Sitting in a job you don’t like is a problem. It’s made even worse when you don’t have the skill set you need to excel in your position, and it becomes a disaster when you realize you don’t fit in to the job or the company at all. By this point, you might be looking for a way out, even if you’re only a couple months into the position. If you need to stick it out but your quality of work is suffering, your boss might need to make a decision neither of you wants and show you the door.
Luckily, this isn’t the situation for many employees and the companies they work for. But it is a reality for some, and it’s a problem that Greg Moran, founder and CEO of Chequed.com, looks to solve with data analysis. We’ve written before about how big data can predict when an employee might leave their job, which gives companies advance notice for filling that position, or taking steps to retain that employee if they’re of great value. But Moran’s focus is on the other side of that process, when companies are trying to hire the best person for the job. Chequed.com’s mission is to aim for “no bad hires.” It might seem like a pie-in-the-sky sort of ideal, but Moran is confident that it’s an attainable goal with the help of predictive analytics.
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 affect of raises on attrition, and more. Josh Bersin, a contributor to Forbes and founder of human resources consulting group Bersin by Deloitte, cites a Deloitte study that found 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. That’s the area that Moran says can grow, and chequed.com seeks to inform the hiring process from the very beginning.
The talent analytics company provides a variety of data-based tools for HR managers to use at every step of the hiring process. The software was developed based on behavioral science and backed by research through The State University of New York and The University at Albany. The goal of the research was to study how pre-employment assessments and selections are made, and see how they could be made more predictive of employee performance and fit at a particular company, Moran told The Cheat Sheet.
With the founding of chequed.com in 2008, and full commercialization in 2011, the company now offers a full suite of products that give input for best practices in job application questions, interview services, and reference checking. When a company signs up to use Chequed’s resources, it can choose from 900 pre-built job profiles that can be customized for that firm’s culture, or it can choose to build completely custom job profiles that detail job competencies required and the personality traits that will help a future employee succeed. For example, one company looking to fill a sales position might need an aggressive person to bring in new business. At another company, an aggressive personality might not work as well.
The reason for that profile, Moran said, is that it highlights the core values for that position, and it helps to keep those needs at the forefront of the entire hiring process. Application questions are centered on finding the right candidates for that role, interview questions expand on them, and reference checks follow up to see if those necessary traits and skills are already evident in candidates. “It brings a huge amount of consistency at every step in the screening process,” Moran said. “One step is really validating the previous, and the picture gets clearer and clearer as the candidate goes through the process.”
Chequed’s software drives the process, generating questions for HR managers to ask during the interview process and which ones to include in the application. Instead of making reference check calls, references answer a short email survey about the candidates. One of the huge differences about the software is that it asks reference questions that have more to do with job skills and whether they would be a good fit, instead of “Does (Candidate A) get along with people?”
Those typical sorts of questions don’t add any valuable information, because they have a so-called “correct” answer, Moran said. “Of course you’re not going to say ‘no’ unless you want to throw someone under the bus,” he explained. Moran worked in hiring for years, and knows that previous employers are reluctant to give the non-expected answer. “I can literally remember the bad reference checks because there were so few of them,” he said. Instead, Chequed’s questions ask references to evaluate levels of competency. It’s less about right and wrong or if the candidate is good or bad. The information is a bit more objective, which allows references to provide candid information, Moran said.
Using data in HR practices is becoming more frequent, Moran said. Just as people likely won’t stop using Kayak for flights and instead start calling their travel agent again, Moran predicts there’s no going back in terms of data’s role in the workplace. “I think what we’re seeing is technology taking a really strong position in hiring. I just don’t see that turning around,” he said.
Chequed.com works with clients including SUBWAY Restaurants, The Walt Disney Company, Esurance, Hallmark, Aspen Dental, and more. “We work with some of the top brands in the world,” Moran said. “I think the common denominator among our clients is these are all companies that take talent really seriously.”
Moran obviously believes that data can help HR managers make better-informed decisions about who the best candidates for a job might be. But he’s also aware that data will never be able to answer every question. “There is no silver bullet in hiring. None,” Moran said. Chequed’s technology doesn’t include “cut scores” – the pass or fail sort of numbers that some application testing methods might use. Instead, the technology helps to prioritize which candidates might fill the position in the best possible way. But at the end of the day, “there’s just a gut instinct that you have to still listen to,” he said. “If you make this stuff so data-driven that you take the human story out of it, you do an awful disservice to the company and the candidate,” Moran explained. In other words, if there’s a candidate who didn’t score quite as well as another, but your gut says they’re the better hire, you now have the option to weigh that with data. The analytics are merely a tool, even if its a rather helpful and sophisticated one.
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