Harnessing Mindful Analytics to Elevate the Human Experience
In this episode of the HR Leaders Podcast, I spoke with Gustavo Canton, CEO & Founder of imhmn, about using ethical AI to elevate human experiences at work.
Gustavo brings a unique background spanning statistics, computer science and behavioral neuroscience along with over 20 years’ experience driving analytics transformations. His goal is to enable organizations to implement technology in an empowering, conscientious way.
We discussed the promise, but also risks related to AI advancement and the need to carefully consider impacts on jobs, productivity and wellbeing. Gustavo highlighted solutions like universal basic income, while noting leaders should not blindly replace human roles with automation.
His advice to HR executives is to establish guidelines early, focused on:
Data ethics and eliminating bias
Experience-first design thinking
Solving business problems vs. technology for its own sake
Gustavo is optimistic about AI’s potential to augment unique human strengths when guided by inclusive values that allow all people to thrive and bring their authentic selves to work.
If this vision resonates, check out our full conversation below. What does it mean to you to have technology elevate rather than replace employees? I welcome your perspectives in the comments.
Episode Highlights
How HR leaders must establish ethical guardrails early when implementing AI to avoid unintended bias and displacement of human roles
How analytics teams should design solutions focused on enhancing employee experiences rather than technology for its own sake
How organizations could supplement incomes if automation accelerates job losses to responsibly transition workers impacted by advancing technology
🎙️ Automatically generated Podcast Transcript
Chris Rainey 0:00
First off, eelcome to the show. How are you?
Chris Rainey 0:03
We finally meet Yeah. finally
Chris Rainey 0:05
Has it been like, what? Seven years? Maybe since
Gustavo 0:07
2017. So yeah, seven years.
Chris Rainey 0:09
That's crazy.
Gustavo 0:10
Yeah. I remember when you call me first. Out of the blue, say, Hey, I was teaching at electrical time, just move from US president and like, yeah, we'll see if people are a fortune either building the team, and you told me about you what you were trying to do. And I use hear your pitch. And I felt like, Okay, this guy has a similar mindset to what I have. And I just wanted to express my idea. So it was a perfect timing for us to meet. Yeah, yeah, isn't
Chris Rainey 0:36
it because that was like just means that the company was me and Shane in my bedroom? Yeah. And I think what happened was is we kind of saw this emerging topic of animal power lakes, it was, I think everyone was calling it HR analytics back then. And it kept coming up more and more in our conversations. And we realised there really wasn't a network or events or, you know, a community that was built around that. And we were like, Okay, this is super interesting. I think at a time there was maybe only a couple of 100 people, probably that had a, you know, a director, VP role. And people Alex, yes, HR analytics, a lot of them. You're one of the first Yes, it was called people analytics. Back then it was like 80%, HR analytics, and then people analytics. Now it's the opposite. Obviously, before we go into more detail, tell everyone a little bit more about yourself, your background, and sort of the journey to where you are now and what you're doing. Now. For those
Gustavo 1:29
who know me, my name is Gustavo Kenton, I was born in Panama, live in the US for many years work for big corporations in the space of analytics, that's been analytics. And data has been basically my passion. I work for all these big companies, you know, in Europe, Latin America consulted internationally. I love what I do love data and technology. But I realised there was a gap in so that's why I founded this startup called I'm human, because I'm trying to help organisations actually transform faster, because the rate of transformation that I'm seeing now in the HR space across the board, I don't think it's going fast enough, relative to what has happened in the industry. So I saw a need, I felt I have a purpose, basically use technology and AI for the benefit of the human experience. If I were to summarise it, that's kind of what it is, right? And that's why it's called I am human, because I want to design for the human experience. I don't want to design for the technology,
Chris Rainey 2:15
which is a mistake. Yes. You've learned that many times in many companies.
Gustavo 2:20
And honestly, I feel I have responsibility, because I was, you know, when social media came about, if you remember, well, there was a time that companies were not using Facebook and Google Yeah, to advertise. And they were trying to prove if actually was profitable to use social media. Yeah. And I was in that space. And at the time, what was the mindset, let's just go fast, this is exciting. We were not thinking about the implications for mental health, or implications for productivity in the workplace, or all the sort of stuff that happened through social media. So now that I am more mature, in my, I will say, my journey, and I have learned and see more things in the space I want to convey. On the one hand, I want people to be excited for technology and transformation. But on the other hand, I want people to be conscious and cautious about how they use technology. That's why I never say, AI is a great thing. I say I support ethical AI. That's that's the space that I that I am. What do you mean by that? Most companies are very focused on for example, data quality data integrity that I trust. Now you hear people talking about data bias, the bias in data, right? If you look at Ghana, for example, they made a list of the what are they, let's say, the top 30 roles that we need for the future. And from the 30 roles, there is one that is dedicated to the ethics of the data that also makes sense, we all should be dedicated to the ethics of the data. And so a very pragmatic thing that you can do. If you have a company right now. Go to your IT team and ask them, What are your ethical guidelines for data? I have my I have accurate ethical guidelines, and I share it, you know, across the board for people to see it. Because I want them to actually start writing. Okay, how do I make sure the data is secure? How do I make sure that there is no bias against specific gender or religion or something that for recruiting, for example, right? Like, do you actually have guidelines in place that you have written in terms of how do you manage the data beyond the fact of looking at quality of data, timeliness of data, completeness of data, like all the things are important, but you need to have somebody with a background, hopefully psychology or neuroscience or something, say what qualifies someone to make decisions. Usually, you have to have somebody with IO psychology background, or some kind of background sociology that actually understands human behaviour that can basically help you kind of manage or remove bias from the data
Chris Rainey 4:32
unique person, right? I want to understand that but also understands that technology that's quite a unique set of skills. Correct.
Gustavo 4:38
And I think that's a part I think most companies that I go to, they don't have that mix of people or they don't have a person that dedicates to this role, and there's a huge gap in the market.
Chris Rainey 4:50
Why is that important, though? What are the implications of not doing that?
Gustavo 4:53
I'll give you the example. And then I'm, nobody can take the future, but you can simulate the future. So you have seen the examples. of when they take data. And they start doing recruitment. And some of the database on the name of the person people get dismissed from the from the, from the pool of talent, sometimes is years of experience or certainly of education age, age. I mean, I don't know how much is the impact of age in Europe today. But I can tell you in the US, there is still a lot of ageism, for now, you know, and again, those things are bias in our data. There are people who have 50 years, 70 years, how many years and they their mindset works great. There are people who have fear. So they might be younger, but they don't have the right mindset. It's not about age, it's about mindset. So there is a lot of information for recruitment, talent, mobility, how promotions are given the sort of bias that we have as managers. Yeah, you know, just to give you an example, we prove to the pandemic, that remote working was effective for many different roles. And now we're going back to that era of we're forgetting about what we learned throughout the pandemic, and we are having this bias of promoting people back, yeah, it's the people that we see often in the office, we have a bias to promote based on that. And managers, you know, we know these two studies and managers are, are making these decisions, because they are looking at their, from the human emotional lens, as opposed
Chris Rainey 6:17
to see that person, a person the office every day, you know, I interact with that person. So yeah, that makes sense. Yeah. What are some of the other examples of that?
Gustavo 6:26
The recent example with Twitter, right? So Elon Musk goes into Twitter, they disrupt the company for good or for bad, how will you want to look at it, it to me is a great case study, because 80% of people were let go of Twitter now called x. And again, to me, that's an example where you are trying to use technology to replace a lot of people's job. And you're trying to use AI to try to their job. But it has been proven based on the revenue and the profit of the of their stock, that that's not always the solution. You need to know how to do this in a humane way. You can not just try to replace everybody, just because you can do it doesn't mean you should do it. Yeah. Right. Another example is what is happening with the trucking industry. Across the world, they are having a lot of work developing self driven cars, and technology. And in theory, you can replace a lot of people today in their jobs. But a lot of a obviously unions and companies and labour are getting together and say, Hey, guys, you know, we need to be careful. Because if you do this 1000s and 1000s of people were unemployed a month. And so now some states are concept, putting guidelines on how to do the transition from that just because you're working in an office with a nice job. And this has been the case, many cases, we look at this, and we think, Oh, this is not gonna happen to me. Well, there are scenarios where 20% of what we call white collar jobs can go away. Because of technology in the next five years, when we're talking about 20 years from now, five years. That's pretty scary. So yeah, we have to be in tune with what is happening. And that's part of the reason I wanted to talk to I talk to people about this is not just because I want to, I want to sell something, I just want people to be conscious and kind of like wake up for the day to day reality of Oh, I'm just working on my job. But look what is happening in the industry. All the world is changing dramatically. And it's going to impact you and your your lifestyle. And it's gonna happen very soon.
Chris Rainey 8:16
What do you think about the argument I hear a lot of people say, don't you're not going to MIT that those jobs aren't gonna be replaced, but you will be replaced by someone who uses generative AI. A
Gustavo 8:25
good example for that is let's take radiologists, right? Radiologists. Right now the AI can do the job as equal or better than radiology. So in theory, there are leaders who sometimes don't understand the concept, the ultimate consequence, right? And they will say, Oh, yeah, let's replace all the radio, the radio is most people who are conscious will not do that. But let's say that happens, you can do it, technically, you can do it. But now what is happening is that radiologists that are working with AI, are actually getting more opportunities. Right? And the ones who are now working with AI are gonna get replaced but yeah, to your point if you attach yourself is like, out men yourself with the technology as an individual do you're gonna continue to do well, if you don't do that and you try to stay away from it is not gonna go well. You can tell me the industry. I will tell you how many people are getting replace leisure. See what happened with Hollywood writers. You see what happened? There was striking right now yeah, there was this there was a bunch of shows that were not happening. They were not read them because there was some pushback right away was technology and the AI Barbie with all the reasons, you know, it's not everything about AI. But with that being said, is showing you how some leaders have this mindset that hey, I can just use technology to replace everything. And the solution is a solution decision. Ultimately, if I'm gonna dig into a
Chris Rainey 9:38
lot of people making decisions don't really understand the nuances of the role. Like a good example, before we hit record I was telling you about my old sales organisation, that they tried to replace the entire sales team with marketing for bots through traditional digital marketing. And I told you how after eight months, the company went from a 14 million or 30 million pound business To setting off in pieces, as well, because they took away the people element, before we can replace that with technology didn't understand the relationships that were built with those specific clients through those individual people over time. And that's earned over time. You can't buy trust, no buy relationships through technology.
Gustavo 10:22
Yeah. And also people, I think people underestimate the culture, aspects of it and relationship. Like once you get into a role, and to me, I was guilty of that, like, I used to be in analytics, because I used to love the data decoding, the modelling statistics, that's honestly what I got into the, into the space. But over time, I realised is very hard to replace someone who understands all the nuances in the data and the tables and how you navigate information dynamics. Yeah, the power dynamics relationships. Yeah. And I started my career in Sam's Club, which is part of Walmart. So it was a gigantic organisation, and you have to know how to navigate that organisation. And I'm telling you, for me, it was a great learning and a great place for me to kind of get it my leadership culture and working culture, because after going to such a huge organisation is much easier for me to go to smaller organisations and learn the hard way. Yeah, exactly. Well, yeah, it works out. And again, same as you happen for you, I sit, in my case, how leaders come in, they try to replace people because they see something very logical, but they don't listen to your point, the unintended consequences of replacing those people, or
Chris Rainey 11:30
it's like, when I spoke to most most CHR OHS that I interview on the show, I say, you know, when you first join a company, what is your first six to 12 months look like? Most of the time, it's, they spend the first six months just building relationships, right? travelling all over the organisation, getting to know the leaders, understanding the pain points, building that trust, before they make any type of change, or invest in any type of technology is building the human relationships in organisations before that, and the ones that don't do that, that come in, and all of a sudden start making all these changes are about really involving the employees and the leaders is a disaster.
Gustavo 12:11
It is as well. And I will say something that I think is a huge mistake in many companies that they don't have an onboarding, like onboarding bodies, like sometimes that will come in and help you get into organisation and kind of walk you through the some of those nuances. I was lucky enough. When I came to Europe, I actually went through a full training of culture, because I was working with the French culture, which is different than the Panamanian culture, Latin American culture and American culture. And to your point, I used to work during my lunch break. Because that was the my, my usual us mindset on the one that one executive told me to start or you need to have these questions in the coffee break with a with the leaders. And I never thought about that until they told me that the sound eating sound. But when I started doing that, I actually understood really what was happening. And they will tell me things that they will not do openly in meetings, because it's a different culture, like a team meeting, their culture in France is very different to a team culture meeting in the US. So I had to learn a lot of nuances in navigating that. And just so you know, every shift and these officers have chief data officer, right now. I think their tenure is less than three years, like 70% of them only the last three years. And now it's actually decreasing. Yeah, part of the reason is that aspect is a nuance, the culture, enabling the business, the relationships, that's honestly what is driving that is not technological acumen or skill set. Is just that how we integrate with the culture?
Chris Rainey 13:39
Yeah, I think we've seen all levels, the same thing of HR, sort of the average, you look on LinkedIn is like, two, three years. Yep. Then they're often the next business. And then kind of part of me also thinks about how much real meaningful lasting change can you even make? Yeah, in in that period of time,
Gustavo 13:58
that will depend on the company. Because this is interesting. Every company has a culture, but everything within the company has a culture, I came from a place when I was in Walmart, you get promoted, they might time every 18 months or every year. So 12 months, sometimes we have promotions. But it was meaningful. Because in Walmart, even though it's a huge organisation, you can make changes very fast. Sometimes, like probably three months, when I was working in Sam's Club, I was the analysts. I was the manager. You know, I was in everything analytics at the time. And I was supporting the fuel division operations, marketing, HR, everybody, and it was three month project. And three months it was into production. Wow, huge decisions. That's the difference of some of these companies. Why they wouldn't
Chris Rainey 14:41
have expected that for a large organ. Normally you associate the larger the company, the slower. Yeah,
Gustavo 14:47
and again, it depends on the team. It depends on your bank. When I got into WalMart, for those who don't know my story, I was an intern, and I did a project my first project was to sell the idea having fuel stations outside of the box, because at the time they were not sure if there was sorry, outside of the actual store, like, you know, you had two stations like the petrol station, which is normal
Chris Rainey 15:09
for us in the UK. Yes, every, as there are Tesco has a petrol station exactly outside. Yeah. But
Gustavo 15:14
at the time they were thinking is not a good business for some reason. I don't know why they weren't thinking about sort of business and they feel division had they wanted me to show the case to support to invest in it. Okay. And so that was my first project ever, as a as an intern. That thing is now worth hundreds of millions of dollars, because it started for Sam's Club. Well, then Walmart, it took me three years to sell it to Walmart. But for sassily was three months to sell it to SAS the Wow, okay, you see a difference? Big difference, even though the same company, and they see the same data to your point, it depends on what function you are in the same company. We're doing what
Chris Rainey 15:53
I want to go back to the AI bid for a second. What do you see sort of the potential risks and implications for humanity as a as a whole?
Gustavo 16:02
So that's, that's the big question. Right? I will do this. Think about this for a moment. We have gone through a 50 year journey. Since AI, like I was listed in the order they to Geoffrey Hinton, which by the way, I think he's from here from the UK. He's considered the godfather of AI. I was listening to him recently and put into perspective, we have gone through this journey for 50 years. But his time he couldn't prove that AI could reach this level of intelligence. Now recently, after all this time, finally, people can see that what he was saying back in the 70s actually can materialise because now we have the technology. We have the scalability, the systems to actually pull it off, right? So we have this intelligence. But now in the next five years, if you know if you're following the trends, that's what people call the singularity, which is when the level of intelligence of the AI self passes the level of the human and they have consciousness we are conscious today. They don't have right,
Chris Rainey 16:59
which is scary. That's like Terminator.
Gustavo 17:03
Yeah, and that's what I was saying. My favourite movie is the matrix. And I'm
Chris Rainey 17:06
okay on a matrix. Yeah, matrix. Is it better version? Yeah,
Gustavo 17:09
I love what we're seeing today is funny enough. How is mirroring? That's pretty scary. Yeah, it's pretty scary. But again, you saw our choices. If we made the right choices today, then there is nothing to fear, we will use technology to benefit ourselves into augmented reality, or two men are at capacity, like for example, with artificial intelligence for the neural link, what Elon is trying to do. Great you know, for people who have this is a mental health problems or disease like genetically issues with like Alzheimer's, stuff like that. Great that can help in the health industry, there is a tonne of potential. And today there is a lot of companies who are using it for the good of things. But on the other side, you know, what happens when you develop ai ai is like, it's like a weapon. weaponize it. You said, Well, when
Chris Rainey 17:56
I said, if you have watched, we haven't got a good track record as humans when it comes
Gustavo 18:00
to Funny enough, have you watched the movie Oppenheimer? No,
Chris Rainey 18:02
but that I literally just thinking about that. As I said, we haven't got a good track record. Yeah, watch
Gustavo 18:08
the movie open Heimer. And in a way, it reminds me like if you see what they went through, during that time period, is exactly what we're going through. Now. The people who are developing the atomic bomb at the time, after they develop it, they realise the implication, they were like, Oh, hold on, we need to be careful with this. We need to understand better the consequences. They actually get conscious and realise what will happen when we did social media, and that was social media, with technology. We didn't understood some of the implications, because we went too fast. And a lot of it has implications today in mental health. You see kids, I will say millennials, I was just telling you, yeah, more than 60% of millennials are having challenges with mental health from social media. Social media is a big component that is everything. But it's a big component of that, right? So my fear with AI is that imagine that you have something that is even better than you understanding human behaviour, we have 100 million connections in our brain, trillion 100 trillion as Shadow today with AI have 1 trillion. And you can make faster connections in that one to in that one to network number we can do with our brains. And that's what we're trying to hit. So now. We have been the most sophisticated being in this planet for all these 1000s of years. We're about to become second place. And trust me, you have seen through humanity what happens when you have two different groups of countries and one has more weapons than the other what happens. My fear is that we can weaponize you know AI and then you know, it can change your life for the worse. You can change the way you think it can change the way you make decisions. It can change the way your your work. Some countries are really starting to test the idea of you know, having given people like a minimum wage and see how they react, how the economy reacts because there might be a point there If we keep replacing jobs with technology, we might have a lot of people that will need a complementary income or something. Yeah, for the day to day life.
Chris Rainey 20:08
There's quite a few countries that already done that. Right. Yeah, some
Gustavo 20:11
some countries are testing it. And also the concept of the four day week. Yeah. Which I'm a highly I highly advocate for that. And when I say this, sometimes people like, oh, my gosh, is that we're working less our being lazy. No, there is no way that you can keep up with the rate of learning that you are supposed to keep up. If you keep working hard, right? You are supposed to work smart and learn heart. That should be
Chris Rainey 20:35
but that's kind of one of the issues with technology, right? Is people are using that free time and just replacing it with more work. It's like, okay, you're free like that time now. Now, you can do even more of that work. No, no, that shouldn't be. It shouldn't be that's leading to burnout. And we're seeing that already with people, right?
Gustavo 20:51
I remember interviewing with companies and asking them, like, what's your policy for remote work. And if I if, if an executive will tell me, like, we don't believe in remote work, this is 2017, I'll be like, Okay, this might not be the right company for me just because of that, that tells me how you think. And in that time when the pandemic happened, luckily, for me, I was working for our Cincinnati electric at the time, I was the head of the VP of analytics, on the people division, you know, like any company has opportunities, but in that regard, they were very flexible. And my thing was all over the world. I have people in Australia, people in Ireland, a remote in Spain, you're everywhere, everybody was remote, we will see shoulder twice a year, or maybe once a year in a team building exercise, and we will spend time together in person. But for the most part, we learn how to work remotely. When the pandemic happened, our team didn't skip a beat, nothing happened. Because we knew how to operate in that environment like you, we were able to adapt very quickly. And I saw a lot of businesses and a lot of teams crumble when that happened, just because they didn't know how to operate in a flexible environment. Specifically,
Chris Rainey 21:54
going back to HR for a second, what some of the applications that you see around HR as a function can use large language models.
Gustavo 22:03
I mean, there is a tonne of implications. I'll give an example. We were talking about learning earlier today. Think about it this way. There are Amazon, for example, was the one who made famous these recommendations for products, right building your products, right? If you today have benefits, like benefits team or your talent team, you know, think about how can use these models in AI to actually recommend curriculum for learning or path that is personalised to a specific employee or associate in your company. That's an amazing application. Like when I was packing Walmart, I used to do a genetic algorithms to optimise the benefit, or the perks that an associate will get. And that was a very complex exercise at the time. And you can do it like we did it once it was a one time shot, you get the data and he's okay, this is the package that you should give, right? Well, now you can get so much more granular with it, you can personalise it, and you can change every time and you can change every day, you know, everything is so it's a different level of speed and personalization. Right. So if you're an executive financial into the, you know, using those algorithms that are being used regularly in marketing, or other fields to recommend your products or your benefits, you are missing out on your application that I think is the fastest growing application in terms of large language models that I'm seeing in terms of API's, these models that are similar to the SHA GPT, with a natural language process, like the search with a AI in the background, right? If you're using one of those, he has grown more than 1,000%, just seven months, I think like from November to I think it was May, November of last year through May of this year at 1,000% growth, Jo's on companies who are using API's for these kinds of engines. Yeah, and think about how you're actually doing some of that, too. And yeah, we're a
Chris Rainey 23:54
team of 10. And we're already using it. Yeah. In all, which we're excited to share, like, yeah, it's incredible. And it's not easy, but I mean, relatively easy. And cost effective. Even if a small company like mine can make it happen pretty quickly. And it's gonna be a game changer. Career. Yeah,
Gustavo 24:10
and you'll figure out kudos to you guys. But if you haven't figured out if you don't have a huge amount of resources to work on this, there are companies that you can partner with to do it. Or if you're large companies, I still talk to some of my friends in like big companies, Starbucks, Walmart, so on. And they have their own resources within the company that are building their own. Some of them are startups now that are coming out in the HR space that you can actually they will do it for you and they will instal it for you in your company. So there is no excuse not to get into this. If you don't get into this, I promise you you're gonna get behind you're gonna stay behind very quickly. Right?
Chris Rainey 24:44
Is that a lot of what you help companies with? Yeah, so in so explain that a little bit more about obviously what you're doing. I'm human.
Gustavo 24:50
Yeah. So for example, I will tell you, when I look at when I go to a company usually have three metrics of success that I look at, and they're all based on individuals. Because I care for an Indian, I care for the experience, I don't care so much for the technology. So usually what I do is I do an assessment, I see where you are in your journey like most companies do. I see your technology stack, I see your talent on the team, and I see what you want to get to. And basically, I do, like a journey, you might be like climbing a mountain, right? And I do a journey. And I say, Okay, here's what your vision is, here's what you want to get to, I want the experience for your stakeholders to be X percent, I want your adoption, your products, X percent, like I look at this as a business of you're selling a product. And I look at it as a team that is within a company, you know, you're you're a team within the company, but your job is to be an entrepreneur, and we want to have X percent of adoption, we want to save X amount of time. And then if you follow this logic, I guarantee you, and you can get to the business, you will get X amount in revenue. You see, I'm going backwards to the logical light
Chris Rainey 25:56
when we first spoke about pay per leg. So the first piece of advice, you said to me, Chris, I was like, where do you start? You're like, so let's start with the business problem. And work backwards, correct. From there. Same same philosophy. And I'm
Gustavo 26:07
telling you, I've been saying this for, you know, for 10 years, and I still go to companies. And when they design the tool, I'm telling you, they start with the technology, or they start with like all these criteria, hundreds of checklists that they go through. And when asked them, Okay, how are you going to measure the success of this? Well, the CPU capacity and the velocity are the two and say, no, what is gonna be the end user experience, what is going to be their adoption, the time says, and then from there, you know, depending on your company, if you want to get into wellbeing, for instance, environment, you know, there are other stuff that are not as technical you can measure with the product, sure. But you should be measuring, we should be selling your data as a product, your company, first of all, you should be selling your services as a product, not as we're going to do one project, I'll give an example why this is important. I don't know the exact number for HR. But in general, most companies who develop algorithms, like machine learning algorithms, they were developing five in the past, and there was one in production. Imagine that. So for every five big projects that you work on machine learning, only one was actually implemented into production. Now we're getting better, we're getting one out of three. But the idea will be to get 100%, of production of your models, you see. And part of the issue that we had in the past, somebody was technology. Some of it was the system security, scalability, all that stuff, the technical aspects. Yeah. But in reality, it was a disconnect between the business and what we were building here, like, we were building something that looks very cool for us, but they're like, We don't need solving. So we're not gonna use it. At least now we're getting closer and closer to a space where people are actually implementing what is input by technologies, the data, analytics team, etc,
Chris Rainey 27:50
comes back to the people with right again, because if you don't understand the pain points, and don't have the necessary relationships, internally, you can be up a genius, and have the best options in a while, but you're not gonna get anywhere.
Gustavo 28:04
Yeah. And you need to have critical mass. Sometimes you go to a company, and you're the only sane person in the room, right? And they're like, 20, people that are still thinking operating like, Oh, this is what we used to do. And why change? I mean, we've been doing it for 15 years, why change? Now, I'm telling you, that's one of the, when I hear that expression, I know this is gonna be a hard transformation. If you tell me you're doing something for 15 years, and why change? Now, if you had that mindset, it's very hard for you to change your mindset. But it's crazy,
Chris Rainey 28:32
right? Wasn't you also working on a project of where companies shouldn't shouldn't invest their resources in terms of offices? Correct? Yeah, explain that better? Me. I did a terrible job of just explaining that.
Gustavo 28:45
No. So what happens all the time? And you can see these four global companies, right having real estate in UK? Yes, Singapore, is Barcelona, you know, Boston, New York, these are very high costs of retail under Plan. Yeah, it's immense. And so one thing that people were able to pick up during the pandemic is how do I invest in my real estate, my footprint? Do I need to have all these people in the offices like, cost effective wise, let's move some offices through India, you know, because it might be cheaper to have the operations there. If we have three floors in the Hong Kong buildings, let's reduce to one and have everybody else work remotely. So we used to help advise the company on doing that, again, because of the background on business continuity, it was easy for me to see how can you pivot quickly and actually, you know, look at the words you
Chris Rainey 29:33
utilise, to kind of get an understanding of how much you would need. How did you measure that like,
Gustavo 29:39
is basically you know, you have the costs of the actual footprint, like how much you pay on lease, yeah, you have contracts, and then you work backwards and see okay, what percentage of people in this floor can do their jobs and operate in that way, and then you do basically a return on investment, right? You have to have X amount of people working on this floor for this amount of time. Does it make sense for me to have the list here? Or should I just change positions? Okay, people who do analytics, you know, if you do geospatial analytics when you try to put a new store or if you put a store here and there's cannibalization, saying sim is a similar working backwards approach or working backwards, interesting to get to that, right. But you just
Chris Rainey 30:21
bought a new thing at a time no one was really doing that. Like all of a sudden, all of the leaders are speaking to a reassessing their real estate portfolio and having to work in a way you just said, but that's not the first time they've ever had to do that.
Gustavo 30:36
Especially that scale, right? Because yeah, it was happening globally. Like you have seen many people like maybe like they were doing in a country. But exactly, or sometimes, the whole thing exactly, but not at that scale, for sure. That was a whole different ballgame. But again, it shows how much we can do it kind of break that paradigm that you have to have these huge offices or this huge campus to operate, you don't need that. I want to challenge every leader that is listening to this in HR. And I want to challenge this and I want to say to your point, what is the balance, right? Depending on the function, we all support the business. So let's say we're supporting our business. And to your point, these are timing for the business. If there is something that needs to happen in six months for the business, there is no way that you can plan a project or a product for two years. You miss you miss the mark. Right? It's already gone. Yeah. So that we should ask ourselves is okay, if we are supposed to hit a six month mark, what are the steps that we need to do and reverse engineer to get to the stage? And again, you also have to have a change of culture. And I'm telling you this with all my my love, depending for the country that you are some countries are very risk adverse. It's a generalisation. Right? In every country, there are different pockets of people, different companies, different cultures within the country. But I see in general speaking, I come from Latin America, Panama, very closely society, amazing for family relationships. But at work, you are very worried if you made a mistake, right? Because the group is important how you're perceived. And you are always sometimes working half step. Yeah. Right. And so my point is, if you're in a culture is like that, that is a true challenge. Yeah. Because if I tell you time is relative, I have seen the same project happen in a company in two years that I was able to do in three months. Yeah, the same exact project, the same technology is just same way nothing changed is not the country, the culture and the people, how people and their mindset of taking risks and how they will feel if something fails to me, there is no failure. There is learning exactly this learning.
Chris Rainey 32:38
I mean, I'd say it's an opportunity for growth and low you learn something out of it's not failure. It's only a failure, if you give up early or if you don't learn from it, listen for let you go, parting piece of advice, or things LLM and AI? And then also, where can people connect with you gonna reach out and learn more about you? For
Gustavo 32:55
sure. So again, my main advice to you is, number one, think in terms of ethical aI think in terms of the human experience. For everything you design, make sure you challenge your IT functions or your leadership in having guidelines for the ethics and how you handle the data. If you have that document that will help you a lot to at least have a framework in which you operate for the future.
Chris Rainey 33:20
If you don't have one or strategy btw can help you right? Well, yeah.
Gustavo 33:23
Go to my website. Okay, WW, I'm human.com. I have actually guidelines you can actually download. Amazing is there Yeah, you can just download from there. And you can see, and I want it to do as a service because I can, I'm telling you, I am not afraid of the future. But I am concerned of how these people are disconnected from the future. So wake up to what is happening, please make sure your decisions and your designs are always with a human experience. As through angle, that should be the reality, you should not be saying thank you, to us for designing technology. I
Chris Rainey 33:55
feel like you're talking to the right audience who aren't who understand that, but it's good to reiterate it. Also definitely connect with the server on LinkedIn, you're pretty active there. But wherever you're listening or watching right now, those links are going to be below. So whether it's you know, so make sure you go and connect there, check out my website. And yeah, man, it's honestly it's been a pleasure to see, like you grow and develop over the years to where you are now. And I'm so excited for the new journey that you're on. You know, you're not only getting to impact it in one organisation but what with many and have a broader impact on society in general,
Gustavo 34:29
like Wes and I wanted to say thank you because I also have seen you grown from your, from your bedroom doing all these things. And I see how you have grown in seven years now you have these amazing setup, you have this audience all these networks across the growth like you have, you have built your brand and your reputation and people trust you and you are doing a lot of good for humanity, which I'm, you know, I love to advocate for people like you. So, again, thank you for what you're doing. Keep doing what you're doing. And don't be afraid to take risk like you have done in the past. Right Just keep doing what you're doing. Be courageous
Chris Rainey 35:00
Well thanks a lot man
Gustavo 35:02
All right thank you
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Victoria Klug, HR Director Eastern Europe at Beiersdorf.