“At ff Venture Capital, we see everything from a global perspective, and we focus on turning these nascent kernels of ideas into massive global companies.”
Oliver Mitchell, Partner, 2023
Whether you were born in the 80s or the 2000s— you’ve probably seen at least one or two films about robots. The wildly popular franchise, Transformers, dominated the early 2000s, generating just above $1 billion in box offices over a period of six years. Just a year after the first Transformers movie was released, robots on the screen appeared to have de-evolutionalized rapidly, at least physically. In Transformers, robots were emphasized for their grotesque and terrorizing nature. Whereas, incoming robots started getting smaller, more nimble, and less overtly violent. Wall-E from Pixar was a minute, clean-up robot completed with computer vision, and the ability to perceive emotion. The Netflix cyberpunk series, Love, Sex, and Robots (2020) opened season two with an eerily realistic depiction of robots blended seamlessly into our environment. The coffee that automatically turns on at a specific time, to the machine that cleans the house and delivers the mail— until of course, it goes through a massive and violent malfunction.
Robots remain a timeless muse for directors and entrepreneurs alike, while various industries (tech, manufacturing, agriculture, education) continue to invest in robots. The enduring fascination with robots, a unique creation between science and art, has the potential to unlock greater solutions for the human workforce. However, not without some recourse for ethical boundaries.
When Oliver Mitchell built Robot Galaxy, a retail entertainment company back in 2007, never did he imagine it would lead him to start writing about robots in-depth, and then later, invest in them. His story shows despite the popularity of fad investing or short-cycle sellouts in the market; the best investments are often rooted in consistent curiosity in a specific industry, getting into the trenches, and diversification. Learning, rerouting, and improving.
Oliver was generous enough to discuss some of the key pivots in his entrepreneurial and investing lifespan which has led him to several successful exits and then raising a unicorn in his portfolio. Oliver has been a partner at ffVenture Capital for the past four years and resides in New York City, where he also teaches an MBA course at the Sy Syms School of Business.
Interviewer: What are some of the key things you look for when you invest in companies?
Oliver: For a bit of background context, I’ve been a founder and an operator of startups, having sold to big multinationals like American Express and ADT Johnson Controls. So, I’ve been in the shoes of a founder during different economic cycles. I think it’s important that regardless of the industry, valuations have to be grounded and rooted within the financials of the business. For a startup, that’s tough because many of them are pre-revenue, but when going out to professional investors, they should be able to have some early validation, either from pilots or proof of concepts. In other words, they should be able to determine what people will pay for their product.
From there, they can figure out what the drivers of the revenue are. Is it through the number of sales reps and the number of accounts they can drive? Or is it through a channel partner? Or is it a license with a bigger OEM? And what does that look like?
It cannot, and I cannot stress this enough be: “I only want to give up 10, 15, 20 percent of the company, so my valuation should be X.” That’s not a good calculus for determining valuation.” But I think this is what the hyperbolic times gave birth to.
Interviewer: What’s unique about investing in automation?
Oliver: With automation, it gets a bit trickier. The reason why is that automation investors tend to belong to a smaller community. At ff Venture Capital, the fund I’m a part of, we’re seed-stage investors. We invest in both B2B SaaS companies and enterprise software within FinTech, InsurTech, LegalTech, and applied AI, as well as automation technologies, drones, robotics, IoT, machine learning, and remote sensing.
We see both sides of this. The perceived scalability within B2B is much greater than in automation technologies. People tend to have greater anxiety related to hardware startups. Therefore, in general, a hardware startup has to prove the margin of their business and if it’s less than 50% to 60%, then you ought to do better. There are ways to get that margin higher, whether through integrators or offering different products or services. In addition, automation technologies are so new and different that often they start with one-time purchases which take a very long sales cycle. They have to figure out how to get a client on a monthly recurring revenue stream. This could be producing productivity reports, analytics, predictive maintenance, and so forth.
You can go from a one-time purpose, to what we call RAAS (robot as a service) revenue. Now that’s easier said than done because if you look at where robots are deployed, whether in logistics, manufacturing, agriculture, or construction; equipment is being purchased currently on a lease basis or a one-time purchase basis. It requires a different mode of thinking and proving yourself in the marketplace. That’s why automation investors tend to have a deeper, more nuanced understanding of the industry, allowing them to take a more proactive approach with startups. At ffVC, one of the statistics that we’re most proud of is that half of our companies make it to series B. That’s five times better than the industry average. The reason for that is we’re additive investors; we get involved not just at the board level and lead rounds, but we’re very proactive. We have a platform team that helps out with the hiring, an accounting group that assists with bookkeeping, and a co-investment network with close to a thousand fellow VCs because we’ve been doing this for fifteen years. We’re an international firm with six funds in the US and soon to be three funds in Europe. We invest in Israel, Europe, and the US so we see everything from a global perspective and focus on turning these nascent ideas into massive global companies.
“At ffVC one of the statistics that we’re most proud of is that half of our companies make it to Series B. That’s five times better than the industry average.”
Interviewer: Can you talk about controls within venture investing?
Oliver: An investor’s job, a lot of it, is mitigating risk. You perform due diligence to ensure you’re working with the most accurate data. I think valuation is one of those critical levers that you can control pre-investment. The stage we come in at, and how much we choose to invest, that’s within our control. But what happens after we invest within the market and how customers react is less in our control.
Things that might influence the direction of how that goes, are introductions, guiding founders through the sales process. and helping them figure out pricing strategy. We can do all that, but one of the early levers is those investment terms and the valuations. I think what’s great about ffVC is we have a cross-section of disciplines. We have people who come from investment banking as well as people like myself who are founders. We have different points of view on how we look at companies.
Interviewer: Having been on the other side of the fence, how do you think you add value to your fund?
Oliver: As someone who’s been an entrepreneur for numerous years, I’m empathetic toward founders because I’ve been in their shoes. I’ve been in these tough situations, where I’ve hired hundreds of people, as well as had to let them go during different economic periods. My experience in selling companies and having exits is also relevant. Ultimately, I’m able to help bring some of that mindfulness to founders that are living through that. I find that investment bankers with no founder experience, have numerous strengths, providing a macro-perspective of investing.
Interviewer: When you’re looking through hundreds of decks a week, what is something that really stands out?
Oliver: Ultimately it all comes down to customers, customers, and customers. The other factor is the thoughtfulness of the deck. Sometimes these decks are not well thought through and so it becomes challenging to discern quickly what they do. The third critical factor is the founding teams; the experience of the members. In the early stage, you’re betting on the jockey, not the horse. The team is crucial.
“In the early stage, you’re betting on the jockey, not the horse. The team is crucial.”
I like people who get their hands dirty and are out there with the customers and have gotten some market validation and are clear on the next steps. They should be looking to us to help them with the commercialization strategy.
Interviewer: What’s your advice for entrepreneurs that have a good product, but are encountering lots of competition on the market?
Oliver: Well, it’s a catch-22 without any competition, it means that you’re too far ahead of the parade. If you’re too far ahead of the parade, you’re not in the parade. It depends, if you’re entering a market and there are competitors out there that are bigger, you run the risk of becoming commoditized on price very quickly. That’s very dangerous. What are the valuable products and services? What is your value proposition that’s not being offered there? Is it important enough for people to take a risk in implementing this technology? That goes back to getting out of the building, validating that value proposition, and understanding the market landscape.
Interviewer: How did you get into the robotics industry?
Oliver: It was fairly serendipitous that the last startup I found was called Robot Galaxy. That was a consumer robot business around STEM education, where kids could build their own robots in the physical and virtual world, from our comic book series, which was published by IDW.
In 2008, things got challenging and my marketing team suggested I go into blogging as it was really popular. We created a blog called Robot Rabbi (as I’m Jewish) and I started to write articles about the real robotics industry. Becoming an observer and a chronicler of robotics, I shifted roles there, and I started to go back into tech investing.
“ I started to write these articles, and I started to invest in these companies. I ended up building a portfolio. From there, I had eight exits, two IPOs, and one unicorn out of that portfolio. ”
I was the only writer in the trades that was writing about the business aspect of robots. Everyone else was writing about engineering, mechatronics, and the servos and the cablings. I wrote about things like the pricing structure of robotics. How does this replace existing workflow and processes? What does the market landscape look like for these things? My articles became very popular, not just my blog, which got syndicated on The Robot Report and Robohub— I became known as a robot investor. There are not so many of us out there. I started my company in 2006, and this was in 2011. Fast forward 12 years, and I’m now a partner at a venture capital firm investing in automation.
Interviewer: What type of fundraising strategy do you employ for robotics compared to other industries?
Oliver: The premise is that I believe that everything within the business workflow will be automated. When I was in the toy business, I would go into factories in Guangdong, China. On my first day going to a factory, I had the assumption it was going to look like a PBS show about the Crayola factory, where everything is being done by machines. I was in for a real surprise when I arrived in China and saw that everything was being done by hand. I think that’s what happens in economic cycles—that when human labor is cheap, you’re able to hire lots of them. We’re seeing this in Asia, when human labor goes up and it equals or exceeds the price of machines, then you upgrade your factories, your warehouses, and other aspects. I believe that everything within the industry is being automated. The area that I’m most excited about is manufacturing. Robots have been used in manufacturing for decades, since the sixties, but these were big robots that were scary. They were caged in, and they would work in these dark factories because there would only be one or two humans that would press the button, and they would do all the welding of all the cars in Detroit.
Now the scale of robots has gone down. With the sensor costs going down, the robot can perceive where it is next to a human being and it can work collaboratively with a human. Humans will play more of a managerial role in supervising the production line. Now robots are like tabletops and they’re being deployed in smaller factories. You’re going to need a lot of technology like computer vision sensors, sensor technology, and so forth.
Another area is shipping and logistics. If you think about the consumer shift from brick-and-mortar retail to e-commerce, well, that creates a huge backlog. If you want one-day delivery, there need to be more people that you can employ to pack boxes, label them, ship them, and drive them. That’s precisely why Amazon acquired Kiva. You’re seeing other retailers like Walmart, and other smaller retailers doing that with auto-stores and other vertical micro-distribution centers, and micro-fulfillment centers.
In agriculture, you run into the problem where there’s a diminishing population of people who want to do farming, even as the world population grows. Robots can do the majority of the manual labor: picking, collecting, towing, and managing. We have a company called Burro that turns a grape vineyard into an Amazon fulfillment center because its robots can manage a whole vineyard there.
Interviewer: When I talk to people from other generations, they have a fear-based mentality around automation. Why do you think that is?
Oliver: TV shows like Black Mirror created a lot of dystopian views on technology. Prior to that, there were plenty of dystopian novels and literature about this area. Yet, some people claim they’ll never use AI, and then once they get over it and they use it, they can’t live without it.
There are still many tasks that humans can do better with their dexterity than robots. We’re seeing that with ChatGPT and the integration with Bing— it’s not replacing the arts.
In education, there’s the debate of whether essays should be handwritten because of ChatGPT. The other view sees ChatGPT as an inevitable tool that’s going to be used by graduates when they enter the workforce. So you might as well embrace it and figure out how to incorporate it into the curriculum. Perhaps, it’s more audio-based assignments, video assignments, live pitches, multimedia…etc. As a professor teaching MBA courses here in New York City, I don’t do testing. Everything of mine is project work. The point is to tailor education for the 21st century—by embracing technology.
At the same time, we should not ignore people’s fears. Instead, we should aim to educate them, whether that’s engaging with policymakers or doing live demonstrations. There’s a great professor at Cornell Tech here in New York, Dr. Wendy Ju, who studies how people behave with robots. She sometimes uses robots and she’ll have the furniture move and observe people laughing and getting comfortable with the furniture. She’ll also see people getting frustrated with autonomous vehicles because of the legal breaking time. Which no one actually does in New York City. There are localized styles of driving that AI will have a difficult time adapting to. It’s understanding and iterating your technologies around those rough edges and where people are getting very uncomfortable
Conclusion
Robots have long existed in different forms, whether in fiction or reality. We often forget that it is automation hardware that ensures you get your Amazon Prime guarantee or puts together your vehicles in due time. While most of the hype currently is reserved for the possibility of salient artificial intelligence or AI that can effectively ‘deload’ menial work from intelligent workers; automation hardware can serve perhaps a larger piece of society. It allows the opportunity for more blue-collar workers to upskill while producing the same if not greater output. As humans learn to work concurrently with robots and upskill themselves, we will see rapid advancement in both human and artificial intelligence, leading to an evermore cycle of innovation.