3Sixty Insights #HRTechChat with Caitlin MacGregor, Chief Executive Officer and Co-Founder of Plum.io

For this episode of #HRTechChat, our guest was Caitlin MacGregor, chief executive officer and co-founder of Plum.io. As readers of the 3Sixty Insights blog know, we are convinced that there is a critical link in human capital management between artificial intelligence and psychometrics, and this critical link needs a cacophony of advocacy. The idea is that fast-developing AI for the world of work runs a risk — a huge one, actually — of failing to account for the most important, necessary aspects of humanness. That is, unless we intercede immediately and in a big way. If we don’t, the prospects for humans in the future of work might not be too good.

To be clear, I am hopeful. Caitlin and I went into some depth on the rationale behind this urgency and why this kind of key information may nonetheless be less than a priority among forces currently steering the evolution of workplace AI. Plum’s expertise and value proposition are in the psychometrics side of this equation. Drawing on the latest science, the vendor deals in modern psychometrics. In other words, and to pilfer an old marketing slogan for Oldsmobile, a now-defunct automobile brand, this is not your father’s MBTI. Advancements in the science behind industrial psychology have produced instruments capable of much depth and accuracy in testing for the potential of people.

And the question has now become, what’s stopping us from doing all we can to take all this new high-caliber insight into humans’ potential and inform the development of AI for the world of work? We’re talking about soft skills, by the way. These are the gold standard in predicting humans ability to survive and thrive in a given role. It isn’t hard skills or past experience or past performance. Too many factors are at play.

A bright future of work is possible. Its likelihood hinges on a number of things, and one of those is how good of a job we do right now in feeding still-young AI nutritious data on people potential. It’s the dimension and perspective that conventional data on people’s job eligibility (e.g., credentials) and past performance, while necessary, can’t provide. Among the upsides, meanwhile, will be increases in retention from improvements to the employee experience and employer culture and brand.

Readers can complete a Plum Profile, by the way, and get access to their own full Professional Talent Guide to learn “exactly what drives and drains them,” as Caitlin puts it. In the meantime, I encourage you to watch the video. She brought much knowledge to the conversation.

Our #HRTechChat Series is also available as a podcast on the following platforms:

See a service missing that you use? Let our team know by emailing research@3SixtyInsights.com.

Transcript

Brent Skinner 00:00
Well, hello, everyone. Welcome to the latest episode of HR tech chat. And I am very happy to have with us today Caitlyn McGregor, who is CEO and co founder of Plum. Welcome.

Caitlin McGregor 00:16
Thank you for having me. I’m really excited.

Brent Skinner 00:18
Yeah, so my, we have had many conversations around just artificial intelligence like metrics where we’ve been where we are today where we want to go in the future, the data, the future of work that we keep hearing about, and in my opinion, psychometrics, just absolutely critical, the sort of the latest modern ones. And, and I think it’s an area that hasn’t necessarily been covered as well as it could be. And, and I don’t pretend to be an expert in it. But I’m learning a lot from folks like you. And we were actually discussing this a little bit earlier. But a really interesting way, I think, to start this discussion around what plum does, and where we are right now, in the state of the of the work of the world of work, right? We have, we’re looking in the rearview mirror, and we’re and we’re looking forward and we have some things to think about. You said it more eloquently than I did just now. Do you want to share?

Caitlin McGregor 01:29
Yeah, so what we find is that, you know, where we are in 2021 is that most of our approaches, and most of the technology that’s being leveraged, it really is leaving people in a place where they’re looking in the rearview mirror, they’re looking at, you know, past experience, past education, they’re looking at, you know, hard skills that are scraped from resumes and cover letters, and, you know, doing keyword searches that match up with job descriptions. And they’re looking at all this historical data, looking effectively in the rearview mirror, trying to understand where we’re going moving forward. And the problem with that kind of historical data that focuses on those hard skills and past experience, well, it’s embedded with the systemic barriers and biases that dictate access to education, access to internships, given how fast somebody progresses in their career. And when we look at the field of industrial organizational psychology, no, we have decades now of proven science that has shown that when you take Betty who was a top performer at one company, and drop her into a new company, she’s not automatically going to be a top performer, because the job and the manager and the customer and the product and all of these variables are have changed. And so you really, if you want to be able to predict if that is going to be a successful top performer, again, is looking at those innate talents, the things that are uniquely human, those human skills about Betty things like her ability to be persuasive, or to communicate well, or execute or innovate. And industrial organizational psychology actually can quantify those. And yet, you know, because of, you know, the legacy, ways of doing it, or the fact that it’s been trapped with consultants, you know, the psychometric data has been left out of the equation, and it doesn’t have to be anymore. And it really is the key to unlocking the potential of your existing employees of the workforce, and really revolutionising how we quantify, identify and optimize potential.

Brent Skinner 03:43
So a few things there. One thing he said that was very interesting. Well, if you think about it, funny at first blush to think, oh, we can quantify soft skills, that’s that that’s somebody sort of on the outside looking in, or just kind of strolling, sort of stumbling into this conversation might be like, what are we talking about, you know, soft, is even worse or worse, might not be the right word here this thing? Oh, soft skills. Oh, come on, please. You know, there’s that attitude out there and, and I think we’re getting beyond it. But it’s still there. A B, you brought up a really interesting with this stuck out to me, for me. So the persona, the person the Yes, Betty Yes. Is it we can’t take she’s a great performer in one organization. We can’t just kind of take her and drop her into the next organization expect the same great things to happen. I mean, it could you know, this. I mean, you’re, you take a bad performer, somebody who has a history of like a like a track record of being bad performance, may very well be a bad performer. Next Good performers, they may very well be a good performer next, but it’s not a it’s not a sort of a foregone conclusion in and I think, implicit in that thinking or just kind of, I would say, intrinsic to that thinking to is this idea that, that the human being the person hit that one person is the defining like, is the factor, right? That is the, it’s like you said, there are all these figures, it’s a kaleidoscope of one of my favorite word’s kaleidoscope of variables there that is different in the new organization versus the old. And so and so what sounds like you’re saying is in and, in fact, I’m almost certain This is what you’re saying. And I agree with it wholeheartedly, is that soft skills, if you want to determine whether someone is going to be what kind of factor that person is going to be in the new environment, look at their soft skills more than their hard skills?

Caitlin McGregor 06:06
Yeah, I mean, all of us that have been listening to all the research around the future work for the last five years, it all keeps talking about how work is changing at an accelerated pace that, you know, we’re hearing from our customers, enterprise customers, the jobs are changing as quickly as every six months. So if the hard skill requirements and the type of activities that you’re going to have somebody doing, you know, if we’re saying that, hey, the reason why Betty’s not necessarily going to be successful in a new job is because of all of those things that have changed outside of her control. We’re saying, you know, that even within a job that’s going to keep happening. So what we want to understand is, are we setting up this person for success? Are we going to leverage what makes them exceptional compared to their peers? Or are we going to put them in a situation where the things that they’re asked to do day in and day out, actually are areas that they take longer to do and they get less fulfillment from and you know, is very draining, we see this through the lens of every single person has certain talents, things like innovation, communication, execution, that drive them and give them a sense of self worth, and allow them to perform at a consistently a higher level than their peers if they’re set up for a situation that leverages those any talents. On the flip side, if the vast majority of the day, they’re asked to do things that drain them, then they’re going to constantly underperform and they’re going to end up burning out and leaving the organization. And so really, we’re talking about getting to the detail understanding of it doesn’t matter if somebody is doing. We have tons of different examples. But you know, we talked about my group an underwriter for six years constantly top performer and amazing, somebody who is constantly shown as saying she has high potential, but after six years, she was completely burnt out and ready to leave the organization. But after she completed her 25 minute plum profile, they were able to compare her to what behaviors were needed in the organization for different roles. They thought, hey, let’s promote her to be director of underwriting we want to retain her, she was only a 63 match out of 100, there were 37% of the population that would be more driven and excel as a director of underwriting. But we were able to show that she was a 94 match for product management. It’s not that she was an expert in product management. She didn’t have the eligibility or the readiness for product management. But within four months, by after hiring her internally for product management, she was able to learn about product management, she was able to job shadow, take courses, read books, watch YouTube videos and Ted Talks. And at the six month mark, she was outperforming product managers with 15 years of prior product management experience. And the one year mark, the other product manager they’ve been hired and with all that experience burnt out and left and she was promoted to be Senior Product Management. So there’s nothing about that past experience. It’s all about could she adopt adapt and thrive because she was being her innate talents, the driver were being leveraged noodle

Brent Skinner 09:24
soup. You hear me really excited here because one thing is really interesting here is that I mean what kind of a hiring manager would ever have intuited that like just been like, Oh, yeah, oh, yeah. That person, that’s the person that’s going to succeed. The best or the most, excuse me, in this particular role. Come on. We had we had our global executive Advisory Council fall virtual Roundtable. That’s a real mouthful, sorry, but we had it a couple of weeks ago, and we had We got into a conference that we just discussed a bunch of bunch of table topics that members of the council were interested in discussing. And one of we kind of we meandered into psychometrics and AI and all this kind of stuff and we’ll say in the psychometrics for now, but there was another example, was the same thing as a fellow on our, on our council that’s, that’s in this line of work. And they were looking to fill debt collector positions. And it turned out that they did like a whole profile for culture fit and all this kind of stuff and, and who would actually enjoy and be good at being a debt collector. That mean, that’s a tough role to hire for rabies. Well, it turned out that they found out that the best their persona was, and I think I’m mangling this a little bit. So I’m not getting this exactly right. But it was something along the lines of somebody who worked in sort of a, like a, like an intense sort of daycare and child daycare environment. Or it was either that or, or former stay at home mothers that had many children like is something about that was somehow transferable to the debt collecting role, which is, you know, it’s kind of funny, you know, to think about, in a way, but, and I had the same reaction, I said, Who what kind of a hiring manager would ever have figured that out on their own. And yet, those are the soft skills that are going to, I mean, those are this, it’s funny that soft skills are the roles that people with this particular soft skills previously had that are going to work where you where you want them next. And the other thing I just want to get out here is this idea that, you know, soft skills that you mentioned, retention, and all this kind of stuff, right? I mean, those are, that’s, that’s, that’s hard dollars, kind of stuff. And, and, and again, you are so an organization might kind of scoff at the me, I might be over exaggerating this a little bit. But I think I think there is an attitude out there that soft skills now, we got to look for a, b and c, you know, we need somebody who can code we need somebody who has an MBA this sort of stuff, right? And, but you’re actually going to it, I think the attitude behind that as we need to do we need to hire for stuff we know they’re going to be able to produce and they’re going to stay and this is kind of rule they’re for and all this kind of stuff. But if you really want to affect those, you know, the bottom line to protect your, your, you know, your, your, your finances is organization, you want to you want to look at the soft stuff.

Caitlin McGregor 12:48
Well, even when it comes to developers, do you want developers that write meticulously clean code without errors? Because you’re delivering enterprise grade solution? Or are you creating rapid MVPs? And you want people to be able to get something quick and dirty up? Do you have an integrated development approach where your developers are working hand in hand with design and product? And therefore communication skills are critical? Are you doing pair programming where teamwork working together is critical? So you know, you can have people that can write code? But are there flaws in the code? Is it is it draining on them are what other things are you going to have to rely on? Being able to understand right out front, you know, you’ve lined up 100 people that look identical on paper, and knowing which people are going to excel in the role Excel, like really thrive long term. That’s you can’t get at it any other way than psychometric data. And then the other part too is there’s other elements where you need psychometric data to understand one of those areas is leadership. Understanding what makes somebody a successful leader, regardless of industry, regardless of all these other factors. But being a successful leader long term in their career, there are foundational dimensions of leadership that are psychometric, the same 25 minute assessment that Maya took, we can layer on a leadership dimension framework and understand, you know, does she have learning agility? Does she have drive she had presidents does she have these six dimensions that predict leadership long term, and the value of that is that a lot of the times when we evaluate leaders, we’re waiting until they’re already in a leadership role. And we look at observe behavior. And you subjectively say, I think this person, you know, has potential or doesn’t have potential doing some form of talent review, that is subjective based on who they’re reporting into, potentially 360 of giving the valuation but it’s always based on the observed behavior. And what happens is that if somebody As a top performer in the role that they’re doing so they’re executing Well, they are more likely to be said that they have potential. But it actually has nothing to do with their leadership potential. It’s how they’re performing as an individual contributor often. So what happens is that if you’re looking at Junior talent, if you’re looking at talent, that is the most diverse in your organization, which is on the earlier rungs of the organization, there isn’t yet observable leadership qualities to be able to measure against. And so to understand, in the first few years of somebody’s career, if they’re more likely to be invested in putting them on a managerial track, or if it’s better to invest in them on the expert track of becoming the best of the best subject matter expert, you don’t have any data, you can look at past experience to say who is going to be your future, you know, best leaders who’s going to perform best on a managerial track versus who will be the best of the best expert in potentially being an expert developer, an expert in in product management or an expert in in an ops role. And so it’s really fascinating that you just don’t have that other those other data points at that time.

Brent Skinner 16:11
Well, this is really interesting, because, you know, there’s the sort of the, the old trope that a lot of people get sort of, you know, promoted into managerial roles, and they’re just not, they’re not cut out, they’re just not the right kind of person to be a manager, and you can learn some aspects of leadership, right? You can become better at that, but, but there’s some folks that kind of just have the innate psychological, psychological makeup for that. And, and there’s, you’re not going to hire well for managerial roles by looking at how well somebody performed and in, you know, up to that point it, you know, sales is a great example, there could be, I’ve heard this many times, and many sales people in various scenarios, circumstances I’ve been over the course of my career where, you know, somebody was a great sales, like a really, really good salesperson, they got promoted into, you know, like, Director of Sales or VP of sales, and was all of a sudden, you know, in charge of, of managing a team of salespeople, and no longer really doing, like soup to nuts sales themselves. And, and, and they weren’t necessarily, in fact, more often than that just weren’t effective in their sales manager, because it sales leadership position.

Caitlin McGregor 17:33
So if we take it back to the concept of what drives and drains, you, you know, as a manager, your goal is to support other people to unblock them so that they can be effective, you know, your to do list is not important. It’s about how you empower and support these other people. Well, day in and day out, not accomplishing your own tasks, and just constantly supporting people can be incredibly exhausting, for some people can be a nightmare, they just go and get their work done. For other people, you know, supporting people gives them a sense of self worth, and they’re really excited. But that means that maybe that to do list was less important, which means when they are in an individual contributor role, and it’s all about their own to do list, they actually might be coming up as just average performers. It’s amazing how many average performers are actually incredible future leaders, because they’re No, they’re not given the opportunity yet to be in that facilitator supportive role. And so it’s really, you know, sweet often as society value leaders, we think, Oh, you know, if I would identify the top 10%, or the top 25% of future leaders, you know, I’m screening people out and it’s more this elitist thing. And it’s actually more twofold. One is we need to embrace that there are two tracks, and they are equal and amazing opportunities, and how do we change our companies to value that expert track versus that managerial track, but also see this as ability to screen people in that are often missed, the way we identify future leaders is embedded with enormous amounts of bias. And this is a way of bringing objective data in to screen and people you may have missed to calibrate your talent review process. This is only one data point, but it brings you that objective lens and just put people on the right track where they’re going to be set up for success long term. And if they’re successful at your company, and they’re thriving, they’re more likely to stay. Yeah, and

Brent Skinner 19:32
you mentioned earlier and I meant to say this in response and reaction because I think it’s a great point that you made you know that you want people doing the work that they feel most valuable, and like they feel like they’re delivering the most value and I think you know, the corollary to that is a they enjoy it the most or they feel they make if they enjoy whether they enjoy it is one thing but they derive the most satisfaction from delivering it to you know, maybe you know, you don’t enjoy every single minute of your day, even if it’s stuff you like, you know, sometimes you just want to take a break. But at the end of the day, it’s like you derive the most as you feel you look back on it and say, Yeah, I feel good about that. I feel like I knew what I was doing. And I was good at it. And I feel like I’m a value of the organization. Well, if you’re talking about valuing people, you know, in terms of, you know, quantifying that in the, in the form of comp compensation even right, you want them to be doing what they feel most valuable doing. So that’s going to, there’s going to be I think, some just sort of natural alignment with compensation strategy to the other thing is complete, kind of unrelated to that, but I want to go back to this leadership thing. How do we know what’s a good like a priority? What a good leader is like? How do we know that? What have you learned in the past many, many years about that,

Caitlin McGregor 21:00
we know that often leaders are selected based on what current the bench of leaders looks like. So if you have, you know, leaders that are very voiceless and, you know, very dominant and, you know, very assertive with the direction that they want, then we assume that that is what leaders need to look like in that organization to be successful. So we do an enormous amount of pattern recognition of whatever the leadership bench looks like today, then that is a mirror of that. But we have a lot of organizations that are kind of having their moment where they’re like, Wait a second, five years from now, is that really what we want our leadership to be? And our leaders look one way? Do we really want leaders to look as homogeneous as they are there? Do we want to have more diversity in those leaders moving forward? So a lot of organizations are recognizing that what leadership looks like today is not what they aspire to be, you know, down the road? So how do you? How do you look for that? So we constantly come back to industrial organizational psychology, it really is a science that has been well validated, over decades and decades of research, looking across the globe as to what does successful leaders have in common. And it’s been boiled down to a very crystal understanding of common talent dimensions. Now, different companies like Deloitte and things like that have come up with different names of it, but there’s a very large degree of consensus. In our case, we’ve called them learning agility, and presence. And, you know, there’s, there’s six of them in total that we go through. And those are combinations, looking at the whole person, what are those pieces that line up to being successful long term, as, as a leader, and all we’re doing is looking at every single person in the same 25 minutes assessment that he already took, you know, either because they were applying for jobs, or they’re an employee, and we were supporting them with the professional development, or we’re helping them with an internal mobility opportunity, that we’re just layering on a framework to their existing universal assessment, and we’re able to surface you know, and you can be in the top, you know, we do it on a scale of Four Diamonds, you can be in the top 10%, how for diamonds, but your mixture may may be different compared to somebody else, there may be certain elements that within that you’re, you know, you soar with, but even if you’re in the top 10%, there’s certain areas that you struggle with. And it really brings that self awareness in the leadership context, in terms of where there may be a friction point, versus where you could be leaning into even more and embracing and setting yourself up for instances where you get to utilize that even more. So basically, that the long answer to what it could have been short answer is, there’s science behind this. There’s research and validation and consistency, we are not reinventing the wheel, what we’re doing is finding a way to give an A positive employee experience where they’re getting benefit from their own insights around their own development guide, and opportunities for internal mobility and development and things like that providing objective data that’s going to screen people in that are often missed, finding way to make this scale so that it’s effortless to continually get more and more value from the same data set. What’s new is how we’re applying it with technology. But the science has been very consistent and clear for the last few decades.

Brent Skinner 24:31
Interesting. That’s, I mean, that’s important. I guess I have a question. Now, this might be a good point. A good segue to the idea of artificial intelligence because I think that’s, you know, it’s, it’s really infiltrating, it’s starting to infiltrate, external and internal hiring. We’ve been speaking with all sorts of vendors that offer some sort of silver along that continuum, right? And I think it’s very important, you know, I think it’s gonna help. It’s, we’ve spoken with folks that help you sort of, you know, understand what’s in your ATMs, which could be like just a massive trove of information, you know, impossible for recruiters to just kind of sift through, you know, you need AI to do that. And, and then I’m just curious, what’s your if you have an opinion on on artificial intelligence, when it comes to internal and external hiring, how it should fit. And, and I’m, and I’m also interested in how your view on how psychometric information should be a part of that.

Caitlin McGregor 25:44
Yeah, if we go back to, you know, past experience, past education, and we look at industrial organizational psychology, it’s consistent that that experience that data set past experience and education, the validity of it, predicting future performance, is less than flipping a coin, like it really isn’t predictive of long term success. So it’s not that that data isn’t valuable, it helps you understand eligibility, it helps you understand readiness, it helps you understand geography of where you know, somebody lives, if you need them in the office, there is valuable data. But you know, with reference checks, for example, we don’t do reference checks on every single person at the beginning of the funnel, we wait until it is appropriate to bring that data in. And what I worry about is that because it was something that we could quantify when things like soft skills felt like we couldn’t quantify it, I feel like we may have over rotated in terms of how we are using it. And I think it’s important, but are we talking about eligibility? Or are we talking about performance? Are we talking about identifying potential? And who is going to be set up to thrive? Are we talking about can they hit the ground running day one. And so it’s all this data is important, but how you order the workflow, how you order kind of those stage gates of decision making, I think is what needs to change in our industry. The data I’m talking about measuring people’s innate talent is four times more accurate at predicting on the job success. So you should be starting with that, and bringing in other data after we’ve shortlisted on the people that are most likely to set up be set up for success. Yeah.

Brent Skinner 27:33
Sorry, I entered. I didn’t mean to interrupt you there. Sorry. But you really struck a chord. When you said eligible? I think you said eligibility versus potential. That, that I mean, that really, honestly, I think that just cuts to the crux of that customer gets to the crux of it, right, we’re looking at, you know, conventional, the conventional approach to assessing whether somebody is, is a good candidate to interview for a job. Interviewing is a whole other area that it’s a rabbit hole, maybe we won’t go down today, but in any event, the decision whether to consider somebody for the role. Conventionally we’ve, we’ve, we’ve looked at eligibility and inmate nav, we’ve looked at past performance, you know, as it is portrayed by the, as a person self presented in their CV and in an agenda view and all this and maybe speaking to references. But we haven’t looked at so that’s to me, that’s another level, not necessarily just edge eligibility, right. But we haven’t looked at we haven’t really looked at like we should first and foremost, like you said, innate capability like potential, which is the potential. That is the potential.

Caitlin McGregor 29:05
And I think there’s two ways of looking at it. We traditionally look at psychometrics assessment in the talent acquisition side of things, you know, being able to screen in people being able to help with that shortlisting, when you’ve often when you have high volume of applicants, that that’s what the industry is more familiar with. But what we’re seeing now, especially with the great resignation is why are people leaving, they’re leaving because they’re not fulfilled. They’re not thriving in work. They’re not having that sense of self worth and feeling like they’re at the end of everyday going. That was the best day ever. I got to really be a superhero today and I executed on these things that really made me feel amazing. They’re feeling burnt out because they’re not feeling like they’re in an opportunity to thrive. And so when we think about the great resignation, we should be thinking about how We truly recognize the humans that work in our organization, how do we optimize for their potential? How do we give them opportunities inside the organization to keep growing and developing and thriving. And this psychometric data has typically not been used other than very siloed. Use Cases in talent management. And I think that’s the biggest opportunity in front of us is using psychometric data through the entire lifecycle. If you like one of our banks, they’re hiring 5000 people a year, well, you’re saying to the applicant, hey, I want to bring you in, because I want to know the whole you, I want to know you know how to how to really leverage you Well, once they become that employee, you use that data to then help them onboard and use that data to help them with professional development, development, use that data to help them move into new roles, and to identify what track they should be on. And if you didn’t hire them that way, use it on your existing employees and help this data and rich, how you can personalize the experience for them and really nurture them and you are going to have, again, if we go back to AI, you’re gonna have a lot of people with the same keywords, the same background, and talent time, but really understanding them and what drives and drains them. And that’s where we have to go into including this additional data set that frankly, people couldn’t access before, because it didn’t scale, it didn’t provide a good employee experience. So it’s understandable that we weren’t doing anything before with it. But now is the time where we have access to this data and can include it to really change our relationship with our employees.

Brent Skinner 31:39
Well, from what I understand, so few things for, from what I understand the psychometric instruments that we have available to us today are much more accurate. And, and, and targeted, and, and reflective of people’s actual innate capabilities. And like the old ones, what I’ve been telling people this year after kind of talking with folks like you is that, you know, this isn’t your father’s MBTI, or whatever it is, you know,

Caitlin McGregor 32:10
like a flip phone, you know, it’s no longer flip phone from 30 years ago, we now have smartphones, we have gone through massive evolutions of how we can, you know, really take this data out of the hands of the consultants, and really expensive one off catalog assessments, and really democratize access to this highly predictive data with a fantastic user experience where it’s a win win, it’s not a black box, this data really allows people to be the CEOs of their own careers, and empower them to optimize themselves just as much as providing the data to the company so that they can be part of the process and have the right conversations and make the right investments in their people.

Brent Skinner 32:50
Well, I think I think you’re right about democratizing access to this to this highly powerful information. And I just want to go back to AI again, for a minute here, because what I’m seeing is that we have a lot of very highly capable, sophisticated solutions that are that are accessing that that eligibility level data and maybe that past performance level data, but not this, that that sort of innate psychometric that psychometric data on the person’s innate potential. And, and to me that, I mean, to me that that’s really worrisome. From a, from a, you know, just an industrial, you know, like, who’s looking for the market space? For the world, yeah, worrisome for the world of work for the future of work, the not too distant future of work right can be is I think that we, if it would be, I think it would be a, in my opinion, a colossal catastrophe for, for AI to kind of for to leave the station for the train to leave the station. And for this, this type of information, which is the most predictive and useful, I am convinced of it, not to get in there soon enough, right? So I honestly think we’re at a critical time, in the, in the profession of HCM in the world of work, in general for this.

Caitlin McGregor 34:24
I couldn’t agree more. And, you know, we know realistically that the Holy Grail is you want as many different data points as possible. It’s just right now, you know, getting this data in there and prioritize properly isn’t the main priority. You know, companies that control the algorithms want the easily accessible data that they can scrape that’s, you know, so it’s going to take some time, but I think it’s going to be customers that are going to say, Hey, you know, we want to also bring in this data source and we Want to prioritize the waiting of this data source, we want to use this first to focus on who has the greatest potential, and then use the other day that as the supplement. And I think that, you know, is educating people in the industry first that this, that there is more predictive data than what’s being harnessed and then figuring out how to combine it in the proper way with the rest of the data sources. The more data, the better. It’s just this is the objective, predictive data. And it’s game changing. And it’s really about getting that message out there.

Brent Skinner 35:31
Yeah, I think you’re right. I couldn’t agree more, you know, the great resignation is a huge opportunity for this, you know, if you’re an organization that wants to retain your people, you want to be able to innovate in the future, by having that top talent. You’re not going to get there with I’m going to keep using this sort of using the parlance of the lexicon of eligibility data, past performance data, you’re not going to get there with that, you know, it’s better than nothing, but it’s definitely not going to keep you competitive in the in the, the that that old term the war for talent, which is it’s really become a very hot war. Yeah. Thank you so much. This has been a fantastic discussion. Fantastic discussion. So many really interesting things happening in this field. Have we missed anything? Anything? any parting words or anything else you’d like to cover?

Caitlin McGregor 36:36
No, I think this was great. Thank you so much. I really appreciate it.

Brent Skinner 36:40
Oh, absolutely. The pleasure is all ours. Caitlin. Thank you very much.

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