#1 in the series
AI, RECRUITING, SELECTION AND TRIANGLES
John Wentworth, the founder of Wentworth Recruiting, and I were having lunch at Beach City Grill. Obviously a regular at this local San Pedro establishment, John didn’t even pick up the menu. While I was focused on what would best feed my midday growling stomach, he was having one of his nutty professor days. “It’s all about two triangles,” he muttered.
“What are you talking about?” I asked, still thinking about my lunch.
“Oh, sorry,” he said. “I’ve been thinking about how recruiting automation has missed the mark.”
He started scribbling on a piece of paper. “Look at this. Most of what’s automated with applicant tracking systems is administrative: when did the candidate apply, contact info, first screening, salary expectations, etc. That’s all important for managing the function and for compliance, but none of it has to do with delivering the very best possible candidates to the hiring manager. The actions that deliver the best possible candidates are either not automated or automated inadequately. They got lost in the rush to make the recruiters’ lives easier.
“They are missing the most important part of recruiting.”
“Which is delivering the very best candidates possible?” I asked.
“Yes. For many recruiters, their secret goal is to put butts in the seats, not to deliver the very best candidates possible. It’s how they get measured, sadly. It’s how they get raises.”
“The employment of a sub-par workforce starts with the recruiter who lets adequate but marginal candidates in the front door and lets them go forward to the hiring manager.”
“I get that,” I said. “Not knowing how to select the best candidates, hiring managers pick the candidates they like, or the best of what’s provided to them even if what's provided to them is lousy.”
“It’s on the recruiters,” John said again, repeating himself. He was getting wound up. “It’s their obligation to put forward only the best possible candidates so the hiring manager can hire any of the pool and still get a great employee. Recruiters rarely can do it on their own. They need help. Artificial Intelligence is supposed to save them. But Artificial Intelligence can only help so much.”
“It shows the limits of Artificial Intelligence. AI does a great job of hitting the problem with a 2x4, but good selection needs a scalpel, not a big piece of wood.”
“Help me understand.”
“AI can look at information and patterns, but only makes sense of some patterns, not others. Let’s say that AI sees that a candidate had the right titles and that the titles have grown over the years through promotions. That means one thing if her employers were all about the same size as your company is. She probably has the skills for your job. However, it means something else if her early career employers were bigger than your company and had gotten smaller than your company over the years. Has she been out of her depth on her jobs, needing to go to successively smaller companies with less complex jobs? Is she too light for your open job? Probably. Can AI recognize that? Probably not today. Maybe in the future when it can tap into a directory of every company in the world and is told to compare the size of the employer to the companies on the resume, and how to interpret those data.
Here’s another example; what if your candidate inherited some money and was only interested in working for a few more years, but had not mentioned that? Do you think AI will be able to pick that up? A personality instrument that measured ambition could give you a clue, but AI probably would not. Do you think the candidate’s ‘I want to cruise to retirement’ attitude would be dysfunctional in an aggressive, get-it-done employer? Probably. Would it lead to termination? Probably. A really good recruiter could catch that. I’m not sure how a machine would.”
“Wow. That’s a dismal picture,” I responded glumly.
“Not so dismal. You can figure out your job’s key success factors, and to build a measurement scales for them. We need to find behaviors that correlates with how much someone wants challenge, for instance, interview for that behavior and rate it on a 1-5 scale. We need to know how much the job needs and then how much the candidate has and then compare them on the scale.”
“What would automation do?”
“Running these types of comparisons creates a lot of data that can be difficult to understand and can add to the ‘fog of recruiting.’ Automation can make complex data into simple and vivid displays that show how candidates compare to the requirements and to each other. Automation helps to lift the fog of recruiting, making the weak and strong candidates obvious.”
“You talked before about AI hitting the problem with a 2x4 vs. a scalpel. Is this the scalpel part?”
“Yes it is,” John said.
“And no machine does this,” I said, not sure if I was asking a question or making a statement.
“They can but most just record, count and report or recognize gross patterns or look or key words. But I just ran into one that does add real value. It expands your pool of good candidates by automating the employee referral process. This is valuable because it enriches the supply of qualified candidates. It reduces the dependence on recruiters managing the employee referral program. Recruiters forget stuff; the machine does not. It sets up innovative and personalized rewards and lets the employee pick; the recruiter does not need to manage that process. It finds potential candidates through employees voluntarily sharing access to their social media, discovers the candidates’ contact information, invites the employee to select and invite candidates to apply, and then processes the candidates throughout their journey. All this frees the recruiter up to talk to people, to do the scalpel part. It’s the best use of automation and AI I’ve seen in the talent space. It’s called Boon.”
We were finished with lunch. And there was a silence. I said, “That was a lot.”
“Sorry,” John said, chuckling. And then he pulled out his usual quiz of what was just said to see if I was listening. “Tell me what you think the point is?”
“I think the point is that if you want to hire the very best people available to you, you can’t cut corners. There is no silver bullet. Automation can help, but finding the best employees, selling them on your job and selecting the right ones is a ‘contact sport’ and takes skilled people applying themselves in a disciplined way. Machines can’t do that yet.”
“All true. Once we start acting like hiring the very best people possible is the real goal, the methodologies will emerge and the automation will follow. They actually exist now. They just have not become widespread yet.”
“Who did you say was buying lunch?” he asked with a smile.
I reached for my credit card.
John Wentworth has been in HR since 1972, a recruiter since 1979 and run his own company since 1984. John is a Vietnam War combat veteran and The Wentworth Company is a State of California Certified Small Business & DVBE. The Wentworth Company has helped 550+ employers hire over 20,000 new employees. The firm consults regarding talent, designs talent systems and offers high volume, RPO and single search services. 88% of their hires exceed the hiring manager's’ definition of qualified. He was interviewed by an imaginary companion.