Iulian Circo

One of the most common symptoms associated with COVID-19 is probably the cough. Now, what if you could quantify that more than giving a simple description about it? Well, that’s what the cough tracking app Hyfe does, and co-founder Iulian Circo is here to tell us what it’s all about. 

Initially working in the humanitarian sector in various countries, Iulian shared his experiences working in war zones and high-intensity environments and how he was drawn to making a similar impact, but this time in a different sector. Now, he’s founded and currently advises many organizations and startups that are geared on making an impact in the world in so many different ways. Iulian also talks about his entrepreneurial journey, Hyfe’s use cases, and the significance of technology, especially in healthcare and new fields like acoustic epidemiology. Apart from that, Iulian said that this generation is ready to make an impact, and so now is the best time to turn your idea into a reality.

With Hyfe, it is an artificial intelligence algorithm that tracks cough in real time. To date, they have over 140 million samples collected from all parts of the world. Now, that’s impressive. They are undoubtedly and proudly the market leader in this space thanks to the wide range of their user demographics which has resulted in an extremely diverse and unbiased data set. It’s a really interesting episode you won’t want to miss.

Iulian’s key lessons and quotes from this episode were:

• “In critical environments and extreme environments, technology is a lifesaver, and it's definitely a multiplier for people trying to get things done.” (5:42)
• “Humanity will always prevail.” (14:19)
• “Where we are, there's no playbook. So, what we do is we have to discover basically where the market is and where the value is.” (28:21)
• “Running a business, and running a startup… that's a very healthy attitude to have, to always be very rigorous in deciding, what is the metric that moves my needle?” (37:07)
• “I don't think there's been ever a better time to do it, and anybody who is thinking about doing that should absolutely do it right away.” (44:33)

In this episode, we also talked about:

• The nonlinear evolution of Iulian’s career (3:01)
• The lessons Iulian learned from his time in the humanitarian sector (11:35)
• Hyfe and how it works (15:41)
• The cough tracking space with and without Hyfe (29:09)
• Iulian’s advice for aspiring entrepreneurs (39:11)
• Mistakes Iulian’s made that he wants you to avoid (45:04)

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Transcript of the episode

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Maiko Schaffrath  00:00

This episode is brought to you by Content Multiplied. It's not a secret anymore that content creation is really important, but very few people talk about the importance of consistency, and I myself have really struggled with that consistency. And for that reason, I looked for a solution, and Content Multiplied was a really good one for me. Since using them, I've been able to focus on what I enjoy the most which is recording podcasts while Mhyla and her team are really taking care of everything else. Whether you have a podcast, you're holding keynote speeches, you're doing a YouTube series, you're writing a blog, a newsletter, a book, the Content Multiplied team can really take whatever you're producing and repurpose it into a series of micro-content. And suddenly, you have dozens and dozens of pieces that can be shared for you, and Content Multiplied even takes care of that for you. Unlock your content superpower with Content Multiplied and go to contentmultiplied.com today. That's contentmultiplied.com. Thanks, Mhyla, and let's go into the show. 

You are listening to Impact Hustlers, and I am your host, Maiko Schaffrath. I have made it my mission to inspire the next generation of entrepreneurs to solve some of the world's biggest social and environmental problems. And for this reason, I am speaking to some of the best entrepreneurs out there who are solving problems such as food waste, climate change, poverty, and homelessness. My goal is that Impact Hustlers will inspire you, either by starting an impact business yourself, by joining the team of one, or by taking a small step, whatever that may be, towards being part of the solution to the world's biggest problems. 

In today's episode, I speak to Iulian Circo, the co-founder of Hyfe, an AI-driven tool that is able to detect coughs through a smartphone app. This technology is now used to produce more reliable data for clinical studies worldwide such as studies researching COVID-19 and tuberculosis. Iulian has started a range of successful companies and nonprofits and has been on a journey to combine social impact and profit since he left the humanitarian sector a few years ago. It's really great to have you on the show, Iulian, and thanks for making the time.

Iulian Circo  02:43

Thanks so much for having me, Maiko. I'm very excited about this.

Maiko Schaffrath  02:47

Let's do this. Alright. So, as I already said, you started your career as a humanitarian and have focused your work on a range of different social issues since then. Tell us a bit more about your story, and why are you doing what you do?

Iulian Circo  03:05

So, I have a nonlinear evolution in my career, Maiko, and I think it's typical for entrepreneurs and I think to some extent, it's typical for humanitarian workers, at least the ones that make it long-term in the humanitarian sector. People tend to be nonlinear, and I think that that's a good thing and it's something that I see as a huge advantage and something that we should respect more in these days. So, I started my career as a humanitarian worker, and that's probably because I came of age in the 80s, I guess, and early 90s. At the time, there were fundamental changes happening all around us. I was really close to some of those changes, the end of the Cold War, whatever came after it, all the conflicts of the 90s from the Balkans to East Timor to, later on, Afghanistan, and my original passion has been human rights protection, basically, and that's my background. I've specialized in human rights protection, and I've embarked on a career working in human rights protection and focusing mostly on post-conflict environments. I spent a lot of time working with displaced persons, working in the first line of response after a conflict, those sorts of settings, and I loved every minute of that. It's very satisfying work. The BS to impact ratio is optimal in my opinion. It's very action-oriented. I love the energy. I love the people that end up working and being high-performance in that environment. Ultimately, it's a highly educational thing to do, and I kind of lived off a suitcase for 10 years, moving from East Timor, to Somalia, to places like this. And yeah, it's been amazing, and it's opened my eyes, not only to the need to do these sorts of work and to the complexity of the impact space, but also to the way that people are resilient and the way that people in any kind of circumstances preserve their humanity and finally, also in the way that they take technology in an environment like that, and they use it to improve their lives. So, technology in critical environments and extreme environments, technology is a lifesaver, and it's definitely a multiplier for people trying to get things done, to stay close their families, and I credit that to my obsession throughout the rest of my career in trying to find emerging technologies, trying to find ways to use these emerging technologies in ways that we can achieve impact at scale. That's been my first career. Eventually, I pivoted into more traditional development, which is similar in the sense that you're in emerging markets, in places without too much infrastructure, but the objective is very different. In traditional development, your job is to create sustainable infrastructure, to create impact that's long-term. Whereas in a humanitarian setting, the impact's just from a day to the next, basically, Let's just eliminate this critical situation, and you're not too worried about the long-term impact of that and long-term sustainability. Very, very different setting, equally challenging, equally interesting. And yeah, so I've had the fortune to be at the center of some very, very interesting projects. I was in the middle of the global response to the HIV epidemic. I've had the privilege to work in a country, Swaziland, which you mentioned before we spoke that you also visited, which was the epicenter of the epidemic in those days, and I was based there working with HIV, working with malaria, working with sanitation, and also working in ways that we were trying to build products and services that would use marketing principles to have impact. It's a very small niche in global development and one that's often ignored, because global development is kind of a top-down, a lot of money given to large organizations type setup. I again had the privilege to work with an organization and with a team where the objective was, can we take commercial principles and apply them basically to build, to create markets that would make these needs that exists now, the need for products or services, that would address them in ways that would not require us to be around forever providing the services? We were working on things like very detailed market segmentation and trying to find premium market segments where we could put a product that would be profitable, and then the profit of that premium segment product would be used to cross-subsidize the lower income segments in the market. For example, you take mosquito net, and you just make a very premium product for it, for that 1% or 0.1% of the population, and you make an 80%-100% margin on that, because it's a premium product. And then, the cash that you get from that margin, you'll apply to sell exactly the same product with a different brand subsidized, so the people who cannot afford to pay full price get a high quality product. Often, I can tell you this, it's the same product. It's just the brand's different. These are ways that you can bring these sorts of products into the market in ways that would work and would have an impact going forward. And going into behavioral stuff and learning about consumer behavior in those markets, which are very, very different from consumer behavior principles that you learn if you do an MBA somewhere in Western Europe or in the US. Long story short, that [was] another super educational period of my life. Loved it. And out of that work, I became a reluctant entrepreneur, I guess. I started to look at ways that we can use technology to make that sort of work better, and I've built first a piece of technology that became something that a lot of other organizations were interested in. And then, that launched me on an entrepreneur journey, because we spun that out into a business, into a social enterprise, and we launched in a number of other countries, and the rest is history. And from there on, I went and built a number of other companies across different sectors. And here I am, 10 years later or whatever, in my entrepreneurial journey working on artificial intelligence and healthcare. Yeah.

Maiko Schaffrath  10:40

Great, yeah. We'll talk about that in a second. One thing that struck me when I looked at your profile and your experience is, you've spent a lot of your time as well working in war zones and really difficult environments. I personally can't imagine an environment that's scarier and full of uncertainty than a war zone and trying to organize things, getting things done in that type of environment. Do you think you've learned lessons in that time that you're still applying today to this different type of uncertainty that you get with entrepreneurship? Obviously, it's not comparable, but I'm sure there are many difficult situations you have to overcome that will still help you today in terms of running companies.

Iulian Circo  11:35

Yeah, I mean, I think that I have a pretty high tolerance to uncertainty, and I guess I have a risk profile that is a bit on the riskier side than most people, and I guess that converts well into entrepreneurship. At the same time, the one thing that I always say when I talk to people about volatile environments and war situation is that if you look at it from afar, it looks like everywhere you go, it's dangerous. The closer you go, the closer you are to humans and the closer you are to humanity. It's almost cheesy what I'm saying, but people get on with their lives. If you read those books from even in Europe, during the Second World War, life just happened. Atrocities happened left and right, but somehow, people stayed close their families, and they maintained social relationships, and they maintained the humanity throughout most of that, and that's something that I've seen again and again. Actually, I feel that- there's different types of risk, and there's different types of violence that you're exposed to. But if you're in a place like- take Somalia. I lived two years in Somalia, and I've never actually felt unsafe the way that you might feel walking down a dodgy neighborhood in the US. It's a different type of safety, or lack thereof. Walking down a dodgy neighborhood in the US is I open myself up to randomness. There's an opportunity for someone to just randomly get violent or whatever. That never happens in Somalia. It just doesn't happen. If you're a victim of some violence, which is very probable and possible, it's not a random thing that just happens. It's something that's part of a plan, well, or not thought through, but it's a different type of risk that you're exposing yourself to. And the latter risk, although the consequences can be much worse, is also a bit easier to manage. It's a bit easier to plan your life in such a way that you don't put yourself into that situation. There's an armed conflict, don't take sides. There are some principles that you can follow, and you'll be okay, I guess. Actually, you meet people in places like this that are even building thriving businesses, and they manage their lives as they can considering the circumstances, and that's one of the biggest sources of optimism for me. Humanity will always prevail.

Maiko Schaffrath  14:21

Yeah, I love it. I definitely haven't spent any time in war zones in my life. But when I when I was in South Africa, I did live in Johannesburg, and even that when I told people about it, and initially, I lived in like really safe suburb, well, supposedly safe, and later moved into Soweto, which is known as the biggest township in South Africa. A lot of people in Europe would be like completely scared like me, telling them that I live there and that I'm just using the normal transport and all that. I think a lot of this is that, yeah, the closer you move, the more you see the reality and humanity of people and people actually doing positive things. Whereas if you zoom out and you're just following media loosely, you're seeing all the worst, the worst of the worst, bad news and all that, so I can completely relate to that, yeah. Let's move onto Hyfe, and that's the reason why I invited you. I think we could record a podcast for each of your startups, but we only have time for one today. So, let's cover in a few sentences, how does Hyfe work and how is it different from existing solutions out there?

Iulian Circo  15:41

Hyfe is basically a very simple product. It tracks coughs in real-time, and it basically creates a longitudinal map of your coughing over time. The craziest thing is that if you get sick now in London and you end up at the best hospital in London, you're going to be connected to all sorts of super-smart devices that will measure all these biomarkers about you. If you have a respiratory condition and you're coughing, your cough will be evaluated by the doctor coming in during the rounds in the morning and saying, "Maiko, how's your cough?," and you're going to say, "It's good," or, "It's bad," and that's the extent of that evaluation. That's the clinical evaluation right there. 

So, although cough is the most common symptom across all diseases, there is no way to quantify, and that's something that is mind-bending for me. So, we just built a way to quantify cough. It runs on a phone. We even have a small wearable that we are working on now and we're testing it out. It works on third party devices. We're not depending on this or the other device. 

Our core product is an algorithm, which is an artificial intelligence algorithm that detects cough in the real world. And it's different, I mean, there are teams working on this and actually, acoustic epidemiology is, in my opinion, one of the most exciting territories in healthcare because it's so new. People look for signatures of diseases in all sorts of sources. You have imaging. You go to a laboratory. There's an x-ray. You have chemical stuff where they take blood or lymph. They run an analysis. But sound, no one's done anything about sound. Yet, if you talk to a doctor, they will tell you an experience. 

They will tell you, "Oh, I can listen to this person. I can listen to their coughing. I can listen to their wheezing, and I can tell you a lot about what's wrong with them." Yet, no one's built anything in that space. So, there are more and more teams. I mean, I'm happy to say that we are the pioneers in this space, and we're definitely the market leader, definitely in cough. 

The way that we're different and we managed to come on the top of this market so quickly is that your typical machine learning team comes out of university. That's what happens. You have a bunch of really smart people in a really good university, and they look at it as an interesting scientific question. Can we build a machine that can detect coughs? Or can we build a machine that can classify different types of coughs? And then, they go about being super smart and super academic about this. 

The first challenge will be, okay, it's a machine learning model, so it needs a data set to be trained. So, they just walk down the aisle at the university where they are based and they ask everyone they need, "Hey, could you please cough into these microphones?" And then, they have enough people coughing. They've maybe a thousand or 500 people coughing, and that's the starting data set, but there's two foundational problems with that. 

One is, that data set has a social demographic bias, and this is a big problem. In this day and age, this is a very common problem and maybe one of the most solid arguments against AI models. There is a bias inherent in the way that you build a data set, because if you are in the corridor of a university where there is a smart team asking people to provide coughs, there's already a huge bias there. First of all, there's an age bias, then there's a social demographic background bias, then there's a geographic bias. 

And then, you build a model that is based on this group and because the model is just unstructured, it just looks for patterns, 10 years down the road, you will have a crazy bias coming into your outputs from that model or for the evolved version of that model that you will never be able to address. So, that's a huge problem. You see extreme versions of this when people do bots and put them on Twitter and two days later, the bots just spur racist tweets, because the bot trains on basically what happens there and what happens there, some people are louder than others. And often, the people who are loud have very extreme opinions, and there's a bias in that model, and you can't fix that. You just have to rebuild the model.

Maiko Schaffrath  20:13

So, what have you trained your models? Yeah, what have you trained your models with data?

Iulian Circo  20:20

I love this. So, we decided to build this and one week later, we had an app in the App Store. We just put an app out there. Our assumption was that there are enough people out there that care about tracking their cough, they care about the novelty of it, and they care about the potential value, that they will just do it, even if the model is really bad. So, our first version of our model was really bad. 

But as people started downloading it, it got better and better, and we bypassed that first problem that AI teams have, because our users were from all over the world across all demographics. We had waves of users coming in from Pakistan, and Bangladesh, and North India, and China, and all sorts of places, Latin America, Europe, Africa, old people, young people, educated people, taxi drivers. That allowed us to make sure that our model is built on a very diverse data set. The second bias, and this is very interesting, and it's probably specific to cough and a few other things is, if I say to you now, "Maiko, I'm about to take a screenshot, please smile. You're going to do this," and everybody knows [that] that's a smile. But fundamentally, it's a fake smile. It's a manufactured smile. And if our thesis is that there's information in a cough, then we want that cough to be organic. It's like, if I want to see how Maiko laughs, I have to crack a really good joke, and there's a difference between Maiko's laugh after I crack that joke and Maiko's laugh when I say, "Please laugh, cheers," and take a picture. This is the other bias that you have in basically models built by academic teams. They go around and ask people to cough into a microphone, or they set up a website and say, "Please go to this website and cough," but you're missing all that subtle, organic signal that would be present if your cough happens naturally. And it's not only signaling the amplitude in the structure of that one cough, but it's longitudinal stuff. Was it three coughs? Was it a cluster of three coughs? Or was it just one cough? And then, you add to that context,  "Oh, it always happens at night. Oh, it always happens when you lie down, or after you eat, or after you had ice cream." There are all these other variables that you can add in, which all convert into signal that can help our models detect things that could otherwise not be obvious. I have a really long story to tell you how our models are different. That's our biggest mode, and I can tell you that right now, because of this approach, we just put an app on the market, we made sure that we create value for as many people as possible, we have the largest cough data set in the world by far. I can tell you that we have almost 140 million samples in our dataset. I was just reading a paper the other day, which I'm happy to share with you, where someone's proposing a way to count cough and they had 48 samples, and they were like, "Oh my god, we have 48 samples from 11 people." And we have 140 million. In fact, there's so many of them that it's our biggest bottleneck. We just don't have the bandwidth to process all of it. And every day, there's more and more sounds because we have so many users that use our app.

Maiko Schaffrath  24:04

Got it. Super interesting. I guess the biggest use case for an app and for technology like this at the moment is research. I mentioned in the beginning that your technology is already used for some COVID-19 research, some tuberculosis research, and I can imagine how this is being run without your solution. It's probably being run by asking people, "How often did you cough in the last day?," or something like that. Is that the case? How does it work without your solution?  

This episode is brought to you by Content Multiplied. I've been using Content Multiplied to produce the Impact Hustlers podcast as well as for repurposing each episode into a number of pieces of micro content that are then shared across our social media channels. Everybody's talking about creating content. I think it's not a secret anymore that content curation is really important, but very few people talk about the importance of consistency, and I myself have really struggled with that consistency. And for that reason, I looked for a solution, and Content Multiplied was a really good one for me. With all the moving pieces in the business, you can't spend all your time creating and pushing out new content. That's why I've started working with Mhyla and her team at Content Multiplied, which always goes above and beyond. They are [an] all-in-one content management and repurposing service that can handle really all your content needs. Since using them, I've been able to focus on what I enjoy the most, which is recording podcasts while Mhyla and her team are really taking care of everything else. Whether you have a podcast, you're holding keynote speeches, you're doing a YouTube series, you're writing a blog, a newsletter, a book, the Content Multiplied team can really take whatever you're producing and repurpose it into a series of micro content. And suddenly, you have dozens and dozens of pieces that can be shared for you. And Content Multiplied even takes care of that for you. They can also help you strategize, multiply, and transform your content into more engaging formats that your audience will love. Unlock your content superpower with Content Multiplied and go to contentmultiplied.com today. That's contentmultiplied.com. Thanks, Mhyla, and let's go into the show.

Iulian Circo  26:35

So, the established way to do this is to either ask people, I guess. If you're on a study at a large scale, you basically have to ask people, because otherwise, it's just not possible. If you're on a small scale study, there are some products out there, which are basically mp3 recorders, like tape recorders that participants are given. 

They basically strap them around their neck, like a little thing like this. And they have to keep that on them for 24 hours. And then, they bring it back to the investigator who then hires people to sit with a headphone and listen to 24 hours of someone's life, accelerated. You can just do it 2X and eliminate the pauses. And then, every time there's a cough, they have a clicker, "cough, cough, cough," and that's how they count the coughs, and that's basically the alternative. It's a no-brainer. Our product works at any scale, virtually. You can run cohorts, and not only do you get the charts for everyone, you can dive in and analyze individual groups, cohorts, all of that. So, that's an interesting market for us. We also have a consumer product. We have an app in the App Store, which we don't make any money out of. We don't sell anything. No one pays us for that. We don't sell the data. And the only reason why we have that is, first of all, because we are creating a category. We don't come into a category where there's a playbook. If you build a SaaS product, there's a playbook. You have to have a license, and that's how it is, and people have to click here, and it has to run in the cloud. Where we are, there's no playbook. So, what we do is we have to discover basically where the market is and where the value is. And then, we have a consumer product, because the number one priority for us is to provide a lot of value for people and learn how that value converts into people's behavior. And once we understand that, A, we get more data from these people, because they continue to use our app. B, we get a lot of feedback from them and insights: what do they want, how the chart needs to be, what features they want. And three, we convert all of that into our other products. We stay on top of this market, and we define this category of cough tracking using AI.

Maiko Schaffrath  29:09

Got it. And what difference does this actually make? Obviously, it's much more accurate. You're capturing the accuracy of how often people cough. But what does that mean for the clinical use cases, for example, for the research use cases? What are you enabling by doing this?

Iulian Circo  29:34

So, there's different use cases and we're enabling for each of them is slightly different. For the consumer use case, we're putting in the hands of a patient a very powerful tool, which is data, because there's people out there and maybe you even have in your extended circles people who just cough, and they don't understand why. There's a mix of allergies or something that happened, they got sick, they never got better and just cough. The cough doesn't go away. It's shocking to learn that 10% of adults worldwide have some form of cough that they can't really explain, and these people have similar journeys. They go to some doctor, the doctor says, "Well, take some weeks or get some rest. Have some tea with honey," because there isn't really much that they can do about it. And then eventually, they're frustrated. Their quality of life is affected. And eventually, they get to the point where they try to take things into their own hands. So, they change their diet. They say, "Well, if I don't eat gluten, my cough will go down, or, if I don't eat in the evening, or I have less acid in life." People just have all sorts of theories that they experiment with, and our app provides them a way to find correlations. "Oh, on Tuesday, I stopped eating gluten and look, my cough frequency went down." Because cough frequency is something that the human brain just doesn't register. If I ask you now how many times you coughed yesterday and was it more than a day before, you have no idea. Although you probably coughed about 20 times yesterday, you have no idea about that, because the brain doesn't register it. The second thing is they go to the doctor and say, "Hey, look," and we actually have these amazing stories of teams of doctors and patients basically working together to customize either the treatment or the management of a condition, because they can see the objective way in which cough frequency changes with decisions that they take to get it. So, that one. On the research side, it's the same thing. If you want to put on the market a treatment, a vaccine, within a respiratory pandemic, you're working on a vaccine or you're working on a treatment, you have to know if the treatment affects the cough of those people in any way, of your cohort. So, you have three cohorts, you have your treatment cohort, your placebo cohort, and you have your control cohort. Cough is probably an endpoint, is probably an important piece of information that you look at as you're doing these trials, because you have to see if the symptoms, which cough is an important symptom, are affected in any way by the treatment. And, if you're working on something like that, then we're probably the best tool you can get because the alternative is to send people home with tape recorders and have other people listen to them. Finally, and probably the most interesting use case, which is, we're not there yet, because there's regulatory things is that I believe that the health care, just like everything else, will go digital, more and more. And that means that when you go to the doctor and get a prescription, there is a digital side of that prescription, and this digital side could be a wearable. So, you get a treatment for something, you go to the pharmacy, they give you the pill, and they ask you, "Here's an app," or, "Here's a wearable," and then you go home, and as you take that pill, the wearable monitors your biomarkers that are relevant to your treatment. And the doctor who could be next door or in the next state or on the other side of the wall or a machine could look at this data that comes from your biomarker and take decisions to optimize your treatment so that your secondary effects are reduced, the impact of medication's higher, they do micro doses adjustments, and everybody wins. As a patient, you get the custom treatment, faster outcome. As a doctor, you get better outcome from your patients. And as a payer, you get to pay less because there's less complications and the treatment doesn't take as long as it would take if it wouldn't be customized. And I'm a huge believer in that use case. I'm very bullish on that use case.

Maiko Schaffrath  33:48

Amazing. I can't wait for you to move into that space as well and see more of that. I think next up, I would love to move into covering some of the lessons learned from your journey and how you've approached starting the different companies and organizations you've started. One pattern that struck me is when I look at different organizations you started, you started Triggerise which is actually a charity that's using data as well to connect people to essential services, health care as well in developing countries, you co-founded Proof of Impact which is a platform for social and environmental impact measurement, Hyfe, we just spoke about how crucial data is to your business and to the outcomes that you produce. But at least officially, you're not a data scientist. You don't have a PhD in data science or anything like that. How did you approach running such data-driven businesses in the early days? Is it something that you've trained yourself or are you working with a co-founder? How are you making sure that you've got the right skills in the team as well to run these data-driven businesses?

Iulian Circo  35:04

Yeah, I mean, that's a very interesting perspective. It's one that I actually didn't spend a lot of time thinking about, and thanks for giving me this perspective. Coming from development, in particular, you have so much data, but most of it is just garbage, to be honest. If you think of a typical development project, you get the money given top- down from some donor, typically, and that money comes with a long list of indicators that you have to report on. And most of those indicators are super complex, so it's not like something that you can check-in every day to see what you're doing. Or, they're inputted. You can control them in ways that you shouldn't be able to control them. A typical example is you report a lot of trainings, "Oh, we've trained a lot of people," but that's just an input. With enough resources, I can scale training endlessly, because I find people, I train them. How does that convert into impact? I don't know. And actually, I'm not sure it does, and that's one of the original frustrations that I had coming from the humanitarian sector into the development sector, that basically, the needle that you're watching to see, "Is my work moving the needle or not?," is very fuzzy. You don't really see that needle, and I think that's a huge, missed opportunity. So, I thought, there's so much technology around us. Back in the day, I understand it was hard to measure outputs of anything. But in this day and age, there's so much technology that would be easy to convert data into outputs that you could measure every day. So, I still am very passionate about that. I actually think that running a business, and running a startup in particular where you don't have a lot of resources and you don't have a lot of bandwidth, that's a very healthy attitude to have, to sort of always be very rigorous in deciding, what is the metric that moves my needle? And, how do I stay away from metrics that are either easy to gain or irrelevant to my long-term business? And it's harder than it sounds. And there's people out there who define metrics for themselves, even in startups, that are vanity metrics, metrics that don't really convert into growth to business, and it's a problem that I'm fascinated for. I'm kind of data literate. I'm not a data scientist, but I'm data literate. I'm very much into trying to cut through the BS and find that one or two metric that is easy to measure, is output-based, so hard to gain, and it moves the needle of the business, and it's just  something that I think you have to do. Yeah, and it gets easier as technology as penetration increases.

Maiko Schaffrath  38:15

Got it. I think we've got quite a bit of an audience in this podcast of people that are maybe currently in a corporate job or actually working for charities, working in the humanitarian sector and that would love to learn from your lessons making that transition from [the] humanitarian sector into entrepreneurship. What do you think are opportunities for people out there currently in the humanitarian space? Would you advise them, "Get out of there and innovate. Start a company. Join a company. Do something good through a company"? Or are there a lot of more forward-thinking organizations out there now, more data-driven organizations? What would be your advice to people that are keen to make a difference, make a change and but are currently working in the humanitarian space?

Iulian Circo  39:11

I think there has never been a better time to go on your own in that sector, to be honest, and there's several reasons for that. One is that the development sector in particular, humanitarian space [is] a bit different, because it's really hard and if you focus on making a commercial success in the humanitarian sector, you may miss the opportunity to deliver impact. So, the trade-off between impact and commerce needs to bias towards impact 100% in the humanitarian side, so that's a different area. But in development, and by development, I mean, something that's quite broad, like anything that has a positive impact against one of the 17 indicators, I guess, anywhere in the world. There's never been a better time because the traditional top-down model is dying, and it's dying because the way that it's been financed traditionally is changing. And I mean, I don't want to rabbit hole, but here's the only two ways in which traditional development funding has been committed to impact. One is people sign every month a check. Individuals, you and I, sign every month a check to an organization that we feel strongly, either because they represent the cause that we believe in or because they have a great reputation, and that's a boomer thing. The new generation just doesn't do that. I'm happy to put a bet out there. Any traditional organization that depends on individual donations is racing towards a cliff right now. Because as the generations are changing, the baby boomers were comfortable with paying 200 euros a year or whatever to their favorite charity are just dying out, and the new generation just doesn't do that. It's not a behavior that they do. They just don't sign blind checks to some organization, because they have pictures with starving children. That model is dead. But, I see there an opportunity, because at the same time, this generation that doesn't sign checks like their parents used to, they're way more committed to impact than their parents. So, you have this gap, which is a huge business opportunity. You have people who are super keen to cause or to trigger and facilitate impact to their behavior. That's why you see so many brands that claim for better or worse that they're sustainable, that they're organic, that they're not harming the environment, that they're local. That's because the new consumer genuinely cares about it, and that's amazing. I'm so happy about that. I call this the impact generation. They care about purpose. Yet, the organizations that could deliver this purpose, tons of it, at scale, they're just not innovating. They're not aware of it, because their head's down doing things the way they've done it for so many years, and that's a huge opportunity. If you have an idea, if you want to build a business in that space, this is the time because the consumers are ready. The government donors already as well, because that's the second source of top-down money, taxpayers. Taxpayers are ready for this. Everywhere you go, there's a segment of the population that complains that too much money goes to foreign aid. It's one of the problems that we have in, I guess, in the Western world. They feel that their money is wasted. They feel that their money is not used well, but these are not bad people. These are not people who don't care about impact. They would be super happy to see their taxes put into impact in ways that are transparent, that you can measure, and that are combining perhaps that impact with some sort of sustainable commercial story, so fantastic opportunities. At the same time, if you go into the places that used to be the traditional recipients of aid, the infrastructure's changing there. Internet is everywhere. Smartphones are everywhere. The younger generation is educated. They've been exposed to the same cultural things like everybody else. They're on YouTube. They're on Instagram. So, there's a huge opportunity now. Technology is finally being an equalizer on that sense. It's terrible in so many other ways. But in that sense, it's an equalizer. So, you have people with money who are hungry for innovation and alternative ways to do impact, you have a whole generation committed to impact and defining themselves, their whole identity about that impact, and you have this equalizing force, which is technology, that brings everybody together in a way or another, or within reach. It's a lot easier to reach people today with information and with products than it was when I started my career, when you had to go to the radio and have some radio show hoping that someone in the village will listen to that radio show. I don't think there's been ever a better time to do it, and anybody who is thinking about doing that should absolutely do it right away. [Do] not wait any longer because they're probably going to be doing all right.

Maiko Schaffrath  44:46

That's what we're here for, to inspire exactly that. I've got two more questions for you. One is, throughout your career as an entrepreneur, what do you think was the hardest business lesson for you to learn? Any lesson that you wish you knew when you started out?

Iulian Circo  45:04

Oh, my goodness, Maiko. I've learned them the hard way to be honest. Here's a quick fire list. I've over- innovated, and this sounds counterintuitive. I have made a mistake, which I see so many smart people doing of focusing their innovation resources on things that are not core to their business. I wanted to build a better website. This is probably the biggest mistake that anybody does who started their first business. They just want to make this amazing website, and they spend a lot of time with it, and they spend a lot of energy with it and sometimes, they spend money with it. A website should take half an hour. There's a template. Just use the template. I wish I would have done this in the past. These days, that's what I do. I just take a template, half an hour later, boom, the first version of the website is ready, and then just look at the numbers and improve from there, because templates have been built on the back of tens of thousands of companies building websites, and that sort of wisdom, you can never over-innovate. It's a huge mistake. Then, I've mistaken interest with willingness to buy. If I ask you, "Hey, what's important to you when you order things online?" You're probably going to say, "Oh, I want to package to come quickly." But if I say, "Oh, would you pay $5 for that?," you probably won't do it. And if you're out there researching your market and your customers and you're asking the wrong questions, you may build a business that no one wants to pay for. So, that's another thing, and the way to do it is to just put your proposition out there in the real world as soon as possible. Don't worry about having a product ready. Don't worry about having it all thought through. Just test and ruthlessly, continuously test willingness to convert, people's willingness to pay. It applies to investors as well, by the way. I've spoken to so many investors in my life, and often, I've gotten them super interested because I'm an interesting guy, I guess. I have an interesting story, they want to have dinner, they want to have coffee, but that never converts. A lot of dinners and a lot of coffees don't necessarily convert into, "Let me sign a cheque to invest in your business," and that's another painful lesson I've learned. I mean, I can talk all day about this. I try to educate my customers. That's another thing. You're building a product and you're thinking, "Oh, the customers are not ready for this product. Let me educate them." Huge mistake.  I partnered with wrong people like, oh, my God, every mistake in the book.

Maiko Schaffrath  47:49

We should do another episode on that. I think a good resource on talking to customers, which I feel like I'm a broken record on. It's definitely not a hidden gem anymore. It's the go-to manual for a lot of people but around customer conversation, I think a book that is really valuable is The Mom Test by Rob Fitzpatrick, which is all around, how do you talk to customers in ways that you can actually validate your idea rather than get some fake approval that doesn't actually tell you whether people would buy your solution? There's some advice for anybody listening. Last question to you. A brief answer from you on that. How does the world look like in 10 years if Hyfe succeeds? How do you imagine it will look like? How do you want it to look like?

Iulian Circo  48:39

I don't have the vanity to think that Hyfe will change the world. I don't think so. But I have the conviction that we are ahead of the trend. We're in the best place that business can be and that is you're early before the wave is building up, and that's the best way to scale a business, because you have the momentum, you have the wind behind it, and I think that in 5-10 years, healthcare will have modernized. If you look at healthcare like you would look at the product, it has a terrible user experience, the worst user experience you could imagine. It's just high friction, low tech, really slow, expensive. It's everything we hate about products. That's healthcare on the interface. On the backend, it's really advanced. There are these super smart people, well educated, all the technology, but on the front end, it sucks. And eventually, it's going to be disrupted, and it's not us. I mean, we're playing a part in that, and we are out there in the battle, but it's going to be the product of others like us, and it's going to change, and it's going to change in a way that the patients will be more empowered and more in control and having just a better experience, and technology is a big part of that.

Maiko Schaffrath  49:59

Love it. I can't wait to see those changes happening. I mean, they're already happening right now, and healthcare is changing, but it's still a long road ahead. So, thank you, Iulian, for joining me today. Really insightful to have you on here, and thanks for making the time.

Iulian Circo  50:18

Thanks for having me, Maiko. I love this. Thank you.