Our vision at Cadient Talent is to revolutionize the way the world makes hiring decisions.
Our goal is to make the hiring process as transparent as possible and consider all of the variables that are used in a hiring decision. That’s extremely complicated, if not impossible, if you have nothing but a human-based approach. The decision-making of a hiring manager is far more complex and less understood than those of a machine learning algorithm. So, we want to focus on the strength of simplicity in a machine learning algorithm; meaning we only want to look at variables and data that are pertinent to the hiring process — and exclude any data that are irrelevant to the job performance.
As a part of my series about “Big Ideas That Might Change The World In The Next Few Years” I had the pleasure of interviewing Jim Buchanan, CEO of Cadient Talent. Cadient Talent provides talent acquisition solutions focused on distributed hourly hiring. Cadient was formed in 2019 through a business unit carve-out from a large private software company. Prior to Cadient, Jim spent 15 years in executive management roles in the talent acquisition industry.
Jim co-founded Merlin Technologies, a human capital management company specializing in assessment software and solutions. Under his leadership, the company saw significant growth and was acquired in 2015.
Before Merlin, Jim was CFO of Peopleclick, one of the first companies to offer an applicant tracking system serving a blue-chip customer base — including forty-nine of the Fortune 100 and more than a third of the Fortune 500. Jim earned his bachelor’s degree at Indiana State University and his MBA at Indiana University.
Fun Fact: Though Jim’s basketball skills are what some may call ordinary, Jim worked closely on a class project with Larry Bird, one of the “50 Greatest Players in NBA History”! Then, much later, Jim had the opportunity to work at a company where David Stern, commissioner of the NBA, served as board member.
Thank you so much for doing this with us! Before we dig in, our readers would like to get to know you a bit. Tell a story about what brought you to this specific career path?
I began exploring the ins and outs of human capital management many years ago, mainly because software companies serving HR needs were some of the first to use software-as-a-service business models. I didn’t know much about HR, but I liked the SaaS model so much more than the perpetual software license model. It seemed to be a much better way to do business and I wanted to give it a try. Once I learned what a great return on investment talent acquisition solutions provided, I never wanted to do anything else.
What’s the most interesting story that happened to you since you began your career?
Well into our careers, a business partner and I got the itch to do something entrepreneurial. We formed a company, raised some money, and acquired an existing business in December 2007 -just in time for the great recession of 2008. The acquisition had a normal amount of leverage and it was a very tense time as revenues dropped, but the debt service load remained the same. The interesting part about it was the incredibly loyal team that worked together to weather the storm. Our original business plan became a pile of scrap paper and we adjusted the strategy to survive. Our great employees and investors pulled together and we were able to push through it. Because of our determination and culture, it became a really successful company. Despite many sleepless nights, it was all worth it.
Which principles or philosophies have guided your life? Your career?
Don’t think more highly of yourself than you think of other people.
Can you tell us about your “Big Idea That Might Change The World”?
Our vision at Cadient Talent is to revolutionize the way the world makes hiring decisions.
How do you think this will change the world?
We primarily serve companies that have a need for distributed hourly hiring. Local managers make hiring decisions and are normally not well equipped to make such decisions. We have data on hundreds of millions of candidates and tens of millions of hires. This post-hire data is critical in developing machine learning algorithms to predict which candidates will become the best employees.
It’s not good enough to automate the way a local manager hired previously. Most have very high employee turnover rates and we don’t want to automate that process — that only leads to hiring the wrong candidates at a faster pace. Our algorithms recommend candidates based on the traits and characteristics of long-tenured, productive employees. The objective is to select a candidate who will not only be a great employee but also feel a sense of satisfaction and fulfillment in their job. This will reduce employee turnover, improve productivity and revolutionize the hiring process.
Our goal is to make the hiring process as transparent as possible and consider all of the variables that are used in a hiring decision. That’s extremely complicated, if not impossible if you have nothing but a human-based approach. The decision-making of a hiring manager is far more complex and less understood than those of a machine learning algorithm. So, we want to focus on the strength of simplicity in a machine learning algorithm; meaning we only want to look at variables and data that are pertinent to the hiring process — and exclude any data that are irrelevant to the job performance.
We want to be able to augment the intelligence of humans, in particular by using the experiences and prior judgment in past hiring decisions, with an emphasis on those that resulted in good hiring decisions. “Good hiring” can be measured in a number of ways, that don’t implement inappropriate bias, such as the longevity of employees. If a new hire does not remain on the job very long, then perhaps the recruiting effort was not done well, and, in hindsight, you would not have chosen that applicant. But, if you hire someone who is productive and stays for a long time, that person would be considered a good hire.
The only way to address a problem like bias in the hiring environment is to acknowledge it head-on. With machine learning, we are able to learn where mistakes have been made in the past, allowing us to alter our hiring decisions to be less biased moving forward. When we uncover unconscious bias, or even conscious bias, and educate ourselves to do better based on unbiased machine learning we are able to take the first step toward correcting an identified problem. Our machine learning can help us achieve that.
Keeping “Black Mirror” and the “Law of Unintended Consequences” in mind, can you see any potential drawbacks about this idea that people should think more deeply about?
Our view on artificial intelligence and machine learning is that it should provide augmented intelligence about hiring. The process should be managed as rigorously as any supply chain but you’re hiring people. That’s different than other supply chain processes. There always needs to be a human element to it. Relying strictly on artificial intelligence and machine learning to make hiring decisions turns the hiring process into a conveyor belt of on-demand employees. That would be a mistake.
Was there a “tipping point” that led you to this idea? Can you tell us that story?
We make it our business to learn as much as we can about hiring. We know that distributed hourly hiring is extremely difficult and feel that there must be a better way. Recruiting is only one of a local manager’s countless responsibilities. Open shifts have to be covered, customers don’t receive excellent service, operating costs increase, and ultimately the business suffers. Often, the local manager hires quickly based on candidate availability and limited information. They hope that somehow it will work out. Many times, it doesn’t, and the process starts all over again. This results in employee turnover in the high double-digit, or even triple-digit percentages. We have seen too many instances of this occurrence. We knew there had to be a better way. Our experience coupled with all the data in our system put us in a position to lead a revolution in the distributed hourly hiring process.
What do you need to lead this idea to widespread adoption?
Education and awareness.
Many people are not aware that a solution like we have exists. Many who are responsible for talent acquisition in a distributed hourly hiring environment accept high employee turnover as an inevitable cost of doing business. They are not aware that there is a streamlined method available.
There is a general feeling that more candidates will solve most of the hiring problems. What do local managers complain about? Not enough candidates. But an abundance of candidates is not the answer. First, hiring managers can’t possibly analyze hundreds of candidates for a job. They won’t even look at 50 — maybe 20. Second, hiring someone quickly(rather than strategically) to fill an open shift should not be the objective. The real objective is to find a candidate who becomes a great employee and is loyal to the company.
We are continuously surprised by the number of people who don’t track employee turnover and don’t understand the consequences of its expense. Replacing an employee costs $1,500 indirect costs. That doesn’t include indirect costs such as lost productivity and reduced customer satisfaction. Those indirect costs can triple the loss. Educating those in the hiring industry on the effect of a bad hire on their business is key to spreading the word and conveying the impact our machine learning can have.
What are your “5 Things I Wish Someone Told Me Before I Started” and why. (Please share a story or example for each.)
a. Over Communicate: Communicate the strategy of the company with your employees more than you think is needed. At Cadient Talent, we shared a vision of the three S’s. Stabilize the acquired software product, Supplement the offering with additional functionality and Separate from the competition through AI and machine learning. Stabilize, Supplement, Separate was pretty easy to remember but it took the repetition for everyone to understand exactly what that meant and how it affected them personally.
b. Find What Makes You different: Focus on what your company does better than anyone else. In the world of technology, there are a lot of temptations to chase the latest and greatest tech things because they’re cool. Next thing you know, you have a bunch of cool stuff that doesn’t work well together. It makes for great demos but unhappy customers.
c. Listen Twice, Speak Once: I like to move quickly and believe that my instincts are right most of the time. But none of us alone, are as smart as the whole team. If you’re like me, it’s hard work to really, truly listen. Without counsel, plans fail, but with many advisers, they succeed.
d. Don’t Be Afraid To Fail: Winston Churchill once said, “Success is not final, failure is not fatal: it is the courage to continue that counts.” We’d all like to be guaranteed success, but life and business don’t work that way.
e. Be A Servant Leader. The people who work for me are the biggest determinant in whether I will succeed. In reality, they don’t work for me, I work for them. It’s my job to help them achieve success and in turn, that will fuel my success in the long run. If I invest in their lives and careers, they will invest in our mission.
Can you share with our readers what you think are the most important “success habits” or “success mindsets”?
Conviction, persistence and preparation. In every venture which I have been involved in, at some point, something comes up that makes you doubt your ability to succeed. It takes a lot of courage to stick to your convictions and keep working, preparing and being persistent. There is no substitute for the hard work of preparing to succeed in something. Bobby Knight, the men’s basketball coach for my alma mater, Indiana University, famously said, “The key is not the will to win… everybody has that. It is the will to prepare to win that is important”.
Some very well-known VCs read this column. If you had 60 seconds to make a pitch to a VC, what would you say? (He or she may see this if we tag them!)
The human capital management sector is extremely competitive and has experienced a lot of investment over the past decade. Everyone is trying to catch the eye of HR for the latest and greatest tool to acquire and manage employees. The absolute best HR investment a company can make is to hire the right person the first time. Talent management systems are not very useful for hires who are unreliable and don’t stick around. In the talent acquisition sector, many providers are not focused on business outcomes. Goals like recruit more candidates, hire faster and make it easier, don’t produce value if you’re not hiring the right people. Paying for a talent acquisition system that doesn’t provide a tangible benefit to your bottom line is a waste of an investment. There is a lot of talk in this industry about soft benefits, but the best B2B technology investment opportunities are those that provide a tangible, quantifiable ROI. Cadient Talent can provide that, and more.
Thank you so much for joining us. This was very inspirational.
Jim Buchanan’s Big Idea That Might Change The World was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.
