply for 10,000 candidates as you can for 100, but you can also make them highly complex – you can even give someone a full computer simulation of an oil refinery job, for example, rather than flying them to refinery itself.
“Because the data is machine readable, you can now perform tests on the data itself to understand what predicts what,” Stevenson says.
Google, for example, has discovered that a candidate’s educational pedigree, once thought to be a strong indicator of success is in fact, a very poor predictor.
Why you need to be careful with Big Data
Given the sheer amount of data that can now be amassed and processed, it’s tempting to cast a wide net. But this approach is risky – and may even carry legal ramifications.
“Some information sources may be off limits or subject to strict consumer protection laws,” warns Angela L. Preston, vice president of compliance and general counsel at Employee Screen IQ. She cites Spokeo, a popular big data aggregator, which was fined $800,000 by the FTC for selling false information to employers and recruiters for hiring purposes, which also violated consumer protection laws.
Employers can also open up discrimination claims when they use data sources that may have been targeting certain parts of the population and excluding others.
“Ethically and legally speaking, if you have no way of confirming the accuracy of the information, or if you think it might adversely impact a protected class, it should not be used,” says Preston. “Bigger is not necessarily better when it comes to hiring data.”
These legal and ethical hazards notwithstanding, big data is having a profound effect on the recruiting process and it that effect will only grow more pronounced over time.
“Recruiting is still in its infancy of using big data,” says Taylor. Which is good news for companies that are just beginning to look at leveraging it: there’s never been a better time to start.
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