Capability Amplifier

Most founders use data for every part of their business - except hiring. They run numbers on their product, their marketing, their cash flow. But when it comes to the most expensive decision in the company, they trust a gut feeling and a resume.

Regina Chou is changing that. She grew up in a rice paddy in Taiwan, became the first in her family to attend college, and built a predictive hiring engine that analyzes 450 psychographic traits to determine - before the offer letter goes out - whether someone will perform and whether they will stay. Her REGI Blueprint powers the Performance Machine and has helped scale companies from Mercedes-Benz dealerships to CrowdStrike's $2 billion IPO.

In this conversation, Regina shares the data point that upended decades of hiring science (IQ hurting sales), the blind experiment that proved resumes are irrelevant, and why the most surprising traits - hope, greed, emotional resilience - are the ones that actually predict your next great hire.

In this episode, we talk about:
  • IQ has a negative correlation to car sales at Mercedes-Benz dealerships - the traits you assume matter most might be working against you
  • Hope, optimism, and emotional resilience are the consistent predictors of performance across industries and job roles
  • A blind hiring experiment with 3,000 applicants and zero resumes produced hires still succeeding five years later
  • "Greed" - aspiration for material goods - turned out to be a top performance driver for garage door technicians
  • Same company, same product, different countries - top performer profiles were vastly different across cultures
  • Gen Z wants the same thing every generation wants - meaningful work and an environment where they can thrive
  • Regina's formula for founders: combine data and technology with heart to build a winning hiring system
TIMESTAMPS:
0:00 Why traditional hiring science is broken
1:16 Regina's origin story - Taiwan, poverty, and a grandfather's dream
5:55 The Mercedes-Benz IQ discovery
8:35 Building a model that predicts actual performance
14:32 Blind hiring at Diamond Asia Capital
19:55 Tommy Mello and the greed factor
23:22 Gen Z - same challenges, louder voice
27:02 Data + heart: advice for struggling founders
31:54 The vision - when resumes become irrelevant

PS – When you’re ready, here’s how I can help: 
  1. Join me for the Ai Accelerator Workshop this March 25th - LIVE from Genius Network Headquarters - register here: www.AiAccelerator.com/Live

  2. Want to discover your next big opportunity? Meet me for a Cup of Coffee at my Digital Cafe (this is where we can meet): www.MikeKoenigs.com/1kCoffee

  3. Ready to reinvent yourself, your business, and your brand, and create “Your Next Act”? Watch this.

Creators and Guests

Host
Dan Sullivan of Strategic Coach
Dan Sullivan is founder and president of The Strategic Coach Inc. A visionary, an innovator, and a gifted conceptual thinker, Dan has over 40 years’ experience as a highly regarded speaker, consultant, strategic planner, and coach to entrepreneurial individuals and groups.
Host
Mike Koenigs
Mike Koenigs helps business owners and entrepreneurs get paid for BEING, instead of DOING by becoming Transformational Business Influencers, authorities and thought-leaders to create impact, income and a great lifestyle.

What is Capability Amplifier?

Join the eternally curious, interested, and interesting hosts, Mike Koenigs of the SuperPower Accelerator and Dan Sullivan of Strategic Coach®, to amplify your capabilities, value, status, and authority on the Capability Amplifier podcast. Ever episode focuses on a new mindset, shortcut or deep thinking exercise that will improve your performance and lifespan. Learn more at: https://www.CapabilityAmplifier.com

Regina Chou [00:00:00]:
When I did develop the prediction model for Mercedes Benz, what I found was IQ actually have a negative correlation to the number of cars that were sold. Wow. And I thought, oh my gosh. So it hits. So the IQ goes up to a certain level and then it drops off. So why is that so? For flight risks, for example. One of the common threads. So across different industry and different job roles, there's one common trait that we found and which won't be surprising to everyone is actually loyalty and commitment.

Regina Chou [00:00:37]:
Emotional resilience is a big one as well. Our goal is become the biggest database of human data. And the application of that is absolutely huge. That was always the vision when we had building the company is to aggregate all this data because it's all scattered everywhere. So once you do that, you're going to have this insight of human potential that just have unlimited applications. Hey.

Mike Koenigs [00:01:16]:
Hey. Welcome to Capability Amplifier. This. Hi, this is Regina Chow and I'm Mike Koenigs, your host today. So I want you to forget everything you know about traditional hiring science. The assessments you currently trust are based on models that are over 30 years old. And my guess today is the reason those old systems are now irrelevant. So imagine a journey.

Mike Koenigs [00:01:39]:
A brilliant lion emerging from a rice paddy in Taiwan where she had no running water and no electricity. She became the first in her family to attend college and grew into an amazing IO psychologist and data scientist. We'll find out what I O means in a moment. So Regina Chow is the co founder and chief scientist behind the algorithm that powers the performance machine. She didn't just tweak old hiring methods, she burned the old model down. Regina analyzed 450 human psychographic traits and built blueprints that predict human human potential and flight risk, similar to how insurance companies use psychographic data to predict risk. Now, our predictive engine known as the Reggie Blueprint, imagine that Delivers results within 15 to 20% pre hire accuracy. And she helped clients like Mercedes Benz predict car sales volumes and scaled CrowdStrike from its founding to a $2 billion IPO.

Mike Koenigs [00:02:45]:
So her mission is simple. Connecting humans to they are uniquely suited for. The technology you're about to see is the result of her dedication to turning guesswork into data backed certainty. And she is a remarkably sweet, fun human being to spend time with. So how are you doing?

Regina Chou [00:03:04]:
Thank you, Mike. I feel fantastic. It's so good to be here.

Mike Koenigs [00:03:08]:
Oh, I just. I love it already. So. Well, let's begin with your journey from a rice paddy in Taiwan without electricity and to become the chief scientist behind this hiring algorithm. So what were the experiences you had growing up that led to what you're doing right now and predicting the potential of what a human being can become?

Regina Chou [00:03:34]:
Well, I guess so. Where I grew up, I grew up in poverty, where we literally. We had nothing. No running water, no electricity. But. So that's. I guess that's when I, you know, learn resilience and hard work. So I think it is.

Regina Chou [00:03:53]:
How do we unlock human potential regardless of the environment we're in? And that is really what started my curiosity into looking into how to elevate human potential.

Mike Koenigs [00:04:08]:
Okay, so you were the first to attend college in your whole family. And so how does that translate, I mean, growing up in poverty to your passion for predictive analytics and organizational psychology? Bridge the gap?

Regina Chou [00:04:24]:
For me, attending the college was actually my grandfather's wish. So we were three generations of rice farmers. And if you know anything about rice farming, if you want to be poor.

Mike Koenigs [00:04:38]:
Yeah, yeah. No.

Regina Chou [00:04:40]:
And so it's actually been my grandfather's dream. And I literally. So it's a promise I made that I wanted to do that for him. But of course, then I had the privilege. My father was. He also was determined to get my family out of poverty. So even though he didn't finish high school, it's something I actually didn't discover much later on. But that's a different story.

Regina Chou [00:05:08]:
But he built a very successful oil sale company in Taiwan. And so that's when he. He always had this dream to move to Australia. Okay, so he achieved his dream.

Mike Koenigs [00:05:19]:
That's where you got the slightly strange.

Regina Chou [00:05:22]:
Accent, my Chinese, Aussie accent.

Mike Koenigs [00:05:27]:
So great. It's so great. So I want to know, bridge the gap here. So Taiwan, rice paddy farming to Australia. And then the psychographic, like, what was the first breakthrough moment you had that bridged science and psychology and like, your first really big deal that started the snowball that probably led you to right now, right here.

Regina Chou [00:05:55]:
Thank you. Yes. So I. I've always been fascinated about human people, and that led me into psychology.

Mike Koenigs [00:06:02]:
Not the other kind of people, not the aliens. Not the aliens.

Regina Chou [00:06:08]:
Well, if I do have a maturity, I would not pass on that. So I was actually working with a Mercedes Benz dealership in Sydney, Australia, and we were just measuring traditional trades, you know, their iq, their emotional intelligence. And when I was at the dealership presenting the result back to the business owner, he basically said to me, so, okay, how does this help with my business? So what if someone scored this IQ or have this certain level of emotional intelligence? And that's when it really hits me, because that's where the traditional assessment fell short.

Mike Koenigs [00:06:51]:
And what kind of assessments, for example, the ones that you were like, these are obsolete compared to the data I discovered.

Regina Chou [00:06:57]:
Yeah. But then the fact is for business owner, the fact that how much they score on different traits actually serves no meaning to them, what's meaningful to them is how will someone actually perform. So in his case, how many vehicles can his salesperson actually sells? So, so, you know, that's when I start to ask, so can I actually know how many vehicles? Can I actually predict how many vehicles someone can sell before you actually hire them? Because that's where you can deliver the value, you know. And so that's when I try to solve that problem. Can I actually. Because if I can actually solve that problem, find a solution to that, I can help many, many business in different industry. And it also means connecting people to meaningful work because that means connecting the right people with the right traits into meaningful job. So I started working on that and that's when I actually find out, well, if I can measure enough psychological trades and then I can actually get the actual performance data, so in this case, how many vehicles they actually sold each month, I could actually figure out what psychological traits are driving the actual sales performance.

Regina Chou [00:08:16]:
And then you can use the same algorithm apply on people actually applying for the job. You'll be able to predict how many vehicles someone can sell. So that was my aha moment. And that's when I thought this is pretty amazing. If I can do that and put it into a software.

Mike Koenigs [00:08:35]:
Yeah. So what that translates into when you go downstream a little bit is I'm going to jump ahead a little bit. But I want everyone watching, listening to understand the magnitude of this work is you're able to look at any kind of a KPI or a performance indicator in any kind of a job. You've got over 450 psychographic traits that you've analyzed. You've built up, I think it was like over 5 million data points. Is that accurate? Okay. And that means you can determine how well a person's going to function in their job, kind of no matter what it is, and whether or not they're going to run away, they're a flight risk, their probability of success. And what I've learned is there's some things we all assume are most important, like IQ and it turns out they aren't necessarily relevant or all of these factors.

Mike Koenigs [00:09:31]:
So can you bridge the gap between the weird, non obvious things that we all think are important that aren't and the ones that matter that was a big compound question.

Regina Chou [00:09:41]:
But in fact, yes. And there's so many biases that we have even actually within industrial psychology there's always been a belief over the years that IQ is actually the most predictive. It has the highest predictive power in predicting how someone would perform the job. So the belief is that the smart smarter you are, the better you're going to do a job. And it's actually belief that applies across different industries and different job roles.

Mike Koenigs [00:10:10]:
And what have you found to be true?

Regina Chou [00:10:13]:
That is absolutely not the case.

Mike Koenigs [00:10:15]:
So IQ isn't the main predictor?

Regina Chou [00:10:18]:
Absolutely not. But this is only because you can't actually look at anything in isolation. So that's one thing that's important. You can never look at IQ on its own because human are so much more complicated than that. What else do we have? You can name it thousands of different attributes that's within all of us at different levels. So try to imagine if you combine someone with high iq, low work ethic or someone with high work ethic and low IQ and that just a simple two by two combination. But imagine combining thousands of different traits. That's how complicated we are.

Regina Chou [00:10:59]:
In fact the first time when I found out. So because of that, with all the prediction model I try to develop when I go into every corporations I try to IQ was actually always in there because apparently that's one of the most reliable predictors. But when I did develop the prediction model for Mercedes Benz, what I found was IQ actually have a negative correlation to the number of cars that were sold. Wow. And I thought oh my gosh. So it hits. So the IQ goes up to a certain level and then he drops off. So why is that? It's basically so it teaches you.

Regina Chou [00:11:41]:
So it was a very obvious lesson. So being a car salesman, the ACU benefit only reaches to a certain point the longer serve the purposes. And one of the dealers, dealership principal actually says, oh you mean when they got to a certain point in IQ they actually sell the car back to customers they're too smart for their own good. Okay, yes, that's pretty interesting.

Mike Koenigs [00:12:06]:
Well, it's like some of the smartest people I know are also the most stuck. They spend too much time staring at their belly button to get to heaven. It's like it doesn't work. So I'm going to ask you another question. Hope that all made sense. So you've got so there's IQ and then there's 450 other psychographic traits. So what are if you had to cast a wide net and Say here are the ones that matter most that consistently show up that mean someone's going to be a hard worker, ethical team player, you know, the things that matter most, matter most to them. Is there such a thing?

Regina Chou [00:12:50]:
There is actually. So whilst.

Mike Koenigs [00:12:52]:
And the non obvious ones are always the most interesting to me. But also. Yeah, what are they?

Regina Chou [00:12:58]:
That's right. So as opposed to iq and in fact one of the common threads I continue to find across different industry and different jobs is actually hope and optimism, which is very, very surprising. But then if you look, is that.

Mike Koenigs [00:13:16]:
Easy to determine and easy to measure and easy to detect?

Regina Chou [00:13:19]:
Absolutely.

Mike Koenigs [00:13:19]:
Okay, so hope and optimism, all right.

Regina Chou [00:13:21]:
Yes. And I guess that's what's driving the resilience in people.

Mike Koenigs [00:13:27]:
And that's a measurable trait too. Resilience. Is it something that you can detect?

Regina Chou [00:13:31]:
Absolutely. In fact, everything is measurable. I know that sounds. But that has always been a challenge of mine. But something, what I've learned is that if you understand it enough, everything is measurable and when you have the data, there is always inside an answer within that.

Mike Koenigs [00:13:51]:
Okay, okay, so let's move on to another case study which is Diamond Asia Capital and tell us about how that work translated into the product. Because at first I assume you were just gathering lots and lots of data and probably crunching a bunch of spreadsheets, but at some point it became possible to create the product that became who hire. So what was involved in that and how did, how did you know? Like how many big lessons did you have to learn and how much data to crunch until you're like, I've got a predictable model, I can adapt to just about any business type.

Regina Chou [00:14:32]:
See along the way over the years there's so many valuable lessons. In fact, you know every prediction model that we try to develop huge lessons across different industry from, you know, when we're talking about, you know, janitors, cleaners in the hotel, all the way to C suite executive management leadership prediction models that we've worked on across different industry. But it all started with actually a philosophy of. I've always believed it's not the education, not the past work performance that's going to predict future performance. It's actually someone's potential and their suitability to a job. So with Diamond Asia Capital, what we, so the founder and I, we have this. He actually had the similar philosophy as me. That's when we started talking and you know, he always.

Regina Chou [00:15:32]:
So because in Asia obviously you have to graduate from Top Pedigree University in order to be in the banking and investment fund jobs. And so he always thought he got lucky that his resume was put in a different. In the wrong pile because he didn't graduate from top university. So he wanted to, because he's been so successful, he want to give back to the society. So what can we do? And so we decided to run a social experiment where we actually open up applications for people to apply for hedge fund, investment manager, apprentice. But we, one thing we did was we didn't allow them to upload resume. Yep. So, and also we actually, actually mask their first name and last name, so we don't.

Regina Chou [00:16:23]:
So we take out all the biases, their ethical background, nothing else. We didn't want to know anything about them other than looking at their psychological DNA. And so we had over 3,000 applications because it's not heard of in Singapore. You mean you're not going to look at my work experience in education. And that was really fascinating. So we had applicants from not graduating from high school all the way to having multiple PhD degrees and we ended up hiring eight of them. And most of them have been successful. Continues to be.

Mike Koenigs [00:17:06]:
How many years later?

Regina Chou [00:17:08]:
Five years later.

Mike Koenigs [00:17:09]:
Okay. And so when you look at the common threads amongst all of them, they all had. What were the common threads? I mean, this is a hedge fund manager, but is that translatable into almost all other businesses and jobs too?

Regina Chou [00:17:25]:
So with every industry, and in fact, let me give you this example. Even with Mercedes Benz, we did the research in Australia, Singapore and Malaysia. And so even same brand, selling the same vehicles, you look at the prediction model, that psychological makeup of each country, they're actually vastly different.

Mike Koenigs [00:17:51]:
Wow.

Regina Chou [00:17:52]:
Even. Even selling the same luxury vehicle. So but that, that really explained to you how different environments are suited for different people.

Mike Koenigs [00:18:05]:
Yeah. So every culture, a language, it's just like there's all sorts of very subtle nuances.

Regina Chou [00:18:13]:
Absolutely.

Mike Koenigs [00:18:14]:
Every environment, every business type. And that's why you've got effectively a roadmap or a blueprint that can be applied to a business. You look for those, you can quantify them, you can measure them, you can predict them.

Regina Chou [00:18:26]:
Yes.

Mike Koenigs [00:18:27]:
And that would be impossible as a human, especially if you're dealing with large volume or at very low probability at the speed that you're doing it now with software, I presume.

Regina Chou [00:18:37]:
That's right. And so for flight risk, for example, one of the common threads. So across different industry and different job roles, there's one common trait that we found and which won't be surprising to everyone, is actually loyalty and commitment. So, you know, and that's something, you know Emotional resilience is a big one as well. That applies. So any job that actually requires a lot of emotional labor, you really need that.

Mike Koenigs [00:19:10]:
So you can't have criers apply. Remember, I don't know if you remember the movie. There's no crying in baseball. Might be too distant of an American reference. It was a Tom Hanks movie. But anyway, that didn't land. That didn't land. It's okay.

Mike Koenigs [00:19:24]:
I want to move on to another one here which is. See, it just goes to show I could have used a predictive model and known that that joke wouldn't land me. Don't run it past an old movie reference that's 30 years old with someone from Taiwan and Australia moving right along. And it's baseball too. Terrible idea. So next one. So you got Mercedes Benz crowdstrike hedge fund. But then you've got Andy Elliott who is in effectively sales training, personal development, personal growth.

Mike Koenigs [00:19:55]:
Anyone who's been exposed like a Tony Robbins like environment, for example, would resonate. He's used this model, doubled his re revenue all the way up to 100 million. You got Tommy Melo, he's in the garage door business, so in the trades. And he sold his company for like half a billion dollars, a chunk of it. He's about to have a billion dollar exit now. And they've, you know, they've taken turnover from 200% down to single digits. They've been able to predict and grow and scale which became a predictive mechanism for figuring out when to exit. This all equates this incredibly complex roadmap you're navigating.

Mike Koenigs [00:20:37]:
So just talk about other predictive models, other case studies or what again, the distinctions between these businesses and industries.

Regina Chou [00:20:48]:
Right.

Mike Koenigs [00:20:48]:
Again, a huge compound question. But I wanted to give you some time to digest and think about because I'm looking for the shortcuts here. Like what are the shortcuts?

Regina Chou [00:20:57]:
Okay, that's okay. I'll give you an example of the model that we developed for Tommy, his garage door technicians because so going to the research work, so in understanding Tommy's value and so then one of the things that I measure with these garage door technician is called greed. And I know that sounds. But greed is essentially measuring someone's aspiration of material goods. And it turns out someone that score higher on aspiration for material goods actually performed much better. And that's when you know.

Mike Koenigs [00:21:38]:
So in this case, greed is good. It's a motivator and it's not associated with one of the capital sins that's actually good in A team and a business environment.

Regina Chou [00:21:48]:
When it's applied properly, it's a motivational driver. And when Tommy saw the result, he thought, you know, I've always, always felt that's the case. And that is actually the culture and the value I want to drive my company. But now not only I have the data to back it up with, I also have a tool to be able to measure it.

Mike Koenigs [00:22:06]:
Yeah.

Regina Chou [00:22:06]:
Pre hire.

Mike Koenigs [00:22:08]:
That's so cool. That's so cool. That's so cool. I was going to use another distant movie reference, but Minority Report, Tom Cruise was in it when they could predict if someone's gonna commit a crime in the future. Right.

Regina Chou [00:22:23]:
It's actually very, very similar philosophy. Exactly. Moneyball applies to the same principle as well.

Mike Koenigs [00:22:28]:
Yeah.

Regina Chou [00:22:29]:
Yes.

Mike Koenigs [00:22:29]:
That's great. A Brad Pitt reference. Okay, next one here I wanna go on. I have a Gen Z. We have a Gen Z in the room right over here. And these let's. You know, I don't know what exactly where the cutoff is right now, but it ends at around someone who's 27.

Regina Chou [00:22:48]:
Right?

Mike Koenigs [00:22:49]:
Okay. Ish.

Regina Chou [00:22:49]:
Yeah. 28.

Mike Koenigs [00:22:50]:
28. All right. And what I want to know, like, they feel like a completely different breed of human. The value systems, their motivations, how they absorb content, but also how to drive and motivate them. I remember when I was hiring millennials at first and. And holy cow. So distracted, entitled, hard to motivate, hard to beat team players. Compared to I'm.

Mike Koenigs [00:23:22]:
What the hell am I? I'm in between Baby Boomer. Was it Generation X? What the hell are Generation X?

Regina Chou [00:23:29]:
Gen X?

Mike Koenigs [00:23:30]:
I can't remember. Born in 66. That what I am. I'm a Gen X. Okay. But I didn't get it. It took me a long time to be able to figure out, oh yeah, they're just motivated by different things. So when you're finding and hiring, talk about the generational shifts, the gaps and attracting and retaining that audience.

Mike Koenigs [00:23:54]:
What's different? What's changed? What patterns do you see? Or is that an illusion?

Regina Chou [00:23:59]:
You know what? Yeah. I actually think every generation actually has similar problems, or dare I say the same problem. We all want to find meaningful job. So it's a matter of that they actually found the right environment that helped them to thrive, to be the best version of themselves. And that is something each generation is seeking for. I think Gen Z just be more upfront and be more vocal about it. But it's no different. Every generation faces the same challenge and that is one thing actually doesn't change.

Regina Chou [00:24:42]:
And so I think as employees, you know, we business owners, we also need to step up in helping the younger generations in achieving that. I think it's also our responsibility in helping them to do that. Yeah.

Mike Koenigs [00:24:58]:
Finding meaning.

Regina Chou [00:24:59]:
Yeah.

Mike Koenigs [00:24:59]:
So how about. So I'm just thinking through, let's say I've got an environment, a business environment. Is there a way to take your tools, your assessment and determine first of all, what are the best humans in that kind of a job or what I need to change so I can attract and retain better? And is there a distinction between different generations or it just comes down to a certain fingerprint of the right psychographic traits in a particular environment? Can you talk a little bit about where's the crossover between environment and people and either adapting one or the other? Again, I don't know if I'm asking that question properly.

Regina Chou [00:25:42]:
No. Well, that is actually our mission. That's what we're trying to do by, you know, bringing. So bridging that gap between the two parties is where we're going to achieve success. So it takes both parties to work towards that. Yes. So not only we need to find out what they're most suited for in these jobs in order for them to achieve potential, but what else we can do in helping them to achieve that. And that's actually.

Regina Chou [00:26:13]:
That would be what our legacy is.

Mike Koenigs [00:26:18]:
So let's go back to you're queen for a day or a week or a month or a year, and you get to give founders who are struggling to find and hire and scale their teams, which is the number one indicator, the compounding effect, so you can get to freedom. We want to grow our business without having us have to be there or to get to an exit to achieve financial freedom while you're creating meaning for these team members. So again, that's a complicated formula. So you're queen for a day. You've got access to the entire audience of business owners. What's your advice for the struggling founder who's trying to make sense out of this and get the best of the best?

Regina Chou [00:27:02]:
Start using data for hiring just like you do in every aspect of your business in terms of your product. Your what? That's one thing most business owners don't do.

Mike Koenigs [00:27:13]:
What?

Regina Chou [00:27:13]:
When it comes to people rely on gut feeling. They think, well, that's, you know, we'll give them a try. We're not so sure. Humans are complicated if they don't work out next. And no, that's not the way to do it. It's a much smarter way, which is data and technology and then combine that with heart, then you have a winning formula.

Mike Koenigs [00:27:35]:
Wow. And those, those when I hear, okay, heart, how do I measure that? How do I predict that? Again, these are so nuanced. What's predictable about determining heart?

Regina Chou [00:27:51]:
Like everything in life, I think it's a combination of science and art and you need both. So it's never just one or the other that doesn't work. You need a good balance of both. And that's where we come in actually. So when we developed the science and technology, we didn't just say, you know, this is where, you know, you, you cut these people out just because they didn't meet this benchmark. No, that's not what we are advocating at all. No. Yeah.

Regina Chou [00:28:27]:
So bring the. So the heart is about your. How do you actually build your culture? And that's something we want to help company to do as well. So you can't, you know, that's what you need to build your identity, your culture and then that's when you bring the people on onto the same team to achieve the same dream.

Mike Koenigs [00:28:50]:
So good. So that's going to bring us back to who hires a data intelligence engine. And can you talk a little bit about the value of your aggregated data and how it's useful beyond hiring people? Hiring people, giving them meaning, finding the right people for the right job that has a high likelihood of success. Just talk about. And you've got this huge map of information that very few or no one has that's quite like you.

Regina Chou [00:29:22]:
Yes, well, our goal is become the biggest database of human data. So we are not, we're talking about, you know, human potentials. And the application of that is absolutely huge. That was always the vision when we had building the company is to have this, to aggregate all this data because it's all scattered everywhere. So once you do that, you're going to have this insight of human potential that just have unlimited applications.

Mike Koenigs [00:29:56]:
So now you have a really cool business partner, Jonathan Wisman, and he's sitting in the room with us right now. But talk a little bit about your relationship and where his unique abilities have merged well with yours and what you're doing in your combined vision. Think about your legacy for who hire and where. You guys are 100% on the same page. We talk a little bit about that business relationship, how you evolved over years and how you've zoomed in on this core goal and what exactly. That is.

Regina Chou [00:30:35]:
Interesting. You asked that. Actually, we actually.

Mike Koenigs [00:30:41]:
You don't look at him. You look at me. Look at me. You can't see his Reaction only I can. I'm putting you on the spot. I know it.

Regina Chou [00:30:53]:
The moment I actually knew I found the right business partner was actually. He actually showed me a video he made about elevating human potential. And every time I watched that, I had tears in my eyes because that is exactly the vision I had when I started the company. Yeah, it's been amazing. An amazing journey we've been on, and I'm so excited about the future that is unfolding in front of us. And, yes, it is all about unlocking human potential. And how do we elevate that?

Mike Koenigs [00:31:29]:
That's great. Well, how will you know? How are you going to measure? Because you're all about measurement. How will you know when you've arrived? Do you have an idea, a concept, a number? Like, is it a number of people? Is it. Like, is it money? Is it. What. What. What would. What do you define as being? I know we're there when X happens.

Regina Chou [00:31:54]:
When the business owners or the companies no longer judge people by their past behaviors, their educations, or their past work experiences.

Mike Koenigs [00:32:07]:
Keep going. Keep going. I love this. And what else?

Regina Chou [00:32:12]:
So that's our mission. So that. Yeah. Because we all have these huge potentials, it is about providing them the opportunity to do so. When companies no longer look at resumes when they are hiring, I think we've achieved our goal. Wow.

Mike Koenigs [00:32:37]:
Can you say that one more time all the way through? Because that is a profound. I think it's a profound mission. Vision in North Star.

Regina Chou [00:32:47]:
Thank you, Mike.

Mike Koenigs [00:32:48]:
Yeah, you're welcome.

Regina Chou [00:32:49]:
Thank you so much.

Mike Koenigs [00:32:55]:
I know I'm putting on the spot, but that was like. That is one of the best visions I've heard in decades.

Regina Chou [00:33:05]:
Thank you. Thank you for this opportunity. I've had so much fun with you in the last few days, and it's been so much such a pleasure getting to know you and your team and everyone's being so fantastic, and it's been such a wonderful experience. Thank you.

Mike Koenigs [00:33:21]:
You are so welcome. I'm so glad I get to participate in this. Good.

Regina Chou [00:33:26]:
It's history in the making.

Mike Koenigs [00:33:29]:
I really do. I think it takes just this recipe of people and technology and vision and heart and values. There hasn't been a better time for this.

Regina Chou [00:33:46]:
Thank you.

Mike Koenigs [00:33:46]:
Yeah. So good. All right. So where do people go to learn more about you and what you're doing right now and. And how do they start a relationship with who hire?

Regina Chou [00:33:58]:
Well, can visit whohired.com so and my business partner, Jonathan Wissman, the salesboss.com to learn more about us all right.

Mike Koenigs [00:34:12]:
So you just got to go there, fill out a form, ask for a demo, line up and find out if this is right for them. There's lots of extra materials they can go visit and download and start a relationship with someone who could change the course of your life and the people who are in it.

Regina Chou [00:34:29]:
Yes. Wow. Absolutely love that.

Mike Koenigs [00:34:32]:
Good job.

Regina Chou [00:34:33]:
Thank you, Mike.

Mike Koenigs [00:34:34]:
You're welcome. All right, well, I'm going to end this with. Now you've met the heart, another part of the heart of the organization. If you haven't watched the interview with Jonathan Wisman, you must do that. I think they're really on the right mission with the right technology at the right time, and they're good people who care. So my name is Mike Koenigs. This is Capability Amplifier. This is Regina from whohire, and it has been a pleasure spending time with you.

Mike Koenigs [00:35:06]:
It's been a pleasure spending time with you.

Regina Chou [00:35:09]:
Thank you so much.

Mike Koenigs [00:35:10]:
Yeah. And we'll see you in the next episode. You did a great job. A great job. This is your first time on camera, right?

Regina Chou [00:35:16]:
Absolutely.

Mike Koenigs [00:35:17]:
All right.

Regina Chou [00:35:17]:
Yes.

Mike Koenigs [00:35:18]:
Wait. What do you think?

Regina Chou [00:35:20]:
It's my debut. That's.

Mike Koenigs [00:35:22]:
Good job. All right. Yeah. Make sure you post. Great job, Regina. And then we're gonna see you in the next episode. So let's say goodbye. See you.

Mike Koenigs [00:35:32]:
Thanks for watch.