Hire the Outcome, Not the Resume - Desiree Goldey and Ashley King

[00:00:04] Oh my gosh, Ashley, we are here in Nashville. Yeah, yeah, yeah, yeah. We thought we'd bring it to you live. You're welcome. Anywho, today's show, by the way, is sponsored by Round One. Yes, let's hear about it. And if you don't know about Round One, Round One is an AI screener that keeps humans in the decision

[00:00:34] making process as we all want to do, as we talk about on the show consistently. So please go check them out at roundone.ai. Very exciting and thank you so much for Round One sponsoring us to be here. Yeah, I will say as a recruiter, I use note takers all the time to help me really, really indulge in the conversation and be able to listen and be attentive to my candidates. So all of y'all check out Round One. It's a good product. Fantastic. Do you have a funny question for me today? Of course I have a funny question. What's, uh, just cause we've been traveling

[00:01:03] in today. What is the weirdest thing you've ever seen on a plane? Oh my gosh. Like this is such, yeah, this is a very open. This is too open. I was about to say you opened up. Close it back. Close it back. But go ahead and just tell us everything that's open. So I will say the most crazy was the guy who like fought with the attendant and had to get thrown off cause he was so drunk and hammered. And then he threw up on her. I was going, I was coming back from San Francisco. And this guy was like, already, you could tell

[00:01:33] that he had gotten way too hammered at the bar. Yeah. And then he like got, he was just out of control. Even in the line, you know how you board? Yeah. And he was like kind of swaying. He's bobbing. He was doing the bobbing weave. And he finally got in and he was just so belligerent. And they were throwing him out as they're like pinning him on the ground. He like, you know, did the full projectile. It was great. That's disgusting. And you know, it's so weird cause human behavior is so weird. Everybody like clapped.

[00:02:03] Oh, to get him off. Yeah. I was like, why are we all clapping? Because it's the societal menace just left the building. That's why. And of course I'm there like. Yeah. Leading the charge. The first clap. Always be the starter clap. Who are you like the clap? Yeah. All right. So how about you? So I actually, as, cause I knew you were going to ask it back to me and I was like, I actually can't even think of a time, but I can. Yeah. I took spirit airlines one time. This is my story.

[00:02:32] It literally, we were on our way to Colorado and this girl had ordered drink after drink, after drink, after drink. And they were there for a birthday party here and her and all her girlfriends. Right. They were sitting right behind us. And the lady was like, you need to sit down. We're about to land. You need to sit down. If you don't sit down, we're going to have to go around loop. So we went around a loop again for this girl. And she's like, I cannot sit down. I am pregnant. And we were like, you just had four things of alcohol. And her friends were like, you're not.

[00:03:02] And so it was just like this thing where like this woman just thought she could get out of everything by being pregnant. And, um, we all just went on a 30 minute loop with this. Is she, isn't she like, should we have served her? So it was quite a fiasco, but in the end she was able to drink, drink. She was in fact not pregnant. She just did not want to sit down. So weird. People are so weird. That's Spirit Airlines, dude. Free advert. Sponsor us. I don't actually think they exist anymore, which is right up our alley.

[00:03:30] Oh, they don't? Yeah. I think they're done, right? Aren't they like owned by the people now? Oh, they're owned by the people? Yeah, the guy was like, if they go out of business, we're going to buy it. And it's like, everybody's pitched $40. So we all going to be, I did it. Sign me up. Own a plane. All right. It's not really how it works. Not the point. I was about to say, not at all how it works. Okay. So moving back. Let's jump in. Let's do that. So we thought we'd bring you something today that is a little, I don't know, right on par for us.

[00:03:58] But I also think it's a little bit how we talk about as we go into Rackfest and seeing all these recruiters. And the spirit of Rackfest this year is not to be talking about AI and not be talking about, to bring a human back into talent, right? And so I think this is a really good one. This is about hiring outcomes and how we should be basing hiring on what the outcome that candidate could bring,

[00:04:23] essentially, right? To instead of focusing so much on what they're doing, what their skills they brought before. Yeah. And so why don't you lean us in a little bit about this topic? Yeah. So this topic, it actually came up mainly because so many people are talking about AI right now. And so many companies and candidates are adding AI into their process as a facilitator, as things like that. And right now in this moment, we kind of have a few options, right?

[00:04:52] So like there's this option where we lean out of AI. Like let's pretend we go down the route where everybody in a year is like, this sucks. We've run out of water. We're going to lean out of AI for hiring. Then there is the leaning in. So everything becomes that waterbot circle where it's your AI talking to my AI to evaluate your AI to see if you can finally make it to a human. And then there's this kind of like, if we stay steady, which if we stay steady, then this is exactly what it looks like, right? Right.

[00:05:19] So it kind of brought me to this concept of like, okay, if we lean in, that's a scary thought. I'm not ready. If we stay where we are, we know what that is. But what does this actually look like if we lean all the way out? Because right now so many people are creating processes, assessments, tools, and things like that that are all AI based to where I feel like we're getting away from the art of how do you actually juxtapose talent? Right.

[00:05:46] How do you actually compare two different backgrounds, two different experiences, and judge who would be better for the same job? How do you actually do that? And again, I feel like the more we get entrapped in this circle of using AI for all these things, we're getting away from that art. And so this episode is really to talk about how would you hire if AI is not involved in any of it?

[00:06:09] How would you hire if the way that we juxtapose candidates was actually like a thorough and thoughtful process and the way that we would want it to be done for the job that they're looking for, right? So that's kind of what today is about. Yeah, but it's an interesting thing, right? Because I think this is one of those where I have to kind of play devil's advocate. We were doing this before, technically. In theory. Wait, I was about to say, in theory. Well, there was an AI, right? Yeah. I mean, there was AI.

[00:06:38] AI just did not start yesterday, people. But yes, there was AI. Start the day before yesterday. Get ready. The AI. But we didn't involve it as much in the process. Yeah. Right? Maybe two years ago. Yeah. It's, you know, evolved over time. But supposedly, we were supposed to be doing this work before about evaluating candidates and saying like who's, even if it was on paper, let's just take it on paper at face value. That was a career job, right? To say this one is better than this one versus.

[00:07:08] And then as they move through the interview process, we were supposed to be able to assess those candidates. Now, were we doing that on outcomes and the job that they would be doing? I don't know. Yeah. I would say no. So, I agree. So, I think that you, we've talked about this before, how like hiring in general has changed and transitioned so much throughout time, right? So, like whenever you first look at quote unquote employment, like first of all, that's like years and years ago.

[00:07:36] So, we're not, we're going to skip over that. We're going to graze over that. But like you should look into that because that's, there's a lot of ties. But you'll hear me most of the time on the podcast and think I'm a cuckoo banana. So, we're going to keep it cool because we're live, all right? Live with- Cuckoo bananas. Yes, always. But essentially, we've talked about how it's gone from this network-based, who you know, hiring to this, okay, this skills, abilities, and competencies hiring, which is very much kind of a potentials-based hiring, in my opinion.

[00:08:06] Because you're basing it off of data points that you've extracted that you think are valuable based on you. Like, again, like, hmm. And it's like, you know, just a good wishes hiring. Well, there was a pause there for a reason. Yeah, there is a pause there for a reason. But, so the next step that you have is outcomes-based hiring, which is when this person would be in seat, what would be the outcome of that?

[00:08:33] And judging based off of what that finished product would be lets us know who would be the better person to be hired in that spot. Yeah. You know, what's funny, as you say that, I was thinking to myself, yeah, I would love to measure for the outcome that someone's going to bring to this organization, whether it be revenue, with their influence on revenue, all of the things that I tell people to measure all the time in the work that I do.

[00:08:58] But the thing I struggle with still is that hiring managers, if they can't define what they want the outcome to be, how are we measuring even the outcome at the end of the day? Like, it's this horrible cycle of nonsense, right? It truly is. And a lot of this starts, and I would say almost actually all of it starts with talent infrastructure. Right.

[00:09:21] And so talent infrastructure specifically, it's not just going to be just job analysis, job description, like it's not just your logistics. Your talent infrastructure is what are the actual duties and tasks that this person does day to day? Okay. How do we assess currently how that person does if it's good or bad day to day? And if it's not a job that they have currently, let's say it's something, because that's one thing is a lot of times, sometimes these are new headcount and they've actually never had a person in this job before.

[00:09:50] So then what you're actually measuring is the gap. Like, what is the gap that we're actually trying to get this person to fill? And that's your measurement. That's going to be our measurement tape is can they do that? And so those, I would say, have a little bit more agility. But whenever you're looking at something that's a replacement headcount, these roles are there, there should not only be fond articulation, but there should be measure points. There should be metrics because that means for every single person that you've had in seat, you haven't had a proper measuring stick this whole time.

[00:10:17] So if you can't do it for the job that you're opening, that means that you haven't been doing it performance wise for the people already in seat. I would argue that most companies don't do that. Don't have the measuring stick. They think they do. It's a theorized measuring stick. They would say, like, we're able to measure that person's effect on the revenue or why we even have the seat open. Yeah. But I don't think that's true.

[00:10:41] I don't think it really measures the deliverables they bring to the table or the outcomes that that person brings. I don't think there's a true measurement for that, but I will have you argue. No, no. I agree. So whenever I actually did this as head of performance and was like, what? And it's specifically looking at recruiters, to be fair, just to centralize it. So that way, you know, because jobs are jobs. There's so many. But so all of our listeners know. And so I actually had to be like, OK, how do you actually do this?

[00:11:10] How do we sit down and measure these specific steps? So there were actually four groups, four specific quadrants that we looked at. One was productivity. So that is what is your recruiter actually doing day to day? What are the efforts that they are putting in that is producing anything? So whether it's the messages they send, the searches that they do, whether it's how many times they put candidates in a different folder, whether it was continued out, whatever it is, we're measuring that.

[00:11:38] I want to see every single move that my recruiter is making as far as their productivity goes and different tools and LinkedIn and whatever it may be. The next one was the actual outcomes. So this is going to be so they've done their production. What is the actual outcome of everything? The reason that we did those actually right next to each other is because in outcomes, a lot of people love time to find, baby. They love time to fill, time to fill. Time to fill. That's their jam.

[00:12:04] I just had a Freudian slip because what I'm going to talk about is actually called time to find. Yes. And so the reason that we put those next to each other is because there is one data point that really slices through your productivity quadrant, and that is going to be your time to find. What is time to find? Time to find is retroactive data that whenever you look at the recs that you have filled on average, how long does it take you to find the person that you've hired? So there were some sales roles that they had worked.

[00:12:33] It took them about four days to find the person that they would hire. So that means the fourth day that this role is open was the day that the person who we ended up hiring applied. Why is this important? Because time to find tells you everything you need to know about your brand and what it's bringing in. Because if you have a recruiter that has low to no productivity, but their time to find is one to five days,

[00:12:58] they have such a popping brand for that role that they don't need to actually have high productivity. So whenever you're looking at this outcomes-based approach, it's almost like you have to look at what they've put in, what they've delivered, and what they actually even needed to do. Have they outperformed what needed to happen in order to create this? So it was something that we looked at there. The other two quadrants that we looked at was impact.

[00:13:23] So, okay. So you have your, what you've produced. You have what has been the outcome of that. Now, what is the actual impact? How long do these people actually sit and see? Do they attrit ASAP? Do they stay for years? Like, what is the actual impact of having you as our recruiter versus XYZ person? And so the fourth quadrant, which is right here in the corner of this mystical quadrant that I'm drawing. But we're live so y'all can see these.

[00:13:51] Because usually they can't. We're on a computer and I'm just like, Anyway, point is. The fourth one, I actually highly, highly suggest. So if we have talent leaders listening, monetize it. Monetize every single piece of data that we just discussed. So if we're able to see that every time they hire someone in sales, their time to find is three days. And these people stay on average three years. And our normal tenure is one. That's an excellent recruiter. And you're going to see it whenever their data is monetized.

[00:14:17] Because it's going to show you the effectiveness of your recruiter at a business level. To where you can go sit at any table in the business. And make a case monetarily. Impact wise. Outcome wise. And production wise. As to why your recruiters need XYZ resources. Why they are as good as they are. And why your team deserves whatever it is that they deserve. Or vice versa. Whatever it is that it may be. But these type of things, it's important to understand that whenever we're talking about hiring based off of outcomes,

[00:14:46] that means that you're going to have to diagnose how much of this outcome is brought to you. How much work is actually being done. And in that diagnosis is how you really find out, Well, how do I assess this talent now? How do I assess someone incoming to be a recruiter, knowing that we're going to look at impacts, outcome, productivity, and the monetization of them? And how do I actually bring in another recruiter knowing that and assess them to fit into this kind of performance law now?

[00:15:13] I was just having this great conversation with a workforce intelligent platform the other day. And the thing is amazing, by the way. And those kind of, you know, that geeked me out. I was like all over this crazy data by employee. Like, that's my itch. Like, it was like all these cool bells and whistles that were really doing some fascinating things. But one of the things I had talked to them about is how we even got in this conversation. And I saw the demo, which is not really released yet,

[00:15:43] was that we talked about decision latency. And we were talking about how one founder at a startup could hold up an entire whole thing. And the decision could be made, but we're just holding on to that thing because we're waiting on this one person to make a decision. And we were talking about measuring decision latency, right? And so I was, you know, went on my rant because it's, you know,

[00:16:09] my area of rant is this kind of operational sense of things. But what it tied back to was also how do you measure the outcome or what happens when you put a manager in the seat? Or what is that manager's team delivering their impact on something? And seeing those numbers, my argument back to him, because he was like, well, I don't, you know, I'm a geek. I love this data, but I don't know how to sell it.

[00:16:36] And I said, I bet you 90% of these people that you're selling to would love to see this data. But then they don't know what to do with it. Correct. Most people don't. So they can see the data and love the pretty whistles and they can see all the graphs and all the things and know that it's supposed to mean something. Yeah. And this is when I struggle with going from, when we're talking about hiring outcomes, because I think that people get lost in how to take that data and actually make a solution.

[00:17:05] Right? Yeah. Do you know what I mean? Like you can have, I know you know this. Yeah. I am. Do you know what I mean? Yeah. I am. I'm pretty sure. But like you, you, seriously, you give them all the knowledge like you were doing. I know that you were doing, giving them all the knowledge and then they take it nowhere and do nothing with it. And I think we always talk about it on the show is that we go back to the training of people,

[00:17:30] how to read data to me is an essential tool in the world of AI that we live in right now. Because if we can do everything faster and smarter and we can get all this data, which we can get this outcome data, right? Yeah. Somebody's got to be able to read it. And if you're a recruiter that can't read it. Yeah. Then you're in trouble because the AI can do everything else. Yeah. Right? So tell me like, what is your philosophy about, because I know that you were in a seat that kind of did this work.

[00:17:59] What is your philosophy about how you train recruiters who aren't used to seeing this kind of data? And what would be the hard switch we would have to make to make it an outcomes type of world? Yeah. Actually, it's a really great question because with my team that I had inherited, that was an issue. They did not actually know how to read data. They didn't even know how to collect data, how data is created or even what their inferences are of the data set. Right.

[00:18:28] And so I had to take them through their own kind of course. And it's very interesting because a lot of people, a lot of recruiters don't know, every single move you make is tracked. Right. Every single thing that you do is, it's a measurement, it's a notch on this cross wheel, and it can be quantitative and qualitative data, which I think a lot of people don't know the difference of. So just to...

[00:18:56] Oh my God, we have to go back that far. Well, they had to too because they don't know. Because you can have quantitative data, which is your digits, your numbers. How many times did you click this? How many times did you do that? It's a how many game? Qualitative is really where you find out everything. Right. Right? Like quantitative tells me what, it will never tell me why. Right. And qualitative is whenever you're talking about how do you create a solution. Yeah. Because so many people, even that dashboard that you just mentioned,

[00:19:23] they will look at this hard data, all these quantitative numbers and say, yep, we got it. We're measuring it. Okay. Silence. Why? Because there was never any qualitative data surrounding any of these numbers. There was no any, okay, we push this button 46 times and only got the result of one. Why are we pushing it 46 times? Why are we only getting one? And now this involves a story.

[00:19:49] Now this envelops, well, this and this and this and this human behavior aspect of it all. Right. And if you want to be good at predictive analytics, if you want to be able to hire based off of outcomes, which is a form of predictive analytics, essentially us saying that this job is going to, we're predicting that this is going to be what it is because jobs change all the time. And that can also change your stuff. And this person based off of this assessment that we're putting them in, we're predicting that this is what this will be based off of their performance and their outcome they've provided.

[00:20:18] There's this kind of, what is this called? I have no idea what that motion is that you are doing. We're going to keep it in the podcast though. I don't want it edited. All right. I'm thinking, what is this like synergy? Maybe I think, I don't know. To be honest, now we've lost the plot, but here's the point. It's hiring based off outcomes is better. Bye. No, here's this here. I was actually reading.

[00:20:45] There's a great post about the new world of talent. And just like they have AI engineers, there should be talent engineers. I'm sure they're on the way. Yes. I'm sure. I don't doubt it. Oh my gosh. I know. So it was a great post though, because it was really introspective about, because there's going to be this overload of data you have available at your fingertips. You have to be in and how to read it.

[00:21:09] And the good talent engineers, right, are going to be the ones who are succeeding at the top of the world because they're going to be able to take that data and actually do something with it. I believe I'm one of those people. I believe you're one of those people. But I do think that most recruiters still struggle, like you said, to figure out just the what is quantitative and what is qualitative data at this point. I believe recruiting is a lot of things. I think people know this from the show. I believe it's sales.

[00:21:39] I believe it's relationships. I believe it's. And I know that my co-host leans heavy into the data. But I do think that there is where we're getting to is there's going to be two things. It's going to be relationships and it's going to be data. There's going to be nerds and then there's going to be nerdier nerds. Right. There's going to be nerds and they're going to be nerdier nerds, right? And I think that's where we're getting to. And I'm fine with that, right?

[00:22:05] Because I'm fine to geek out on all the relationships and building the whole spectrum of candidates in a really real way that's not AI. And I'm also willing to dig in with the data and really understand the outcome that person could provide in the seat. And I think that's what it's going to take. It's the full circle of a human being's role in an organization. Yeah. Right. It's like everything they are to that organization.

[00:22:33] I would love for somebody to tell me they do this right now. So if you do this, please contact me. That they provide the 360 view of when a person hits the door to when they leave to tell me all the effects they had on that organization. I bet you that doesn't happen too often. Well, and probably not till they leave. But if you were to do a 30, 60, 90, like some people. But again, I feel like that variable changes, right? Yeah. And sometimes it changes based off the candidate.

[00:23:04] Like sometimes you have a candidate that's really good at X, Y, Z, you get them in seat and you're like, maybe we should let them in this room. Maybe we should allow them to dive into this a little more. And, you know, sometimes. And so those things happen. I think whenever we think about hiring based off of outcomes, what I'm really thinking of is we're moving to a world where, again, AI is at that top of funnel. So we're about to start getting probably seven page resumes because it's all going to be based off hot words if this person's AI is just going to sift through based off of who had what.

[00:23:32] So like so there's like that tiny conundrum. And then tiny. Yeah, I know. That's huge. Small. I've never heard that voice in my life. Really? It was great. I'm glad it was here. I'm glad everyone got to witness this actually. See, why are y'all doing this? Y'all making me lose my caboose. My thought caboose. Anyway. Anyway, you were excited because you, said that AI is going to have seven page resumes.

[00:24:01] Basically, AI is doing all these difficult things to where resumes are eventually going to lose their place too. Oh, absolutely. And if you haven't thought that they're already starting because people will be like, well, they put too many M dashes in that resume. So that person's going to be an AI profile. They're not even real. So it's like there's so much stuff to where it's like if you don't know how to hire based off of outcomes, you're going to be losing the plot pretty, pretty, pretty soon, in my opinion. And so that's the part that I kind of want to dive into is like, how do you actually hire based off of outcomes? How do you do that?

[00:24:30] And I know we've been diving into the infrastructure piece. Well, let's move to the other piece though, because I think we started this kind of move to this when we stopped telling people to write out their duties on a resume, right? We said, name your accomplishments and what you did. You're not your responsibilities exactly at that organization. Show me what you achieved on a resume versus like the nonsense we used to have, right? So we're starting to move that way, but go ahead. We are starting to move. So I do agree. It has been a very chronological, what have you done?

[00:25:00] To much more of a skill based, what have you achieved? And so that's a good thing because now it's a sample of what you've put forth, not what your expectation was. And those are two different things always. But I think what's useful in the hiring outcome, and again, we're going to have some feedback that people are not happy about, but if your true job is to find the best top talent, it is the only way to actually do that the best way.

[00:25:28] Because what we're saying is I'm not hiring you based off of your experience, your titles, your logos, your anything else other than how well can you do the task at hand? And that task assessment should be indicative, this is where it gets dicey, of the whole entire kit and caboodle, right? If this person can do this X, Y, and Z, then they thus can do this job. So that is where the hard part of hiring outcomes comes in.

[00:25:58] I think it's really tricky. It is. And I will say it's also very much a legal issue because if you assess people, and it's not reliable, it's not validated, but you're stamping on it, there are people who do personality tests. And they use the third-party personality test. And they would say, well, we're hiring based off this. You will get sued because of those personality tests are not validated. They're not like all these other things. Then it's not an actual true assessment. So a lot of times, a lot of people stay away from this because of that.

[00:26:27] They stay away because there's this fear that if they don't assess properly, which is wild whenever we're thinking about the fact that literally all they were doing before is being like, hey, is your name Joe? Okay, Joe. Hey, Joe. Do you not do this? Joe? Okay, Joe. Versus Joe, show me how you pick up a spoon. I don't know. What's the job? I don't know. Give me something. I don't know. Truck driver. Show me a software engineer. That's much better. I don't know how I would have showed you a truck driver. I don't know. But it wouldn't be good. Actually making them write lines of code.

[00:26:57] You see them do that. I don't know a single person that hires for a software engineer that doesn't have a technical portion of their interview. Why? Because you can take exactly what they're doing on the job, give them a much smaller condensed form of it, and evaluate their actual skill set within it. I actually think that you can do that in recruiting as well. I think that if I give you a sourcing thing, and I give you an outreach, and I give you, I'm going to get a pretty good sum up of how you run your desk.

[00:27:24] Like, I feel like I could create a pretty decent performance outcome recruiter deck. I agree with you. I've done them for jobs. I don't actually like them as a candidate. Oh, I was about to say, let me go down this rabbit hole. I knew you were about to. I'm about to tear you up. Which is wild, because you actually love interviewing with AI too, and I hate it. I hate it so much. She loves it so much. It's wild. I don't care, because I don't care. Because I don't care. Well, I mean, it's just like, I don't know. I don't like talking to anybody. I've never,

[00:27:53] if anyone even sent it to me, I'd be like, bye. Really? Oh yeah, I would not actually entertain them. Oh, it does not. And I work at round one. I do not. I do not hate it, because actually, I think it's very succinct. Okay. And I've had some really bad. Maybe I just have an interview with round one. Yeah, right. And I've had some really bad recruiters as well. Yeah, fair enough. And so I feel like, I don't know, which is worse, the bad recruiter or the AI. I don't know. I could go down that whole thing, but I'm not going to. What I was going to say about the assessment is,

[00:28:22] I don't hate them in a general scope. What I hate is, if I am in a job similar to, like, let's take marketing, for example, like, it's, I get that you can do a personality test, and you think you're giving me a cognitive test, by giving me all this math, and like, yeah, that's silly. Okay, I hate those. Also, what's the relevance here? I don't know. Like, objection, relevance. Exactly. Literally. So I think, I agree with you, that there are probably an assessment for every job. Oh, right. Probably. You could probably give one to everybody.

[00:28:52] They're not good. But I don't know that it's necessary to me, for every job. I don't know that it's necessary for every job either. But I do think, if you are going with your outcomes theory, right, if you say this is the right way to hire, then you have to do the assessment layer to me. You have to. You also have to. Those assessment layers also tie into performance. Right. They tie into how you promote.

[00:29:16] They tie into how you evaluate and measure anything that you even currently have in-house as well. So it's very, very much a thorough structured approach. And that is honestly what keeps people, I think, the most away from it, is because so many companies are reactive. They're not usually in a position where they have tied the skills, abilities, and competencies, made a through line to, let's say, a senior there and been like, okay,

[00:29:45] this is what's expected of them. Thus, this is what would be expected of you. Like, it's just, it's not done as thoroughly as it could and should be. And to be honest, a lot of times it's on the back burner because none of that stuff's a priority to it. I was about to say, the urgency. No, and so again, it's, I think this is somewhere where we'll get once resumes have finally lost their spot, then it bumps it up.

[00:30:11] Once AI really takes over the full first layer for all parties, it's coming up. Like, because there comes a point where if AI can do your interviewing, if AI, like, then AI can do the job. And so now what's the only way that we can assess between, should we just hire AI for this or should we hire a person? Then you got to get their butt in the seat and see what they can do. Right. Yeah. And so it's almost like an inevitable right now. I, as we're talking about, I remember whenever Kat Kibben,

[00:30:41] they were like, Oh, we won't have resumes in a few years. And I remember thinking crazy, crazy. Let me tell you something. I think they're onto something. I think that the way that things are going, it will be much more a prove to me what you can do. It's show me how to do math on paper. Cause everyone can use a calculator. That's the difference. And I agree with you. Listen, I think the resume should be, I just thought it was, should have been gone five years ago. I hate them. I mean, what would be the other? Like what is the,

[00:31:11] if it's not a one page marketing sheet of all your bullshit, then what do you actually send people? I don't, I don't know. Cause that was my question with Kat. I was like, what, what do we do? I think it's like a portfolio more than it is a resume. A LinkedIn page. I guess we have moved there. Kind of, kind of right. That's fair enough. Here's the thing I struggle with. I struggle as a person at 51 going on 52 to put everything I've done in a real way on a piece of paper.

[00:31:39] And get it enough for AI to read it. One page enough for the recruiter to read it. I don't know. I just feel like we should move. And LinkedIn profiles do do that. In the fact that you bring, you can have the resume piece, which is your experience. It's a consistent format. Right. It's a consistent format. Yep. It's every single person. And you can add in the things that give you flavor. This is what I always say. Right. You can add in your special interest. You can add in, I have my pot, this podcast on it.

[00:32:08] Like you can add in these pieces of the puzzle that would not go necessarily on your resume. So it's the whole person to me versus this resume thing. When I read my resume back, it's actually, it's actually comical to me. I know I'm getting way off the subject, but. No. But I mean, but it's true is like, first of all, people are not professional resume writers in general. So it's like, and the way that I describe a resume to people is like,

[00:32:36] this is your one page marketing sheet as to why you're a fit for this job. Fill it however you will. You get one page. Like that is what society has said right now. And so I want, I don't know what we would do next. I guess it is the carbon footprint of what's your profiles. What's your. Yeah. What have you left on the world theory? Yeah. But here, this also goes to outcomes, right? If we were doing this in organizations where we were like measuring outcomes and doing,

[00:33:04] I was a candidate would have more to take away. Cause I would understand that data as well in my head. Right. Right. And then I also think it would set us up as candidates, prospective candidates for success for once you know what's expected. Now you can articulate that far better on your resume. Yeah. You can articulate that far better when interviewing just so many different things. But I definitely think with the way that hiring is headed in general, unless we just go straight back to who shakes whose hand and come on in,

[00:33:33] which we never really did. We are in Nashville. We're from Texas. We're allowed to do that. It's honestly, whenever other people say yeehaw, I'm like, you're so weird. But then like, it's like, I'm from Texas, so I can say that, but like you can't. So like, please stop. She's from Texas too. So we fit here. We fit. But yeah, I just, I definitely think that whenever we're talking about who can do the job now,

[00:34:00] one of the other sticking points that I see a lot of people have is whenever you do performance outcomes based hiring, it really diminishes previous experience. Now, in the sense of what it looks like on paper and how you're evaluating them, it eliminates them in the assessment of evaluation. It doesn't eliminate them from your brain whenever you go in to do that performance and provide that outcome for the assessment. And so that's where I think it actually, I love it the most is because it's like,

[00:34:28] if your 10 years matters, then it'll show up. Like it'll, if your 10 years that we're so scared of that now you're competing with someone with only two years of software engineering experience, and y'all are given the same assessment, then it should show up. Your 10 years will show up. You'll have some historical knowledge that says this code, that code. In theory. But again, I think, I mean like, again, this all comes back to is the assessment written properly. Exactly. And that's really what it comes down to. And that's why I think a lot of businesses don't do it.

[00:34:57] It's because you're going to have to hire a third party. You're going to have to get an IO psychologist down there to validate it. You're going to like, there's a lot of stuff you're going to have to go through with it. But once you have it and it's tied to every job code, and then you can alternate it based off of whatever, you'll be set for literally the rest of your business life. I agree with you. I think if someone does this right, it's perfect, right? It's a perfect way to do it. So we can just scratch this episode. I just think most organizations don't even take the time to think this through enough.

[00:35:27] This is an investment. Why would they? Yeah. This would take manpower. This would take hours. But the ROI, again, going back to my four quadrants, if we're able to monetize everything that we've done as recruiters, then we've made the case, look, this is what we should do with every single role. This is how we should do it. This now ties into your performance plan, your development, how you mobilize them, how they get promoted. It ties into absolutely everything.

[00:35:56] And you see, to me, that's why it should work because the CFO loves that. It is a roadmap. Right. It is the roadmap. Yeah. And we're just saying, okay, what's the taste tester appetizer we want them to have before we allow them to take this roadmap, who fits best in that seat and actually making the seat, the actual taste test. Don't just talk about the taste test. Don't tell me about the last time you went to a taste test. No, let's do our taste test here. I want to see how you actually perform. Yeah. And it's just such a different,

[00:36:26] and I will say every time I'm put through a process where it is that, where it is, we have this scenario, we're going to turn off our screen. You keep on yours and you work through it. You get five minutes. Tell us what you find. That stuff is the realist because that's the stuff that actually happens. That's the stuff where I have HRBPs coming to me and being like, okay, we can't fill this job and I don't know why. All right, let's dig. Like those are the operating skills. I need to see how you actually do because everyone's a great employee. Whenever everything's going great,

[00:36:55] it's whenever the grit I need to see in these employees, the proactivity, anything like that is whenever it's tough is whenever like we need to put in this, we need to do that. We need to be drilling on whatever, like whatever it is. And so those are the skills I really want to assess and weed out and look at and examine and say, what is the best fit for this team? For myself as a manager, for our group, like all these different things combined and hiring based off of an outcome does get you to do that. It's just, how do you validate and do the reliability of your testing?

[00:37:25] But if you can do that, it is the, in my opinion, the premier way to hire. If we do things decent and AI doesn't just take over absolutely everything, then this is where I would think we would go. I don't, again, I don't disagree with you. I just think that organizations do such a shoddy job of taking care of people, you know, even in a data sense, like understanding the value of someone and assessing that.

[00:37:53] I just struggle with the John CEO really getting this, I guess. He won't. Right. And, and spending the money and investing in it. And then saying, we're going to turn our organization into this, that hires like this. And then all these other people following suit. Now I could see if one company who's really huge, does it effectively. Then it takes off and goes everywhere in the world because McKinsey or somebody said it was fantastic. And then it goes wild.

[00:38:21] I just think it's going to take that one. That was my plan. And then I ruined it. One major setback. One major setback. And here we are again. All right. All right. Let's, let's get into it. Talent outside the box. You got one today? Let's, let's, we should do some, um,

[00:38:50] like Korean emotions. Talent outside the box today is actually to talk about the HR channel. Because you should see us outside of a box and you should see us at rec fest and on the HR channel app. That's what we given you today, folks. We serving that up hot. I don't know what just happened. What? No, it's great. I just advertise for people for free. I didn't even have lines. I did really well. I thought like, we are on the HR channel folks.

[00:39:17] We are here live at rec fest and we are doing some really great things. This is our second. We are a year and a half in going really strong. And we're excited about where we're going. And we hope to do more of these things. We hope to do more lives, more events. So you can see us on the road. We are on Roku and fire TV through the HR channel right now. Please subscribe to the newsletter. I have a book coming out in the fall. Woo. We also obviously are wearing, um, Ashley's company right now. Talent ed.

[00:39:46] Uh, it's a recruiter's university. Would you like to say a word about that? I would like to say one word. Okay. Sure. Word. Talent ed is a recruiter university that is truly here to make hiring better for all people, for managers, for recruiters, for candidates. And we really teach every single talent level, how to do what they're doing at their level in the best, most efficient way. There is a very big difference between working in an industry and leading it. And we are working hard to be leading that. So find us on our webpage, learn talent ed.

[00:40:15] And as far as talent outside the box, here's what we got today. Folks took me a minute is the difference between reliability and validity. You have heard me talk about that a lot because we're talking about assessments. And I think every recruiter should actually know the difference between the two. Um, because if you ever talk to someone like an IO psychologist that might be helping you create assessments, you will need to know that. And the difference is this validity is, is it valid? Is it hitting the target? Example? If I say,

[00:40:45] Keep going. Keep going. I cannot. Keep talking. This is my nightmare. It's valid. Please pretend that this is just an arrow pad thing. What are those things called? Dartboard. Dartboard. We're doing well. Listen, we came prepared. I speak Ashley.

[00:41:16] Listen, listen, listen. Here's the deal. We have a dartboard. All right. Every time I hit the bullseye, that means it's valid. It's accurate to hit the bullseye. Is that a hundred? I'm accurately hitting it. Great. So that means that it's valid. The second question is, is this reliable? Reliable is repeatable. Am I able to hit this, uh, bullseye every single time over and over and over again, regardless of who's in seat and get these same results, or does it vary every single time in order to actually have an assessment to

[00:41:45] use in talent as a prerequisite to hire someone? Your assessments have to be valid on target and accuracy with what they're searching and then reliable, which means repeatable over and over in different environments by different people. We still get the same results. One thing that I will say is there are a lot of people who think that they assess on certain things. I had one manager one time that thought that they were assessing based off of grit because they would tell a candidate one thing, wait to see if the candidate actually changed X, Y,

[00:42:15] Z by the end of the interview, um, to which what they were not actually was assessing was not grit. They were assessing their listening skills to see if they retained it. And those are two very different things. But if one mentioned it at the end, they would qualify them. And it was based on all gouache, uh, not really much snake oil. So that is the difference. You need to have something that is valid, measuring what you think you're actually measuring and reliable, repeatable in different circumstances with different people in different environments. Thank you so much for that.

[00:42:44] That was actually a really good one. Was it? Took you a minute. Once we got to the bullseye part, I was locked in, but like up until that moment, I couldn't even remember. I could picture it. The target symbol in my head. Well, if you're a regular listener to this show, you know, this is how it works. If you are new to the show, welcome to the Ashley zone. Well, anyway, this was a great episode. We will see you next time or here. Listen to us next time. Blue sky threads everywhere.

[00:43:14] You can find us. YouTube, please subscribe to our YouTube. It's been a struggle. How's it? I don't know. We're everywhere. And are you? We are. I don't know where YouTube is. Subscribe to us on YouTube. Do all the things. Thank you so much. And we'll see you next time. Bye. Bye.