Episode Transcript
[00:00:00] Speaker A: Good morning, everybody. Today I'd like to talk about the process of recruiting and talent acquisition in a little bit of detail to explain why I seem to have dozens of calls every week with large companies and small struggling with this entire process, not just around AI, but with the process as a whole. And what I've learned over many, many years here is that this is one of the most complex and maybe strategic parts of human resources of all. Because of course, if you're not getting the right people into the company, you can't run the company effectively. You'll have high turnover, you'll have poor performance, you'll have lack of innovation, et cetera, et cetera, et cetera. So getting people into the company is almost the lifeblood of running the company. Now, of course, the other reason it's such a complex process is that everybody who's ever been hired has an opinion as to who to hire and how to hire them. So this is not something where the HR leader or the HR professionals can tell people what to do. We all have our own experiences with the process, we've all been through it and we've all seen where it can result in poor decisions. The first thing I want to point out is that before we talk about AI and automation and technology, this is not a single process at all. The process of hiring a, an entry level employee out of college, a high turnover, hourly wage employee in a routine work job, the process of hiring a scientist or a highly refined, highly skilled IT professional, hiring a mid level manager, hiring a senior manager, hiring a sales executive, hiring a business executive, hiring a C level executive are all different. So what you're really dealing with here is a process that isn't really one process, it's really many dozens of processes. And I haven't sat down and tried to draw all the different tributaries, but each one is different. And you know, those of you who work in HR, that executive recruiting is vastly different from entry level recruiting and sales recruiting is vastly different from technical engineering and IT recruiting. But it's even more complex than that because for many of you, if you work in entertainment, if you work in travel, if you work in financial services, if you work in pharmaceuticals, you have regulatory issues, you have culture issues, you have skills and experience issues, and much, much more. Now, the reason I decided to do this podcast today is we just spent the last year doing a lot of work with a company called Findom. And I'm going to write a report or an article on Findom in a few days. And what Findom did is they Took all of the data about people in the workforce, about a billion employee profiles, and they applied data labeling and time series analysis to this data. So using the Findum data set, if you were to look at my profile of my experience and notice that I worked at Sybase in the early 2000s, and if you knew what was going on at Sybase in the early 2000s, which I do, but most of you don't, you would know that I worked for a hyper growth company at the time and a company that was run by its founders and went through a series of acquisitions that caused it to eventually fail and be sold. So I had a particularly unique experience as a marketing and product professional, living through and working in that environment, and met many, many people who joined Sybase during its fast growth rate because it was a hot company in Silicon Valley. None of that is reflected in my job title, my job profile, or any information that I might put on LinkedIn. But what I did, which by the way, isn't very so in my particular case, or in any particular case, when you're looking for a manager, an employee, an executive, or any particular role, there's this three dimensional experiential history and training and skills and cultural background to every single person you hire that's really invisible to the hiring process. Now, one of the approaches to dealing with this multifaceted problem of hiring is what's called a pre hire assessment. I've done a lot of research on pre hired assessment over the years and interviewed many, many companies. And what this process involves is you sitting down with the hiring manager and understanding the actual nature of the job, the day to day activities, the required strengths and capabilities that are needed, the kinds of stresses and problems that this job faces, and then coming up with some sort of realistic job simulation or preview or test so that the person applying for the job can understand for themselves and you can understand as well whether they would be a good fit. It turns out, for example, that there is a particular job I know of in a distribution center that has a 300 to 400% turnover. In other words, the entire organization has to rehire everybody three or four times a year. And I talked with the HR department of that company and they said, well, we know exactly why that is. We know what these jobs are like. They're very difficult manual labor jobs and unfortunately we have not yet found a way to change the operation to make them easier. So we're suffering and dealing with that turnover issue. And we are very clear to people when they apply for these jobs, that they're going to be difficult. Yesterday I also had an interesting conversation with the talent acquisition team at a large poultry company that it's actually one of the largest. And they explained to me that the jobs in those companies and I've also talked to others in that industry are very difficult. You're standing on your feet the entire time, sometimes lifting very heavy objects and dealing in obviously a very complex, frenetic experience that many times people apply for the job except come in and leave the same day or they don't show up at all. So, you know, what's the point of going through that process? Why not give somebody a preview of what that job's going to be like? I remember when I was doing a lot of research on pre hire assessments that a large retailer of jewelry used a very sophisticated pre hire assessment to put candidates through a simulation of what would it be like if a couple walked into the jewelry store and the husband told the wife, we can't afford that piece of jewelry. And the wife said, but I love it, I love it, I love it, I want it. What should you say?
And it was actually very interesting simulation and it tried to measure the empathy and the sales skills of the prospective hire. And this goes on and on and on. So, so there are, you know, attempts. We make many, many attempts, particularly in high volume jobs, to create realistic job previews or assessments that better estimate the real experience somebody's going to have that make it easier for the candidate, by the way, and also for us. Some of the pioneers on this include shl, this interesting company called Maki People that has applied AI to this and many, many others. We just did a case study on Kmart in Australia that's in the podcast series. You can listen to what they did with Prescriptive Hire. And it's a really, really interesting part of the process. And my experience in talking to many, many companies is these work extremely well. They feel like a lot of extra work. They feel like a rather big project. But if you're doing a lot of hiring as a for lots of flight attendants or retail workers or operational workers, it really pays off. But the second sort of magic to this is not relying on hiring managers to make the decisions. Now, it may seem a little counterintuitive that we don't want the hiring manager to decide who to hire, but in reality, hiring managers don't necessarily see the entire company picture. Sometimes they do. And many hiring managers are very, very seasoned at recruiting and they know exactly what they want and they have experience doing this and they've run these kinds of businesses or operations before, so you really want to rely on their expertise. But across your company, whatever company that may be, you have unique cultural issues. So for example, at Deloitte, where I worked, or at Google where I know some people pretty well, most difficult decisions in the sales environment are made in a very, very collaborative way. There are very few renegade salespeople that can do whatever they want because the deals are complex and the way a deal gets done and the way a client or a customer is attracted is through a combination of internal people working together on a large proposal and a large contract. So if you're a salesperson that's used to working alone and don't have experience in cross functional collaboration, you may be very, very successful at one company and a dismal failure at another company. In fact, many studies from many companies have proven to me that in most sales situations, internal relationships are almost more important than customer relationships because you need to leverage executives and others internal to make these contracts happen. So that's another example of this. We did a case study many years ago for an automobile insurance company and found after enormous effort to hire college kids with great grades and people that had had lots of leadership experience in school to get really blue blood top name people into the company, that most of them were failing in the entry level jobs in the auto part of the business for some reason, because it was actually a very, very tactical job. Auto sales is a very much of a commodity type of sale and you really need to learn how to position the product quickly and understand the budget and the issues facing the buyer. And they later realized through statistical studies of the high performers that the people that were the most successful were actually people that had worked in the auto industry, not people that had come out of college with good grades. And because they could talk to the customers about their cars and it made them and endeared those customers to this particular company that they were going to get a good policy and a good experience.
So that idea of studying the high performers and using that information to go back and change how you hire and who you select is also a hugely important idea. Going back to the chicken company, which I suppose the industry that they're in is agricultural food services. They have, as most companies in this kind of industry do, do have relatively high turnover rate. In some parts of the company it's 60% per year. In some parts it's higher, in some parts it's lower. They're now introducing a whole series of metrics, manager by manager, to identify where the high turnover pockets are and study statistically, and they're about to buy a whole new talent acquisition system to do this, to study where the turnover is higher, to understand the characteristics or the attributes or the management issues that might be causing that in that part of the company. So there's some really big opportunities for science and deep thinking and statistical modeling here in talent acquisition, far beyond the basic intricacies of doing an interview. Then there's the issue of interviewing. Now, I've never been a very good interviewer. It's never been my thing, although I know people that are good at it. And there's many, many books written on this and lots of science behind it.
But again, unfortunately, what we generally rely on is the skills of the interviewer. And what I've learned over the years as an analyst is that the best way to conduct great interviews is first of all to create a behavioral interview where you ask people behavioral questions. By the way, Galileo is extremely good at this because it knows so much about all these different jobs in the world. It creates incredibly well developed behavioral interview guides and then use a panel of interviewers. And don't just study the questions, but study the successful track record of different interviewers. And what you find is that it's actually statistically been proven to me in different companies that certain people have a track record of hiring and assessing the highest quality, highest performing candidates. I can't exactly explain why that is, but what you'll find is that you'll have some people that are very, very successful at interviewing the best candidates because of their nature. And there are probably books written on this. I don't really know where they are, but it's an interesting problem. And so that's another big part of this. And now that we're doing AI agent interviews where an electronic agent is doing the interviewing, more and more of the science of behavioral interviewing can be encoded.
One of the complexities, of course, of interviewing is the scheduling of the process. And believe it or not, that's a massive overhead in every part of talent acquisition. There's interview schedulers and lots of software that does this. I think, you know, maybe one of the most interesting revolutions we're going to see in talent acquisition is the AI interviewer that's available immediately. So you apply for a job, maybe it's the evening because you're working at another job during the day, you finish the application, you go through some sort of job preview to understand what the job is, the location, the shift hours, the pay, the benefits, et cetera, and the System says, would you like to go through an interview right this minute?
And rather than wait to be scheduled and go after back and forth for days and days and weeks and weeks, you just do the interview immediately. And the system assesses you at that point in time and says, you are an excellent candidate for this job. Let's proceed to the next step. Or you're potentially a good candidate for another job. In our company, we think this may not be the right fit. Would you like to proceed to this step? Or you may not be the best fit for this job. We suggest you perhaps look elsewhere. So that's going to become a big part of this process.
And then, of course, there's the cultural issues of hiring. We always hire people, for example, in our company that have a consulting culture, that they're good listeners, that they're problem solvers, that they're willing to think deeply about a problem or a situation.
We actually used to have people write research studies for us before we hired them into the analyst role. That was also a very interesting process of seeing how people think, seeing whether people can write. One of the things I found many, many years in this work is that some people just don't have writing skills. They never really learn to write very well. And as a result, they don't think necessarily in a very strategic way. And they don't, and it's difficult for them to organize their ideas. And we can't really teach people how to do that very quickly. We can over time. So we realize that writing skills are sort of something we assess in our cultural process.
We also spend a lot of time interviewing people in our company across the organization because we're not that big and we want everyone to essentially like and feel comfortable with every hire because we all tend to know each other pretty well. There's lots of cultural issues like that. My boss at IBM years ago, used to bring people in for interviews all the time, and he would have our entire team meet them. And then at the end of all of our meetings, he would sit us down and say, well, do you like them or not?
[00:15:35] Speaker A: And it was that simple. Of course, IBM had lots and lots of training. And so, you know, almost anybody could learn how to get to know these jobs at IBM because there was so much support around it. So there's the cultural aspect, and then there's this idea that the hiring manager doesn't really own this person anyway. We're hiring this person into the company as a source of talent for the whole company. So why would one manager be able to make A decision on who to hire when it's not really up to them.
It's really up to the whole organization whether this person is a new hire. And it may be that the manager themselves for some reason isn't a perfect fit. And so they're hiring people into their group that are more aligned to their desires and their approach and their group is not a fit with the rest of the company.
So there have been lots of studies done by Google and others that we have to take the manager out of the process to come up with a better, more high quality, enterprise wide approach to hiring. Then there's the issue of assessing somebody's technical skills. Do we give them a test? Do we give them a coding test? Do we make them do a bunch of math problems? It's interesting. At Google for many, many years, they built an incredibly good software engineering organization over many years by giving people very, very rigorous tests. I had a very funny conversation at a dinner not too long ago with a bunch of recruiters in it who said to me, you know, our tests don't work anymore because every time we give somebody a test, they seem to pass it 100% because they're using AI to take the test. So we need, you know, continuous forms of testing. I mean, I remember when I took the professional engineering test many, many years ago when I was a mechanical engineer. I could tell from the test that it wouldn't have been that hard for me to read the test in advance and basically game the test. Another problem that you're going to run into, especially when people applying for jobs are using AI skills to apply. So that's an issue as well. And then there's the issue of disability, gender, race, age and other forms of discrimination. Many companies have told me over the years, back when we did a lot of research on DEI a few years ago, that there are managers in their company that will not hire women, that will not hire black people, that will not hire minorities, et cetera, for various biased reasons. It shows up in the data. They look across the organization and they realize that one part of the organization is inconsistent in its demographics with others. And one of the chros actually told me, I know who the racists are in my company. And she had done enough analysis that she could see where that was happening. So, so that's another part of this process is how do you eliminate that natural bias that people have based on their life experiences? And then there's of course the issue of temporary job, part time job, gig job, versus full time job. If you look at the nurses around the world, which is the most in demand job in the United States, happens to be in clinical professionals in healthcare. Many nurses, because they're highly skilled, work in a contract basis. They're either traveling nurses or they work as a, as a sort of a gig job because they want to have time with their families or the rest of their lives. And they like the idea of working in flexible hours.
So you have to determine what is this person's availability, what is their ability to work nights. You can't ask them a lot of questions about their family, you can't ask them a lot of personal questions about their situations at home. But you have to assess whether they're telling you the truth about whether they're going to be able to work nights or weekends or other shifts. That's another aspect to many jobs. If you go to work at a McDonald's or a retail store, there could be customers that come in that are dangerous. There could be safety issues in the store, there could be safety issues driving a truck, there could safety issues in a manufacturing plant. And so you need to assess people's interest and nature of learning and taking care of processes that could cause damage. And actually, there's a company by the name of Axonify, that's an online training company that is very, very good at assessing and training people for operational skills like this. There's also simulations, 3D simulations. I mean, Shell Oil, for example, and other oil companies have very extensive, complex simulations of oil drills and drilling platforms and wells to show candidates what it's really going to be like to go work on one of these platforms, get helicoptered out into the middle of the ocean and, and deal with these jobs which are not easy. So as I said in the beginning, every company has dozens of situations that are different. And when we centralize talent acquisition, the purpose of centralizing it is for you to apply your intelligence to this process, not to just do a lot of interviewing as fast as you possibly can and hire a lot of recruiters. By the way, the process of hiring and staffing recruiters is also a massive problem. If you look at the talent acquisition process in most companies, there's a job assessment, assessment process where you understand working with the hiring manager, what is the job, what is the need? That's usually done by a business partner or a talent advisor. And there's lots of interesting issues there on assessing whether this job is necessary even to be hired, and have they scoped it correctly, have they leveled it correctly, and have they defined it well, then there's the process of sourcing. Where should we look for this person? What are the demographics, the location, the educational history, the experiences we should look for, and all of the data issues around that which I talked about earlier where I was able to find them. Then there's the issue of attracting these people through advertising or job placements. Then there's the issue of screening and assessing them and interviewing them, as I talked about earlier. And then there's the issue of giving them the right pay and making them an offer. And so if you centralize all that, which is what most companies do, which makes sense, then you're going to have a lot of data and a lot of science to think about. And the reason we talk about what I call super agents is that this is a perfect application of AI. And I keep going back to this analogy and you're going to read all about this in January when we produce our imperatives report of a self driving car. You know, a self driving car is not a power steering agent connected to a power brake agent connected to a lane change assisting agent. It is a different thing. It is an integrated system that looks at all of the sensors of information that come into the car to make sure the car is driving quickly and safely from point A to point B. In some ways, that's really very, very similar to talent acquisition. All of the things I just mentioned on this podcast are complex and they're interrelated. So we want to bring them all together to have a high performing, high efficiency, high effective process.
Let me conclude with sort of one more message here for those of you that are in the recruiting function or at HR leaders. You know, one of the companies I've interviewed many, many times over the years is American Express. And I'm a huge fan and admirer of American Express. I've done business with them for almost my entire career, worked with them on hundreds of things personally in my professional life for different things, and talked to them internally. And their talent acquisition group has gone through a few transformations and I've talked to different people that have been responsible for it over different periods of time. And one of the things they told me was interesting was, you know when you call and you work with American Express to buy something, to get a new credit card, to deal with an issue, to plan a trip or whatever it may be, you notice that they're a very consultative organization. The way their call centers work, the way their staff handle inquiries. There's something about them that is very different from typical credit card company. I'm not saying there Aren't other great banks too but, but they are in particularly unique and if you look at their stock performance and their financial performance over the last multiple decades, it' pretty exceptional. It's a very, very well run company. And one of the heads of talent acquisition there that was involved in a lot of the tech stuff and I talked and he said to me one of the things that we learned at American Express from all of our recruiting over many many years was that we're not really hiring financial services people, we're not really hiring customer service people, we're not really hiring call center people, we're hiring hospitality people. And they learned over the years that one of the best experiential background that they had at the time, and I'm not sure if this is still true, but I wouldn't be surprised if it is, was not people that had done this job before, but people that had worked in a hospitality company or a hospitality environment.
Because in a high quality hospitality business like a high end hotel or a high end travel company, there's a lot of consultative service oriented culture embedded into the environment. And you can learn that. When I went to work for IBM in the 80s, I learned about care of customers, I learned about listening, I learned about empathy, I learned about studying the problems of the person on the other end of the phone or sitting across the table from you. I didn't know anything about it when I got out of college, but I did learn it over the time that I was there and I was there for 10 years. So what American Express decided over some period of time was that we're not going to hire people that worked in a bank call center or people that had worked in IT just because they know the systems, just because they know how to answer questions. We're going to hire people that have experience in a hospitality culture and you know, you can't argue with their success. You have exactly that exact formula in your company, I can guarantee it. I know this from my experience working with so many companies over the years that every company has some aspects of its culture that are unique to that company. At Microsoft, I don't know exactly what it's like to work there, but I know that they honor software engineering. They are engineers at their core. When you meet people at Microsoft, you can see that they're deeply engaged in the design and the product management and the engineering of the things that they build. Not all software companies are like that. Some software companies are very, very sales and marketing and customer focused. And the engineering is there of course, but that's not their primary value proposition. So you get to decide based on the culture of your company and the leadership and the history of your company and the legacy of your company, who are you going to hire? You look at a company like l', Oreal, which is basically a gigantic marketing company focused on beauty. You look at a company like American Express, you pick whatever organization you're in. And that is another important part of talent acquisition.
So let me just conclude, for those of you that are recruiters or lead or run part or all of the recruiting process, we admire what you do. What you do is so important and so complex, and AI is going to play a larger and larger and larger role over time. But if you simply just respect the complexity of this, and by the way, this is the reason companies outsource a lot of their recruiting. Because there are very specialized outsourced companies, headhunters, companies like ams, others that really understand this process, then you are really building the growth engine of your company. I like to think of talent acquisition as the company growth department. You're not just collecting bodies. You're responsible for implementing and planning as much as you can how your company will grow. And sometimes you're going to say to a hiring manager, that's not the right person. We strongly believe we should have somebody like this, not that, because our company will be better off in the long run if we hire this way. And I just want to tell you how much I respect what you do and we admire the complexity of it. And we're more than happy to help you with your talent acquisition strategy if that's something on your mind. And as you'll read more about in January, the agentic world of super agents is going to have a massive impact on talent acquisition in the next year or two. And so get ready for lots of exciting changes to take place. Thanks. I hope this was helpful for everybody. Talk to you again soon.
