S5 E45 | Recruiting Community: Mark Gray and the Evolution of Recruiting with Real Data

From fax machines to AI… recruiting has seen a dramatic evolution in the past two decades. We’re looking forward to talking with Mark Gray and really getting into how AI is impacting that evolution and what’s next in the world of talent acquisition.

S5 E45 | Recruiting Community: Mark Gray and the Evolution of Recruiting with Real Data

From fax machines to AI… recruiting has seen a dramatic evolution in the past two decades. We’re looking forward to talking with Mark Gray and really getting into how AI is impacting that evolution and what’s next in the world of talent acquisition.

Chris Hoyt, CXR 
Are either of you friends fans, or the show friends used to be on? I’m thinking to Gerry packing up and he comes up from the basement. Could he be wearing any more clothes? I don’t know you’re gonna do it.

Gerry Crispin, CXR 0:19
I don’t know. But you know, it’s, it’s, it’s time. So you know, I’m gonna go do it. And, and I’m not going to start until really after Christmas. So

Mark Gray, Invisible Technologies 0:32
I’ve got a plan, probably not the best plan to sit on a live call, but take like a first like couple of boxes of things that like you really cherish that are really important to you. And then just burn the highest time, because then you’ll get the insurance check. And then you’ll get all the money for the items and save the house and then you can buy new items. You don’t have to move it anyway. So the money on the movers, you’d save mental health money, and you probably get an extra couple of bucks for your troubles.

Chris Hoyt, CXR 0:59
So …

Gerry Crispin, CXR 1:00
Excellent idea, but we are being recorded.

Chris Hoyt, CXR 1:02
Wait did we just go from maybe sneaking some stuff out of the house that we didn’t want him or two insurance fraud zip

Mark Gray, Invisible Technologies 1:12
don’t forget all right, Chris.

Gerry Crispin, CXR 1:15
I’m in over.

Chris Hoyt, CXR 1:17
I was never here. I was never here. Are we ready? Talking about AI and recruiting? Yes. All right, here we go.

Mark Gray, Invisible Technologies 1:26
Welcome to the CXR channel, our premier podcast for Talent Acquisition and Talent Management. listen in as the CSR community discusses a wide range of topics focused on attracting engaging and retaining the best talent, we’re glad you’re here.

Chris Hoyt, CXR 1:55
Okay, if you’ve just joined us, welcome to the three different stages of a beard podcast, we’re excited to have you here I am Chris Hoyt, your host for the recruiting community podcast, president of CXR. And I am excited we do these every week, sometimes a little bit more, if you’ve never dialed in, to listen, and we do, we do actually stream these live on LinkedIn, YouTube, Twitter, Facebook, and of course CXR.works/podcast. But if you’ve never joined us, this is where we bring in folks from within the recruiting industry, they may be practitioners or leaders or folks that are doing something in the space, maybe in the services side, to talk about what’s top of mind for them, what’s keeping them up, we try to keep these to about 20 minute conversations. So they’re pretty snackable easy to get through. The beauty is if you’ve joined us live on some of those platforms, and there’s a little chat window, you can jump right in. So we do our best to show you off if you do that. But if you’ve got questions for our guests, we asked you to just drop those in there or even comments on the stream. You can do that too. We’ll do a little fancy overlay on the screen. And we can share that we’ll read those out loud for those who may be listening on a treadmill or Stairmaster or peloton or whatever. And as a reminder, we don’t do ads on the show, it is a labor of love doesn’t make us any money. We’re just doing it because it’s kind of fun. But we like to promote the work that we think makes a difference in the space, people that are just doing cool stuff, shining a light on it. And I’ll remind you been doing this last couple toasts because it’s a weird time right now, in the industry. And of course in the year tough time to lose your job. So if you do know of somebody in the recruiting space, who’s been hit with layoffs, downsizing, displaced, we’re gonna we’re gonna ask you to point them over to CXR.works/jobs. Now we update that list daily. That’s from over 100 companies that are that are recruiting for recruiting related roles, it is just recruiting jobs, that should be in that list. And I think as of this morning, there were nearly 200 jobs listed there. We have a little hiccup today on the map. So you can ignore the map at the top I think that shows 10 in the world. But we got quite a few more they’re seeing flipped on there. There’s a new search that’s been added as well. And notifications. If you don’t see something today put in a keyword save a search. And you’re able to set that up so you get notification. So with that I want to go ahead and jump right into it because we’ve got kind of an interesting topic, you’re gonna hear the word moneyball and if you’re in recruiting, you haven’t heard it for a while. It’s kind of been on the download and out of the space, but I’m gonna bring in Mark Gray and for those who don’t know Mark is the head of hiring at Invisible Technologies. Mark, let’s bring you in and out of the green room. How are you?

Mark Gray, Invisible Technologies 4:22
Good Chris, how are you?

Chris Hoyt, CXR 4:24
Good. Welcome back to the podcast. We did a top secret podcast a month or so ago that for some reason didn’t stream so this is technically your second time here.

Mark Gray, Invisible Technologies 4:35
Yeah, I’ve memorized the script from last time so we just need to time it exactly. So we can do a layover.

Chris Hoyt, CXR 4:42
Same thing. Yeah. So same graphics overlay will bring in the production. And welcome Gerry. We’re glad to have you on the show today.

Gerry Crispin, CXR 4:51
Pleasure being here.

Chris Hoyt, CXR 4:52
All right. Gerry is gonna have a lot of questions and we are if you’d if you know what phase of the beard everybody’s in, you can go and drop that in the chat too. We’re happy to hear that So So Mark, before we jump in for those who don’t know who you are, and I guess, invisible technologies as well, because you guys kind of no pun intended, you kind of fly under the radar for a lot of work that you do. Why don’t you give us sort of an escalator pitch of who is Mark, and why should we be paying attention to Mark today?

Mark Gray, Invisible Technologies 5:21
Yeah, so I’ve been in the hiring space for 14 years, mainly in the tech startup and scaled space. For the last six months I’ve been with Invisible Technologies. So Invisible is essentially the business within your business, we can still operate under the radar. We’re ops as a service or scale as a service, we essentially automate processes, in any business, any industry any vertical, whether they’re super simple, or very large or complex. And we essentially take all the repetitive work from your team, and kind of manage that ourselves. So that the people you have in your business can focus on being creative and adding work leads to a very interesting business with a very different ethos.

Chris Hoyt, CXR 6:12
And what about yourself, Mark, like a little bit of background on you, like how long have you been at Invisible? And where were you prior to that?

Mark Gray, Invisible Technologies 6:20
Yeah. So for the last 13 years, I’ve been in, you know, anything from a four person startup, scaling that up to 250, to some of the kind of larger tech companies like Zendesk going through their European and APAC expansion. So I’ve been all the way at the, you know, bootstrap startup, to the kind of luxurious tech offices where everything’s free, and you’ve got like 15 types of ham in the fridge. That always sticks in my head. That’s when you know, you’re in a very fancy tech company, you’ve got a ham variety, not just beverage variety. And then yet for Invisible for the last six months, and hiring it Invisible is very different. Because we have three types of people or groups that we hire. First, we have partners, who are kind of equity holders, usually in senior leadership roles. We have specialists who are, you know, usually in a very narrow focus, very narrow category of work. And then finally, which is what’s the bulk of the organization is what we call agents. So agents are individuals all around the world. So we’re fully remote, no offices company. We have agents in 74 countries at the moment, who log in every day into our platform and help our clients automate them. So yeah, it’s fast paced, it’s it’s huge volumes of times in terms of hire, and doing anything from hiring kind of general operators to AI traders, you know, there’s a real broad mix and the type of profiles we’re looking for. And to your point with moneyball, is how can we utilize data statistics, some IO, psychology, some social sciences to kind of model out, what does a really good person and function X look like? versus someone who might be better in a different function? Or in function Y? And how can we kind of create those baselines using kind of pure data so that not only the invisible know that they’re getting something that’s going to really succeed? But arguably, even more powerfully, you can tell the candidate that, hey, look, based off these, you know, 42 variables that we’ve pulled, we can actually say, to a high degree of certainty that you’re going to be really successful at this. Or, you know, hey, actually, you should consider this because we think you’re going to be really good at this. And yeah, and I guess that’s, that’s kind of the broad strokes of what I do.

Chris Hoyt, CXR 8:55
Yeah. So it’s funny, because we, you know, we sort of joke about that moneyball term. And I think when when data really hit the scene for recruiting, right, and Moneyball, came out, everybody had a presentation called Moneyball recruiting. All of us want to be to the Jonah Hill or the Brad Pitt of that of that story. And forget it. I forget the author right now just get built. Billy. Does anybody remember?

Mark Gray, Invisible Technologies 9:18
Oh? God, who wrote the book? Yeah, haven’t had it in here. So Billy Beane, was Brad Pitt’s character, but yeah.

Chris Hoyt, CXR 9:28
So I’ll have to pull the book up, too. For the author. I’m a little embarrassed but but anyway, all of us wanted to sort of be in that. And I think a lot of recruiting organizations felt like they were really, really taking that Moneyball approach, but I’ve walked through some of the stuff that you’ve been doing and working on and I think now we’re years later and we’ve got all of this, you know, all of this muscle behind AI that allows us to really create some insights and make some real decisions together, can you without giving away the formula, right secret formula, everything that’s going on? It doesn’t open Can you share a little bit around what why it’s different now as opposed to maybe five years ago, when we we all hoped we were doing Moneyball recruiting like what’s different.

Mark Gray, Invisible Technologies 10:09
I think now, the the kind of proliferation of technology in general, and how quick and cheap it is cheap might not be the right term, but more affordable, maybe is a better term, getting access to these platforms, and then pulling the data off it. So you know, within minutes, we can pull a huge amount of information on a candidate from whether, depending on the product you use, whether it’s a video record based product, whether it’s a tech based product. But also I think we’re just getting much better at understanding what performance actually looks like in certain functions. That’s not to say that there’s some roles where it’s still incredibly difficult, you know, software engineering, what’s a good software engineer? How do you quantify that it’s very, very difficult. You know, the other end of the spectrum, you could argue sales rules much easier because the output is very clear and tangible. And then there’s rules that replicate that, especially in invisible where the, how we classify put measure, I put it was very clear in some of the both agent partner and specialist tools. So once you have the baseline, then it becomes an easier fix long term, especially if you’re hiring at scale or at fault. Because the more you hire, the more data you have, the better your model is, the more accurate it is, uh, you know, it’s that kind of much more of a kind of easier cyclical effect of going like, Okay, I think this might be wrong. Well, actually, no, the new batch of people we just hired just says, Actually, it is correct. You can keep monitoring this over a period of time.

Chris Hoyt, CXR 11:45
So for that to work, though your baseline needs some validity, not not just, I’m not the expert here, right. But but not just here’s what I think a good, you know, sales account manager or, you know, whatever an X role would do, I’ve got to have some information that’s proven, at least within my own organization, right? Like, how does invisible go about that? Or how long does it take to sort of put put a valid baseline together like that?

Mark Gray, Invisible Technologies 12:12
Yeah, there’s a few. I think one thing you have to factor in is like, the prices law, which is the square root of the total amount of participants accounted for 50% of the output, which is also why, you know, the impact an individual has, as a company skills actually increases. So we’re just kind of you wouldn’t think it but you know, if you think of the amount of home runs hit by baseball players, like I don’t know how many baseball players are on their roster, how many teams you’ll see that it’s actually you know, it, it applies in everything, amount of records sold by artists, you know, it doesn’t matter. So if you play that to an organizational level, and then like a department level, so we can go, Okay, there’s 100 agents in this team. 10 of them are accounting for most of the automations. And then when we look into the data, like, actually, we can see, it might not be a perfect 10, it might be like, you know, the 8.97 or an 8.45, or something close, let me go get here the eight that we want to kind of replicate. But for this to be a fair assessment, we’ll do the test on all 100. From that, we can then break it down. Okay, here are the Top 10% Top 25 Here’s the midpoint, here’s the bottom 25. And then we can start looking for patterns and analyze that against it and the validity of our statements. So we can go okay, big five traits. Is there an impact on openness or conscientiousness? On certain performance groups? Yes, there is. Okay. Well, that’s an important factor. Is there a factor in task variety, which is like 10 Different varieties, which is 10 things that measure how individuals approach tasks? You know, do they prefer the same task over and over again, do they perform a variety of tasks are they autonomous, you know, all of these things we can start to measure. Then once we have that, we have like a very straightforward baseline of like 18 variables. And then you can add others like okay as English requirement, or you can do English test is, you know, in our hiring because we’re hiring all over, they have good Wi Fi, that’s a requirement, that’s a variable that we have to consider. And then you can kind of plug this in, and then you can start building out kind of tabulated scores which removes the kind of gut feeling aspect of hiring completely, but it also means that we can hire at scale with a very small team, you know, the on the agent hiring team, there’s, you know, me running it. Whilst we look for a director of agent hiring, you know, shout out if you’re interested. There’s,

Chris Hoyt, CXR 14:47
We’ll throw that out there. Everybody wants to reach out to you.

Mark Gray, Invisible Technologies 14:52
And there’s two recruiters and to give you context of how well this is working with two full time recruiters ers, basically the other side of the world. So our team’s geographic, we hired 361 agents last month with 2 recruiters. And the reason we can do that is a the data doesn’t lie, be the model keeps improving. See, we have built a lot of automations in greenhouse. So that there, it kind of removes all aspects of the candidate to next stage, it’s like, well, if candidate hits X score, they automatically get moved to next stage next assessment sent, or it’s sent to the coordinator at a scheduled time with the hiring manager. So we’ve kind of really overly optimize the hiring funnel, so that, you know, 400 candidates come in, and we know okay, well of that 400, maybe ad will make it to this stage and that stage and that stage, and we’re getting better and better at predicting them.

Chris Hoyt, CXR 15:50
I have to tell you, based on a conversation, Gerry and I had recently, I suspect, we know about roughly 130 heads of talent that would say that’s not over optimized. That’s just about right.

Gerry Crispin, CXR 16:03
Yeah, you know, there’s, I mean, I love it. And, and the fact of the matter is, you know, we’ve been doing these kinds of things for over 100 years. The problem is, the access to the kind of data is what’s really changed. So it seems to be mark that one of the things that really is advantageous for the kind of business that you’re in, is your ability to tap into the data that can come in literally in real time, and be able to use that data to move things forward, as opposed to the ways people would have collected it 10-20-30-40 years ago?

Mark Gray, Invisible Technologies 16:44
For sure, I your ability and the amount of people required to claim that data. Yeah, if you think about statistical modeling 10 years ago, you know, so…

Gerry Crispin, CXR 16:54
So let me, let me let me ask one key question, though, from my perspective. So once once you have acted on the basis of what is the equivalent of concurrent validation, do you do you then track or follow the success and measure the relative success of those folks that you’ve now hired? So that you demonstrate if you will, that what you’re doing is predicted

Mark Gray, Invisible Technologies 17:20
10%. So anyone, anyone that we’ve collected information on through the hiring process, even if they leave, we hold on to them? Because we want to start understanding what that pattern looks like, you know, is there a certain predisposition for people to leave this role or function as a result of some of the data we’ve captured? Or, you know, is there something we missed? Are they leaving, because they’re frustrated? Because they can’t do well the job? Well, then that’s something for us to kind of look for, kind of, in the margins, to understand why is this happening? So it is this constant, you know, the more we hire, the more information we have, the better we get at actually being able to place people in the right agent function, or the specialist function for that matter. So yeah, 100% otherwise, you know, it’s just, you know, okay, this sounds about right, off we go, let’s just keep the same model for a year, we have to be constantly upgrading and changing.

Gerry Crispin, CXR 18:19
I would hypothesize that very often what we’ve done is over balanced the decision process, from the employer point of view on will, can they do the job, which is really a lot of the variables that you’re talking about collecting. And one of the issues that I think is the choke point, is the other side of that decision is the decision of the candidate often lacks information that might have influenced their choice to accept the offer, if you will, knowing perhaps that the person they’re reporting to is an asshole as opposed to a wonderful developer. If the information is left off, it may impact not the fact of whether they can do the job but will they do the job long term and fundamentally if you’re capturing some of those kinds of elements long term you’re improving not just the DIS the the ability to to identify the people can do the job, but you’re you’re increasing your ability to actually provide better information to the candidate to make a better choice.

Mark Gray, Invisible Technologies 19:33
Yeah, no, that’s a great point and it’s called a god I’m gonna butcher this but text model for personality trait based performance, you know, something very boring and academic, actually, like hits upon exactly what you’re bringing up is. So you have the you know, at the top of the individual’s personality, and then on the left here, you have, you know, the function of the work the team And then you can argue like psychological safety, how much control does this person have over their job? You know, how much of the decisions can they make? mental well being, there’s a lot of ways you can interpret that. And then that impacts their job performance, which then links to their intrinsic and extrinsic reward center. And then it just constantly loops. So that yeah, the 100%. Right. And that’s something we’re trying to understand that as well, it’s kind of team dynamics, are certain people with certain traits are more qualified to work with managers with certain traits than others? The problem is, it’s extremely complicated. And I don’t think we have the processing power to be honest.

Gerry Crispin, CXR 20:38
yYou know, it becomes complicated as you increase from, you know, not just the decision of the hiring manager, but now the decision of the candidate. And now the decision of how does this all fit together in terms of team dynamics, because nobody does a job by themselves anymore? At least very few do, most of us are doing it in collaboration with a team. So understanding that team dynamics may be that that other band of success in terms of predictive validation.

Mark Gray, Invisible Technologies 21:09
Yeah, one thing we are looking to do is with certain projects that are much larger than others, and there’s obviously much more teams that we can look into. So what we’re trying to understand is our if we look at, let’s say, 100 individuals, and let’s say there’s 10 teams of 10, there’s not exactly it’s a bit more varied, but we can then go okay, within those 10 teams, there’s high performers, there’s midpoint performers, and there’s low performers. But are there any clusters, whereby the median and low range is significantly higher than the other teams? And then you can go, okay, is that result of the management team? Or is that a result of team dynamics or as a result of what the 10 people in this team are actually much more better fitted for the role? So this is another bit of like, diving that we’re going to start do early next year, there’s a few things we have to have in place before we can really accurately dive into this, but it’s probably the next chapter of what we’re looking to do, which is really interesting, because it’s like, Well, okay, we believe that it’s because we’re really good at hiring that we bring these people in, they’re doing an amazing job. But is there you know, the team dynamic factors, which is okay, the managers exceptional, or the way the team is clustered, works really well for specific reasons. And then, you know, diving in and try to understand what that reason is. So there’s like, so much we want to look into, and try and understand. Because I think just going hey, yeah, we’re amazing in our jobs. You know, that’s why we’ve hired such great teams. As much as an ego pattern is I know, it’s just not the reality. There’s so many more forces at play.

Gerry Crispin, CXR 22:44
So we’re having a lot of fun.

Chris Hoyt, CXR 22:46
Yeah, I mean, it occurs to me, you are you are you are creating, you can while you’re getting rid of historic recruiting challenges. With this sort of new way of recruiting, you’re creating new recruiting challenges for yourself. And I would imagine that one of those, the biggest might be the data collection, because you mentioned earlier 40 plus points, right points of interest or points of data on a candidate, I would assume that’s it’s easier to gather internally, but then my mind my wheels start spinning like, how are you collecting all of that information? Certainly internal. Are there automated touch points throughout my my career and Invisible? Is every project wrapped up with a with a survey or a report out? And that’s, that’s a lot of information to be pulling, and then you’re talking about team dynamics? That’s a whole nother set of data collection.

Mark Gray, Invisible Technologies 23:34
Yeah. So some of our happens on the application stage. So as I mentioned, you know, like, you know, Where are they based, Wi Fi speed. Three or four more, emptied my brain right now. And then at the application phase, there’s the, in some rules anyway, there’s like a written part, a written assessment, which gives us some indicators, but also there’s a video AI interview component. And then obviously, there’s performance data, which, you know, happens every two weeks. And then, you know, obviously, within that there’s additional sets of data. So it does keep getting bigger and bigger, and that we’re looking into the main thing is like, how can we gather this without it becoming a burden on the candidates experience?

Chris Hoyt, CXR 24:21

Mark Gray, Invisible Technologies 24:22
So it’s kind of like, what’s the greatest thing you could tell her? You know, someone in recruiting say, well, the greatest interviewers are the ones that conduct an interview and the candidate walks away go, Well, that was a great conversation. And it’s kind of the same thing with gathering data. It’s like, how can you take it without being like, hey, you need to spend 30 minutes on filling out this form for, you know, endless amounts of questions. You know, we don’t want to do that. And there’s a lot of give and take. So like, well, take some data from them. And then we’ll like jump on a call and go Well, this is why Invisible is great. This is why it’s interesting. You know, what are you looking for great. Okay, well the next steps this we take a bit more and then you It’s about competencies.

Chris Hoyt, CXR 25:02
Is that data that’s collected? Sorry, Gerry, I got one more is that data that’s collected with regards to the DE&I front. So looking for from an inclusion and an equity standpoint within the organization, is that is that also get get pulled into that that calculation?

Mark Gray, Invisible Technologies 25:22
Yeah, so we pull that I’m excited about it, we actually pull that I’m excited about the hiring process that happens after someone kind of comes on board through our hrs. We don’t, we were at one point in looking at the impact of country, culture and attitude towards employment. But like that was just a rabbit hole we didn’t want to touch because it was like, way too complicated.

Chris Hoyt, CXR 25:50
I can see you getting lost in that pretty quickly.

Mark Gray, Invisible Technologies 25:54
Yeah, I was just like, Yeah, I’m not touching this. But yeah, I think it’s, you know, at the moment, we have 74 Different countries from agents. And then I think the organization as a whole isn’t like 77 countries at the moment. So like, it’s pretty much we’re trying to get everyone in the world, if you know, any good recruiters in Antarctica, that’s what we need to check off soon. So

Gerry Crispin, CXR 26:20
That’s pretty cool. I don’t want the one question that I had left to ask at the moment is, is you’re not obviously hiring every single person who goes through the process, you’ve you’ve improved, obviously, from an efficiency point of view, so that your funnel is better organized from a shape point of view. But those folks who do not go forward, what is your practice or policy in relation to how you help them better understand what you’ve learned about them, that suggests that we should not go forward.

Mark Gray, Invisible Technologies 26:55
So at the moment, depending on the role in the function, we’re actually able to give a very clear reason why we’ll be like, Look, you know, one of the processes we’re running now, which is actually quite a big project, is we can do a very clear assessment on natural language processing. And from that, and their explanation as to why they approached the task the way they did, we have a pretty good, like a pretty high success rate of understanding that people that will succeed or fail, and we’re very open about that feedback, we’re like, look, unfortunately, you didn’t succeed. And what historically we’ve seen from individuals that come on board that don’t do to wellness assessment is they struggle for a few months and leave. And we, you know, obviously, we’re putting it in a very nice way. But essentially, you know, we don’t want to bring you in for three months for you to just leave and be upset. What we want to do in the long term, I don’t know, if we have three minutes, I’ll rattle through it. We want to create a non stop nurture campaign. So the more data we get, the more we start to understand rules, functions and outputs from a data perspective. Well, if a candidate comes in, and they’re not a fit for anything, we have no, we can actually already tag them and go, Hey, you’re not good for this. But these five projects, we think you’d be brilliant for, we don’t know or have a timeline as to when more slots are gonna open up. But when they do, we’re definitely to contact you, we create a tag for that candidate. And the second, we open a new role. For any of those five projects, everyone tagged on that gets auto sent an email saying, Hey, we actually have 10 openings on the team, we have openings, let’s set up a time to talk. So once again, we’re just trying to constantly want to say recycle candidates, but I think a lot of companies waste opportunities when people kind of show up and they’re like, you know, not a fit now reject or, you know, put them in a nurture campaign. And we’ll send like one email a month about the company. No one ever gets converted. So we want to constantly be evolving on how we can bring people in and kind of keep them in the loop for however long it needs to.

Gerry Crispin, CXR 29:04
Cool. Thank you.

Chris Hoyt, CXR 29:05
I love it. Oh, Michael Lewis. Is Michael Lewis,

Mark Gray, Invisible Technologies 29:11
Michael. Michael Lewis.

Chris Hoyt, CXR 29:15
Click. Well, okay, so Mark, I want to ask you, as you take us out, if you were going to write a book about the state of things right now that you’re working on, right with the AI and recruiting, and you can’t use the word Moneyball. So if you’re gonna write a book about that, what would the title of that book be?

Mark Gray, Invisible Technologies 29:35
Cash Sphere

Chris Hoyt, CXR 29:41
I guess technically that counts.

Mark Gray, Invisible Technologies 29:43
Yeah. What would the title be? Well, it depends if I want to be. It seems very in vogue right now to have like very inflammatory book titles that are very, that are very inflammatory and topics are flammable. So it’s like You’ve Been Hiring Wrong…. no I think it would be. I actually I believe this is probably why I wouldn’t write a book that couldn’t even think of a title. Oh, yeah. How to fix all the world’s problems using data? And there’s the thought behind that. Yeah. Calum market is arguably the most inefficient market in the world. And it costs I think, well, there was a cost US economy 20 billion a year, I think in lost productivity. So if you save even a fraction of that productivity, you know, that fixes roads, more charitable donations, if you implement that throughout the world, and there’s like, you know, less and less, less inefficiency in hiring, and people are actually happier. Pharmaceutical industry is going to be upset, obviously. But you know, everyone’s going to be happier and doing better work and actually enjoy the work. So yeah, there you go. Fixing All The Problems. Doing and doing it. Well. There you go.

Chris Hoyt, CXR 31:14
Alright, so who gets get your first sign copy?

Mark Gray, Invisible Technologies 31:19
You guys, you guys wrestle over it?

Chris Hoyt, CXR 31:23
You’re in wrestling. We’ll do some sort of some sort of.

Mark Gray, Invisible Technologies 31:27
Sounds good.

Chris Hoyt, CXR 31:28
All right. Well, Mark, great to have you on technically, again, we were super excited, much gratitude for you cutting out your schedule. I know you’re super busy. So we’re really grateful that you were able to join us today. Thank you so much.

Mark Gray, Invisible Technologies 31:41
Ppleasure was all mine. Thank you so much, Chris and Gerry. for pleasure.

Chris Hoyt, CXR 31:44
You got it. I’m gonna shove you guys over in the green room hang out for a little bit. We’ll be right back. All right, really quickly, I just want to remind everybody, if you have not checked it already, head out over to CXR.work. See if your organization qualifies to join we got about 130 companies and brands that is over 5000 recruiting leaders and professionals that are part of the CareerXroads community, we know what we’ve been doing, we’ve been doing it collectively for just about 30 years. And also a last reminder, even if it’s not you that’s been displaced or impacted by layoffs. If you know a recruiting professional that’s looking for work put them to CXR.works/jobs again this morning 200 some odd recruiting jobs out there from some pretty well respected organizations and companies. And with that, I think you’re gonna be excited as we head into the holiday season we’ve got some best of sessions coming up so you’re gonna get to hear our team’s selected some of the best of podcasts that we did this year and you’re gonna get to hear those with an intro and find out why they thought they were so awesome. So with that we’re gonna cut out and we’ll see you guys next week. Thank you so much

CXR Announcer 32:49
Thanks for listening to the CXR channel please subscribe to CXR on your favorite podcast resource and leave us a review while you’re at it. Learn more about CXR at our website CXR.works facebook.com and twitter.com/CareerXroads and on Instagram @career X roads. We’ll catch you next time.