Stefan Heck is the cofounder and CEO of Nauto which is an AI technology company on a mission to make driving safer and smarter. Today, the company has raised over $174 million with partners and investors including General Motors, Toyota AI Ventures, BMW iVentures, SoftBank Vision Fund, Greylock Partners, and DNX Ventures at a valuation rumored to be over $1 billion.

In this episode you will learn:

 

  • Taking the leap of faith and the right time to risk it all
  • Finding top tier investors
  • How to seek guidance from mentors before taking big decisions
  • Artificial intelligence working at its best
  • How to scale hyper-growth companies


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About Stefan Heck:

Dr. Stefan Heck is CEO and Founder of Nauto, the Palo Alto-based an AI-technology company on a mission to make driving safer and smarter. Nauto’s intelligent driver safety system assesses how drivers interact with the vehicle and the road ahead to reduce distracted driving and prevent collisions.

Prior to Nauto, Dr. Heck was Consulting Professor at the Precourt Institute for Energy at Stanford University, directed the Energy Transformation Collaborative and was a research fellow at the Steyer Taylor Center at the Stanford business and law school.

Previously he was a Senior Partner at McKinsey and co-founded and led the Cleantech and Sustainability practice there, working extensively with Global 100 technology, industrial, infrastructure, building systems, retail, utility and energy companies across the US, China, Korea, Japan, India, and Europe.

He is on the Board of the Silicon Valley Leadership Group, is an angel investor in disruptive technology companies and is the author of a critically-claimed book, Resource Revolution: How to Capture the Biggest Business Opportunity in a Century.   He was recently named to the inaugural Recode100 list.

Stefan earned a Ph.D. in Cognitive Science from UCSD and a B.S. with honors in Symbolic Systems from Stanford University. As an undergrad, he launched Stanford’s first Solar Car project, which continues in the present day.

Connect with Stefan Heck:

 

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FULL TRANSCRIPTION OF THE INTERVIEW:

Alejandro: Alrighty. Hello everyone and welcome to the DealMakers show. I’m excited about the guest that we have today. Someone from Europe, just like myself, so it’s always great to be with people that are from that part of the world. So, without further ado, Stefan Heck, welcome to the show today.

Stefan Heck: Thank you very much. It’s great to be on the show.

Alejandro: How was life growing up in Austria?

Stefan Heck: It was wonderful. I’m from a small town up in the mountains, skiing every year. I learned to ski at age two and a half, basically shortly after walking. It’s very bucolic. It’s grown a lot since then. It’s been a long time of course, but it’s still a very lovely landscape. I love going back.

Alejandro: What brought you to the U.S., Stefan?

Stefan Heck: I came to the U.S. twice actually. Once, as a teenager. My day worked for the United Nations for a couple of years, so we lived in New York where you are now. Then the second, I went back to Austria for high school. Then the second time I came for college to Stanford, and then stayed on for graduate school and settled here in California.

Alejandro: So, I’ve got to ask you. What is Symbolic Systems which is what you studied at Stanford?

Stefan Heck: Yes. It’s basically artificial intelligence. At that time, AI was not as popular a term, but it’s linguistics, computer science, AI, psychology, and I did some neuroscience as well studying human thought processes.

Alejandro: We’re talking about the early ’90s, so definitely AI was not even in the picture for many people.

Stefan Heck: We’re talking about the late ’80s actually.

Alejandro: Wow.

Stefan Heck: That dates myself. So, yes.

Alejandro: Wow. That’s amazing. Then after that, you did you Ph.D. as well in cognitive science.

Stefan Heck: Yes. At that time, it was called parallel distributive processing, now much better known as deep learning. So, I did neural networks on a NeXT machine which was the hot computing platform of the day long ago and doing my own code running Computer Vision networks. It was great fun. I learned a lot. And philosophy, so looking at the ethics of AI and looking at how concepts arise which has all come in handy now 30 years later.

Alejandro: I can’t imagine. Putting AI and deep learning on philosophy. Man! You must be a force to be reckoned with.

Stefan Heck: It’s an unusual background, but it’s good preparation for being an entrepreneur delivering AI for safety today.

Alejandro: Absolutely. One thing that stood out for me was that you have a really diverse background. Your first job was as a researcher, but then you did a little bit of Apple, McKinsey. So, I want to ask you here, McKinsey because there are many people that I interview, many, many successful founders and also founders that are good friends. They go to Bain or McKinsey. What do you guys learn there that is just so handy to build and scale a business?

Stefan Heck: It’s all about business. I joined, and as you described, I ran my own startup doing web design and online presence in the very early days of the internet. This is now mid-’90s. For me, it was a way to pay my way through graduate school, but I realized very quickly, I did not know enough about business to really run a successful business at scale. My company at that time was very small. So, since I didn’t have an MBA, I did a technical Ph.D., I saw McKinsey as a chance to learn about business. Like many people, I joined thinking I would be there for three or four years. Pay back my student loans, learn a lot about business and then go off into my own thing. I fell in love with the place because it’s such a stimulating environment. You do different projects every few months. You’re watching companies grow. You’re helping to dig into their problems, and you’re doing all that in an environment where you’re being mentored and coached and getting feedback all the time. You’re learning from some of the best clients in the world, and also amazing McKinsey partners. So, for me, it was a great way to get all the business background. I arrived right at the beginning when the internet became a key element of business strategy. I joined McKinsey in ’96 right at the beginning, and that was pretty much the beginning of the internet bubble. So, I did nothing but internet for the next four years which was great fun to see it rise, and then ultimately the decline.

Alejandro: Really interesting because there are a lot of people talking about potential corrections. I’m just thinking like based on what you’ve learned and maybe some data and things like that, what have you learned about this type of, I would say, market cycles, and for example, how would you suggest or recommend entrepreneurs that are listening to go about them?

Stefan Heck: It’s a great question. Yeah, I’ve been through two of these market cycles. I graduated in the middle of the recession in ’91, ’92. That’s when I chose to go to graduate school. Then, of course, the internet bubble burst. Then if you count 2007, that’s actually the third recession, although that’s not specifically tech-focused. I think the biggest lessons are really think about your business model and think about what drives your growth, and how dependent are you on CapEx spending or one particular customer or something being off topic. If the answer to any of those is that you’re very concentrated on a few customers, one customer, that you’re very dependent on some trend that is going to end, that’s all risk factors. I like to think of it as we want to have a model with scale. We got to profitability very clearly. It’s not a bet on the future that something’s going to happen to make us profitable. It’s part of our strategy. Definitely raising more money before the downturn. It’s almost impossible in venture capital to raise money in the middle of a downturn. Everybody shifts to focusing companies they already have, not investing in new companies. Then thinking about how do you diversify your risk? For us, we’re an AI company. We decided to go across geographies: Japan, Europe, and the U.S. early because that diversifies our risk. We have very different business cycles. We also decided to go after after-market and retrofit our AI capability to commercial fleets rather than wait for autonomous cars because there are a billion vehicles in the world today. About 15% of those are commercial. That’s a huge market we can go after today and make money on. We sell a service there. It’s a SaaS service. So, it allows us to be robust no matter how long a transition to autonomous takes. When I started NAUTO four years ago, you could get estimates of anywhere from “It’s here in two years,” to “It’s never going to happen.” Most estimates at that point were 15, 20 years out. Then everybody got excited two years ago and thought it was going to happen really soon. Now, the pendulum swung back a little bit, and people have realized that getting really good autonomous driving is actually really hard, though everybody’s pretty much clear it’s going to take several more years at least now, and we’re not really that close. For us, that doesn’t matter, and that’s really my advice to entrepreneurs. Build a business where you’ve got a gradual step-by-step plan that allows you to grow, and you’re not betting on something that’s not under your control coming into play. Then you find customers. We started in the taxi spaces very early adopters, family-owned businesses. Then we progressed to logistics and services and goods delivery. That diversification is also very good for us because now if you’re a taxi company, business is not looking so great. You’re under threat from ride-sharing, from many other dynamics, scooters even. But at the same time for us, my logistics is booming because everybody is ordering everything on Amazon, and it’s all being delivered overnight or same day or next day. So, that space is growing like crazy.

Alejandro: Got it. We’re going to get into NAUTO more in just a little bit. So, let’s not like go right into it, Stefan. Let’s continue here on your background because I think it’s really amazing. I want to really understand why did you decide to become a professor and leave McKinsey behind?

Stefan Heck: Great question. I was working with a lot of very large companies internationally. It has been amazing the previous decade building up new businesses for them mostly around disruptive technologies, clean technologies, solar, LED, but I could see that there was another level of change coming. At the time, I was looking at three spaces: energy, transportation, and education. The life of a McKinsey partner is pretty crazy. You’re on the road all the time, and you’ve got multiple projects. It’s pretty hectic, so you don’t get a lot of thinking time. For me, going back to Stanford as a consulting professor was great because it allowed me to give back and share with the next generation of students. It allowed me time to really think and explore what I wanted to do next. I knew I wanted to do something new and innovative helping these new disruptions and new technologies come to life, but I didn’t have a business plan yet. It was during those years at Stanford that I got a chance to, first of all, debate with a lot of fantastic students, but also do my own research on the economics of these disruptions. Ultimately decided transportation was the biggest and the fastest disruption. So, that’s where NAUTO came from is those two years at Stanford thinking very hard about what’s going to happen in this space. At that time, it was a radical idea that autonomous sharing, electrification, and connected vehicles would all coalesce into this amazing mish-mash of ride-sharing, but autonomously-driven electrified service, and plugging into both micro mobility at one end and public transit at the other end. I did a bunch of modeling back seven, eight years ago and gave a talk called [Asis 10:07] to describe where that was going. Then settled on data and being able to understand these dynamics in real time through AI as the right entry point and using safety as the initial value proposition to say, “We can keep you safe. We can get you back home every day.” That was the benefit of being at Stanford. You have time to really, deeply explore without the day-to-day pressure of a McKinsey job.

Alejandro: So, talking about exploring and about starting to really think about the idea and creating that canvas and what colors the canvas is going to have because ultimately as I think entrepreneurs are like artists. They’re like painting this canvas that started from nothing.

Stefan Heck: Yes.

Alejandro: So, how did that canvas from nothing develop into something for you and really led to incubating this idea?

Stefan Heck: I like your metaphor. It’s a big part of being an entrepreneur. Every once in a while, you’ve got to take the eraser or paint over a part that you already did.

Alejandro: Yeah. In many instances, it looks like a spaghetti mix, but hey, you know, it’s all in making it work.

Stefan Heck: That’s right. Like, “Ops. I really needed a different color here.” Yeah. It all started with that thinking time at Stanford. I was using public data sets at that point from California from the Federal Government and began to realize that first of all, the public data sets are always lagging behind because they’re driven by the census, and real-time data is locked up in a handful of big companies that have either control of the phone or control over maps. How could you get large amounts of data? I looked at almost everything. Inground, satellites, drones, all of which somebody has tried since then, of course, but became convinced that the vehicles themselves are the best platform for collecting data in real time, and that the way to get permission to do that is to provide an immediate benefit. That was really the genesis of our focus on driving safety and on saving lives and reducing collision costs. That became our mission from the very, very beginning. The initial canvas was we took an old dining table and set it up in our garage and begged my family for permission to take over the garage. That’s where our company started. First, three or four people all hired into the garage which is ironically about two blocks from the much more famous HP Garage. HP started in the 1920s. That’s where we built out for prototypes. We started driving around with them. We started looking at what are the different use cases, and we discovered some great data sets both in the insurance industry and from Virginia Tech Transportation Institute which showed where the sources of collisions and the sources of loss come from. Then we used those insights to begin to prioritize our road map and develop our first application scenarios; becomes pretty clear, and this has really become a huge part of our mission that the most common kind of accident is rear-ending a slower stopped car in front of you. Of course, famously that’s where started with four-car collision warning 15 years ago. The #1 root cause of those collisions has nothing to do with the car in front of you. It has to do with the driver being distracted. So, we began by focusing not just outward looking at the risks, but inward looking at the human driver and saying, “Could we warm them? Could we help make them better? Coach them? Give them an alert when they were distracted at the appropriate time.” That has worked wonders. We’re seeing huge productions way beyond our initial goals and expectations. Over 50% of the losses were removed today. Before any other autonomy, our devices don’t take control of the vehicles. They’re simply there to help assist and augment the human driver.

Alejandro: Let me ask you this, Stefan. Who are those three or four that you convinced to work in your garage?

Stefan Heck: Great question. One was a good friend of mine and a buddy from McKinsey who worked in a lab building his own equipment for many years and had done some other startups on his own, totally unrelated spaces. The second actually was my college roommate from when I was an undergraduate at Stanford. He’s a designer and worked at many fantastic companies over the years. I convinced him to jump in. Then we hired a guy who is still actually with NAUTO to this day who came out of the federal physics labs and had an incredible diversity of programming, building electronics software development. So, that was the initial crew. We grew very rapidly from there. We hired a woman who was an expert in insurance. None of us knew much about insurance, but obviously, if you’re going to reduce collisions and losses in the commercial fleet world, insurance is an incredibly important partner in that as well as in our first product managers and additional firmware and software engineers. I remember those days fondly, although I will tell you, it was scary. We did not know what we didn’t know at that point, and I’m glad we didn’t because maybe we would have been scared off.

Alejandro: I hear you. That’s typically the case in most instances. You guys are really working in this environment, really innovative stuff. There’s a lot of hype right now around AI technology. So, let me ask you this question, Stefan. What does AI at its best look like?

Stefan Heck: I think AI really is about implementing a part of what we can do as humans. Most of exciting applications are around perception tasks. So, recognizing things, classifying scenery. In our case, it’s about recognizing dangerous situations either because outside you’re about to hit something, or inside you’re not paying attention when you’re about to get into a dangerous situation. We also detect things like drowsiness in the meantime so you fall asleep. AI’s a great tool. I believe that there are at least as many if not more applications of AI complementing, helping, assisting, augmenting humans. We’re a perfect example of that. We don’t displace driving at all. We simply make driving safer and easier for the expert human drivers, but if you think about autonomous vehicles, that’s the other application of AI which you’re taking a task entirely out of human hands to basically create more free time and more luxury and convenience. In that case, you’re taking over all of driving if you’re building an autonomous vehicle. The exciting part for us is we don’t need to wait for full autonomy to get a lot of the benefits. We can cut your insurance costs. We can cut your number of accidents by more than half with the same vehicle you already have today and already own today. We simply retrofit a small amount of sensors and compute with AI embedded in it. That’s what allows us to function. The other great thing about AI is all of us as human drivers basically have to spend statistically about six years learning to drive. You can see for a teenager, depending on the country, 16, 18, when they start driving. Statistically, it takes about 2.8 collisions in six years to learn how to drive properly. That’s when you go back to normal adult risk. But for AI, we do that training on the collective experience of all the vehicles. So, we may learn something in New York that we may apply in California, or we may learn something in the winter in Michigan that we can apply in the Sierras here in California. That collective data set allows us to learn much faster, and of course ultimately, more from all the best drivers, not just from one or two in building that into the AI capabilities. So, I’m a huge believer in humans informing how AI should run and what good looks like. Humans are the role models. Our best human drivers basically never cause a collision. We want the AI to learn how to operate like that. But conversely, AI can also make the humans better. So, if you take your average driver, they’re distracted once every 11 miles. A significant portion of those 11 distractions every 11 miles turn into very high-risk near-miss situations. Then a small portion of those turn into an outright collision. So, we want to avoid and reduce those incidents and help those drivers get to be as good as the best ones.

Alejandro: Really cool. So, I guess in terms of monetization, because I’ve seen that you scored a really big partnerships with companies like BMW or GM. How do you guys monetize?

Stefan Heck: Most of our business today is working directly with commercial fleets. So, big package delivery fleets, people in the passenger transport space, taxis, ride-sharing. There, it’s basically a monthly safety service that you subscribe to. We put one of our devices in your vehicle, and then you pay. The payback is very, very quick because basically, we reduce so many of your losses and incidents and collisions that the device pays for itself in a matter of months. We also have a number of insurance partners, some of which are public, Allianz, Sompo, that are basically incenting fleets to put our device in so they get a reduction on their insurance premium. That essentially makes our device free for the fleet initially, and then allows them both to gain in the savings. That’s our core business today. Where this is headed though is to use all of the experience from all those professional commercial drivers, and as I mentioned, train the AI app to learn from all of them? Then use that AI in the safety systems that are being built into production cars. You mentioned some of our OEM partners: GM, Toyota, BMW. We’re working closely with them on enhanced collision warning systems and on enhanced driver assistance systems. Both Level 2, Level 3 vehicles, we’re making those vehicles smarter and more aware of their surroundings and of the driver state. A famous problem in autonomous driving is the autonomous car can handle the easy highway cases, but can get stuck with a situation and doesn’t know what to do. The standard approach now is to turn control back over to the driver. But, of course, to do that safely, you need to know, what was the driver doing right now, if they’re asleep, or if they’re reading a book, it takes them some time to get back engaged in the driving task. So, those are the areas, that’s a little longer time scale, working very closely with our auto and truck maker partners to build the technology directly in so that you don’t have to buy a device anymore at all. It just comes as part of your vehicle.

Alejandro: Really cool. With all the lives that are being lost on the road, I’m sure that this is going to make a huge difference. One of the things that I saw here, Stefan, is that you started the business in 2015. It was really interesting to see that right away, literally on September, you guys raised your Seed Round. It was just like immediate almost. I would assume that for an operation like this is quite capital intensive because of developing the technology and scaling up and all of that stuff. So, how much capital have you guys raised today?

Stefan Heck: All in, we’ve raised over 174 million dollars. That’s across all of the rounds. You mentioned the Seed Round. We had a number of angel investors. I put in some of my own personal money at the very beginning, funding our first purchases of equipment. We then had our Series A which was led by Playground, Andy Rubin’s fund, along with Draper Nexus and Index, and number of the automotive that are partners. Then we raised our Series B led by Greylock and SoftBank two years ago now. That was our latest round.

Alejandro: The investors that you guys have, Stefan, is very impressive. Just for the listeners so that they know, I see Index, Greylock, SoftBank, like you were saying, Playground. So, I guess even General Motors has investors or BMW Ventures. How did you meet these guys?

Stefan Heck: It’s a mixture. A lot of them I knew from my McKinsey life in terms of the bigger companies. A lot of it was also reaching out, getting to know people. We from the very beginning took a view that this is an open ecosystem and that we need to work with partners. There are a lot of startups in the last couple of years that have started with a vision of being all in vertically integrated. We’re going to build the car, design the systems, operate the vehicles, build the AI, build the sensors ourselves. I think if your company is called Google, you can do that, but if you’re a startup, I don’t think you can bite off all that by yourself. So, we took the opposite approach. From the beginning, we said our core expertise really is the AI capability and the learning and the understanding of driving behavior and driving risk, but we want to work with other people who are much better than we are at building the cars. We want to work with insurers who are much better at understanding risk, and pricing risk, and providing a great insurance product. That was a message that really appealed. People were excited about the safety potential, the immediate tangible loss-reduction, going in when 1.2 million people are killed every year, sadly on the roads saying, “I can save half of those today. You just need to deploy very simple technology and affordable technology.” That got their attention, and then we took a very partnership approach. We’re doing the development together. We’re open to licensing our capabilities to third parties because we know we’re not the best way to go to market only through a small company. We want this technology available to everyone and be embedded in as many vehicles as possible. That’s our mission. We’re all about the safety and making driving safer and smarter.

Alejandro: One thing that I see and from all the entrepreneurs that I either interview or that I know is that a business like this, it’s at the beginning. Now, you’re obviously in this rocket ship, but at the beginning, it’s quite risky because there’s a lot of investment that needs to happen up front in order to really start to see profit and start to understand that things are going into the right direction and that you’re going to survive. So, for you, at what point did you say “We’re going to make it?”

Stefan Heck: You know, we had some near-death moments early on.

Alejandro: Could you share one of those moments with us?

Stefan Heck: Well, I’ll share one which is between the Seed Round and our Series A that you mentioned earlier. We had some initial seed investment that allowed us to get prototypes out. We had shipped phones all over the world to run prototype software to begin to understand driving in the desert, and crowded Asian cities, and the rural countryside, and it was great. It was great input for our algorithms and development. But you have to remember, and it’s kind of hard to picture this nowadays. This was an area before autonomous vehicles was a household word. So, when we started out raising our Series A, I talked to over 60 different investors including some very good friends who all turned me down for one reason or another. Some didn’t like automotive. No one has ever made money on automotive. Why would I invest in that? Some didn’t like the fact that we had hardware. Silicon Valley has very much focused on software only plays. SaaS, Cloud, is all very hot. But anybody that had any hardware dimension, even the hardware’s not the core of our product. We do require a retrofit for a vehicle to get the sensors that we need as input. The moment we said, “There’s a device,” they said, “No thank you.” So, I wound up self-funding the company for a period of time. All the executives took no compensation for a period of time. We were really running on the edge.

Alejandro: How many people were at that point of the business?

Stefan Heck: A little bit shy of 20 probably, 16, 17. Something like that. It was a good size startup for early stage. It was in that environment that we ran into Playground, and they are focused on AI, deep learning. They’re all ex-hardware makers from amazing companies, Android, Apple. So, they were not scared about hardware. They were not scared about AI, and a couple of them had worked in automotive companies before as well, so they were not scared about automotive. The irony is, they had internally had a discussion, “Oh, we should give a free dash camera to people to learn what driving looks like.” We showed up with a model that basically says, “We have a great dash camera with AI embedded in it, so it actually adds value to the driver and can help protect them, and therefore people are willing to pay for the service. You don’t have to give them away for free. So, they fell in love, and the rest is history. That was about a year into NAUTO’s life. We nearly died at that stage. The irony is a few weeks after we closed our Series A two things happened that changed the entire landscape. One is Tesla announced over the update of their autopilot software. As much as it’s maligned for overstating what it can do, I have a Tesla, and I’ve tried it many, many times. It’s a great initial achievement to say I can actually drive on a highway without having to steer and take control the whole time. That got people’s attention because that meant some version of autonomy even though it was relatively a basic one was now live in the field, then if you recall in that time, around the same time, I think a difference of about one week, GM bought Cruise for a billion dollars, and all those VCs that had said, “I’m not interested in automotive,” suddenly changed and said, “But I am interested in autonomy.” Many of them came back and said, “Weren’t you doing something in autonomous.” I said, “Yes, we did.”

Alejandro: Unbelievable, and just out of curiosity, as you were speaking, when do you think we’re going to be able to see completely fully autonomous cars?

Stefan Heck: You know, it comes in phases. There are fully autonomous vehicles on the road today. Waymo is running some in Arizona. You’ve got Uber giving rides in Pittsburg. You have May Mobility in the Michigan area, Voyage. The thing all these have in common is they’re limited to certain conditions. It’s low speeds, generally 35 mph or less. It’s within a geofenced area, so you can only take certain trips. You can’t say, “Take me across the country.” Most of them are pretty limited neighborhoods. It’s in an area that they’ve highly mapped and studied and test-driven in. And it’s limited also by the conditions. They’re not on crazy traffic jams. They’re not in the middle of a snowstorm. So, at that sense of autonomy, the first baby step examples, they’re alive today. I think we’ll see that continue to spread gradually, geographically. Cruise is very ambitious in wanting to drive in San Francisco, and they haven’t enabled commercial service yet, but we definitely see their test vehicles on the road today. That’s a more challenging environment, big city environment, lots of pedestrians, lots of bikers. No one has dared to go to New York yet, but Manhattan would be kind of the next-step challenge. Then maybe one day Bangalore or other cities in India or Africa that are even more complex, more stuff going on, on the road. The other dimension is what’s happening on highways. So, we’ll see more luxury cars have evolutions of the Tesla autopilot so that you can do highway driving more or less on straightaways following the lanes automatically. There are a number of European carmakers that have launched that capability now. Then the other dimension, there are trucks. That’s a huge market because similar to what we do at NAUTO, augmenting human drivers, as a truck driver, staying awake for 8, 10 hours a day driving lots and lots of miles is challenging, and your pay is limited by how many hours you can drive, which the Federal Government restricts for safety reason, so you don’t fall asleep and get too exhausted. But if you could, like an airplane captain put the truck on autopilot for the many, many miles of backcountry interstate and drive the first miles and the last miles, and handle the loads, the inspections, making sure the truck’s safe. Now, suddenly you can actually make more money per day. So, I see that as a big application for freight. We’re in a lot of truck and last mile delivery vehicles today. Again, we don’t drive. We’re only warning the drivers, but we have a lot of interest from truck makers and truck component makers to build our algorithms into their systems directly and head in that direction.

Alejandro: Stefan, how big is the operation of NAUTO today?

Stefan Heck: Today, we’re in three continents. Japan, North America, and Europe. We have a couple hundred people, and the vast majority of those are AI and computer vision, and data scientists working on the algorithms. We do design our own hardware very much like Apple. It’s designed by us and then manufactured in China. And we have a large sales and customer support team in all three of the regions that we operate in that helps customers adopt the technology, but then, more importantly, use it to improve safety. And we see very impressive results. I have to tell this story. When I started NAUTO back in the garage, we set a goal when we first said, “We’re going to focus on safety as our first application.” We set a goal and in the first 18 months of deployment reducing damage and losses and collisions and therefore ultimately fatalities by 20%. So, 18 months, 20%. We hit 35% reduction in month 12 of deployment. A short while later with our real-time alert capability, we were warning the driver as they get into a dangerous situation or as they’re getting distracted. We crossed 50%, and really, we haven’t found the limit yet. Obviously, there’s some limit. The last 5%, 10% will require full autonomy where the human-error element is taken out of the system. But we now think we can get to 70%, maybe even 80% reduction. Still having a human driver, but helping assisting them. That’s very exciting. If you had told me two years ago, “I’m going to give you 80% of the benefit of autonomy for $500,” people would have laughed. But now, we have the data to prove it.

Alejandro: Really cool. For you, Stefan, this is your first really meaningful rodeo as an entrepreneur, and correct me if I’m wrong. Would you say that’s accurate?

Stefan Heck: It’s my second rodeo, but the first one was a little tiny pony. This is a real horse.

Alejandro: So, when we’re thinking about a real horse, and being the jockey of this, the learning curve is pretty steep. We have probably a lot of people that are listening right now, and they’re probably taking the reigns for the first time in their life in their professional career. So, based on the lessons and that steep learning curve, what would you suggest to the people that are listening that it’s their first time around? What is the absolute must that they need to keep in mind as they’re building their business?

Stefan Heck: I have a lot of lessons, hard earned. The first is you’ve got to really focus on what is your initial product? What does it do? How does it become compelling? The proverbial MVP. In our case, that really aligned very closely with our mission of saving lives and improving safety. That really inspires people. The second is, and I can’t over-emphasize this. Be very careful in how you choose your team in both the skills they bring, the experience, but also how much time you spend together aligning on what you’re about. We have had some amazing experiences with people that made NAUTO much better than it could have been without them and have taken us beyond the original inspiration and vision through their talent, through their capabilities, but we’ve also made some mistakes. My lesson in hindsight is if you have any doubt, in that interview debrief one of you is saying, “This could be an as*****.” Stay away and make the decision “No. It’s not worth it.” We’ve had only a few of those. We’ve been very lucky, but each one there was an early warning sign where we weren’t sure, and now we have a cardinal rule: if you’re not sure, just pass. I think the third area is very early on, build yourself a network of partners, of supporters, of advisors. We invested in having an amazing board early on, insisted in our Series A that we have an independent board member, Karen Francis who’s a longtime GM and Ford executive, ran her own startup company consequently. She has brought a wealth of knowledge. We’re lucky to have an amazing woman on our board, our VCs, of course, as is so common in the industry still are mostly men. So, that perspective of thinking through marketing, thinking through how the drivers and the customers will experience the product, it’s been a great addition, plus her amazing network in the auto industry.

Alejandro: Why an independent board member? For the people that are listening mainly, why would you bring or why would a company bring an independent board member? You were kind of alluding to it and the details and everything that she’s able to bring to the table in marketing and other areas. But what would you say that also makes an independent board member effective?

Stefan Heck: It’s the background, and skill sets, and perspective they bring to the table. It’s really that simple. Their VCs have typically grown up in tech. Some of them have been operators, but not all of them. Occasionally, they have experience in an industry outside, but for us, that depth of emersion in the automotive industry. You know, when I go to Detroit with Karen, it’s like a reunion. We meet people on the street. They’re like, “Oh, we worked together ten years ago.” So, that network, I don’t think there’s any VC that could bring that level of networking capability. Then, there’s just a degree of focusing on other functions. In Karen’s case, a lot of that has been marketing skills. Her early background is from Procter & Gamble. She ran a multi-billion-dollar marketing and advertising budget when she was at GM. So, that kind of knowledge and background of how you think about the consumer is very different from the way the tech industry thinks about customers who are usually in IT or engineers. So, bringing that capability in a business-to-business content because we’re serving fleets. We’re not serving consumers. But still bringing that understanding of a different industry. Then, I’m just a huge believer. I focus on this in our executive team as well that diversity makes the company stronger. You need to have that alignment around the vision and all of your passion about the same mission and the same goal. But within that broader mission, you want to have as much diversity as possible, so you don’t have blind spots. If you hire people that are all like yourself, you will miss really warning signs, you will miss subtle cues, and you’ll make bad decisions.

Alejandro: Got it. Really cool. You were alluding to some of the tips and recommendations that you would give to first-time entrepreneurs, but there’s one question that I always ask guests that I have on the show, and that is knowing what you know now; I mean, it’s been an unbelievable journey for you and for NAUTO. Really highs and lows, as well as you were pointing to, but definitely, this is heading in the right direction, and a rocket ship. But now, looking back, if you had the chance to really have a conversation with your younger self, with the younger Stefan before launching the business, if you had one piece of advice that you would give yourself, what would that be and why?

Stefan Heck: It’s a great question and one that I’ve thought a lot about. What would I change? What would I do differently? I think the main one was my second point that I already mentioned which is be even more careful in picking your first dozen, first 20 hires because that establishes the culture. You’re setting norms for how you make decisions, for what good looks like, for how you deal with difficult tradeoffs. We have challenging tradeoffs all the time. People who want to deploy our technology into a country where it will be used for purposes that we don’t endorse. It’s very easy to misuse a dash camera as a spy camera. Our system is designed to shore privacy because of the artificial intelligence and really only intervene when there’s a safety situation. But other people out there want to use cameras for other purposes. I’ll leave it at that. So, how do you as a team make those decisions? I’ve made that very explicit in our recruiting. I made that very explicit in our fundraising. Every single board member knows if there is a dubious question or dubious customer, we will turn business away and except that we grow a little bit more slowly. Right now, we’ve got so much demand that we can’t even handle it all, so that’s not slowing us down at all, but in our past, certainly, we have faced decisions where we have chosen not to do things because we wanted to do it right, and we wanted to make sure AI, in particular, early uses of AI are done with great ethics and great concern for equality and for privacy. So, that’s my biggest advice. The other is you will never have enough hours in the day, enough energy to do everything. This comes from my good friend and mentor, Reid Hoffman. As a startup CEO, you’re always picking which fires to address and which ones to let burn, and nothing will be perfect around you. We’ve matured a long way, so we’ve put out a lot of fires in the meantime, but our first couple of years, we knew there were a lot of things we had not yet gotten to fix. That’s changed a lot in recent years as our team has grown. Now, we can actually put people on figuring out how to make the insulation processes easier or figuring out how to make the graphic interface easier to understand. That’s one of the things you earn over time as you grow, get more capital, your team grows, you can begin to polish and refine aspects of the product.

Alejandro: One follow-up question there, Stefan. Really interesting what you were sharing about making decisions and look, if you have to grow a little bit slower, you do that. In that aspect, especially for the folks that right now perhaps are dealing with very important decisions that may impact the course and the nature of their business in the future, what is typically your process before you actually make the decision? What does that process look like?

Stefan Heck: I get advice. I’m very open with our executive team. We debate all of our major decisions, and I want to get that diversity of viewpoints. For us, we also have very much a working board. Our board meetings are not dog-and-pony show report outs. We bring and tee up our toughest decisions and our big debates, and we give our point of view, but we also get input from the board. I open every single board meeting. This is something I would recommend to every entrepreneur once you have any kind of advisor group initially and then board a little bit later usually. I open every board meeting with what’s working, what’s not yet. That level of candor establishes a tone that builds trust, gets everybody on the same side of the table working through these issues. We have gained tremendous strengths from our board because these board members, not only do they have experience and input, but they have networks. They have a network of people that they can refer in for hiring, for expertise. They can make introductions. That has substantially accelerated our growth. Unless we’re clear what’s going well and where we’re struggling and where we still have gaps, “We need instruction to this particular fleet,” or “We’re looking for somebody with this expertise.” Then you actually allow the board to help you. I think many early CEOs make the mistake that they think their board is like a boss that they make sure they’re going to look good in front of. My advice is share with your board all of the good stuff, but also the things that you’re wrestling with because they’re here to help you. They’re here to help you make their investments successful, to help you grow. I always ask for feedback at the end of each board meeting, and I love the feedback I get: the good, the bad, and the tough. It helps me see where there are still areas where I can improve, where my team can improve, and then it allows us to act on that before it becomes an issue in the field with a customer or something we missed.

Alejandro: That’s great. That’s fantastic. Well, thank you for sharing that. Stefan, for the folks that are listening, what is the best way for them to reach out and say hi?

Stefan Heck: Basically email. stefan@nauto.com. For Twitter, @Stefan_heck and for LinkedIn, go to LinkedIn and type in /stefanheck.

Alejandro: Amazing. Stefan, thank you so much for being on the DealMakers show today.

Stefan Heck: Great. Thanks for having me, and I hope for all of you that are listening that you’re enjoying being an entrepreneur and that you’ll all be successful.

 

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