Teams, Trends and Focus: Q&A with Bill Malloy — Sway Ventures
What are the top five qualities you look for when deciding which companies to invest in as a venture capitalist.
- Team: we like to see a diverse team of high-performers that have had success before
- Culture: passion that emanates throughout the company, a higher calling, desire to win, constantly inquisitive, and humble.
- Market/Category: is this a new category or taking an existing category in a different direction?
- Product/Tech: is the underlying tech an elegant solution to a difficult problem and can it be protected
- Timing/Stage: is the company at the right stage in their lifecycle for us? Will team, product, and market all align over the next decade?
Where are some indications a tech company holds potential as a transformative innovator, or one that could lead to the next enterprise or consumer category?
It comes back to teams and culture. High-performing teams with a desire to be category leaders is palpable, you can feel it just walking into the office and in the first 30 seconds. Of course you still need to have the ability to build the product and the market, but if we’re talking about truly transformative innovators, there’s almost an electricity to them.
Describe your focus on unique data sets among early-stage artificial intelligence companies and how this might differ from other VC firms. How do you identify engineering talent that is building truly unique AI?
We look for companies that can develop and own a proprietary stream of data at massive scale. Many times the value of the data isn’t obvious or even known at the time, but the understanding that there’s tremendous value, not just monetarily, is clear. Other times the value is patently obvious. But ownership of a unique data set is key.
When it comes to engineering teams and AI, a lot of the best talent is still in universities right now. We’re in such early days of AI and the experts in the field are largely still in academia. You have to trust the programs and institutions that are producing students out of these programs and identify those who even their peers identify as gifted. AI Engineering talent is almost logarithmic, the gap between good and great is so wide, that an all-star can supplant an entire mediocre team.
We spend a lot of time in academia, identifying the best talent. We have partnerships with Stanford, University of Washing, USC, Clemson, and other universities. As a VC you also need to surround yourself with people much smarter than you. Our partners come from such diverse backgrounds and fields and they help inform every decision.
How would you ultimately like to see early to mid-stage tech companies change how we interact with technology.
For us, we like companies attacking massively inefficient markets. Global shipping, logistics and the supply chain, cybersecurity, transforming the enterprise, healthcare…these are ares ripe with problems. We think the best companies are ones where the tech is so elegant, that it fades into the background, and you don’t even notice it.
Promising Portfolio Companies:
Tally is a great example of a company attacking an inefficient market, consumer credit. A huge problem, I write about it here, their approach is so elegant that the user rarely needs to engage with it. Add to that their vision for a nearly automated personal finance world, aligns with our thinking.
Le Tote is another company that has been on a tear of late. Subscription rental fashion, they’re dominating in the US, they just opened in China, you can read about it here. We see a lot of similarities of with Stitch Fix and Le Tote. We love the team, their solution and the market, and think you’ll see something special in the next 18 months, but not giving any hints.
Portfolio companies changing the face of work/life
We are bullish on the future of work. We think that AI and robotics will actually make the workplace more human, not less. Humans doing meaningful work, robots and AI doing, soul-crushing tasks and computations.
Fetch Robotics — deploying autonomous mobile robots into large warehouses. Workers and robots working side by side, increasing productivity and worker happiness
Noon Home — smart lighting switches that instantly transforms homes into smart, thoughtful spaces. Lighting at home should feel like you’re being bathed in the perfect light
VC Trends in 2018?
I see fintech as an area that will continue to rise. Look for companies that are leveraging AI and behavioral economics as part of their offering.
Blockchain (not Bitcoin) for massive markets (think insurance, etc)
Non-tech wise diversity and inclusion should be and needs to be a key trend. We’re leading from the front…with our $1M parity fund initiative to demand diversity and inclusion from our investments.
Red Flags when Evaluating Companies
Single founders, while it can happen, we look for a blend of technical founders and operations founders
AI heavy pitch decks, AI light products: we see a lot of pitches with AI in them, very few actually have AI in the product
Unrealistic growth and market assumptions: early-stage companies need to fail, experiment, get the product right and educate the market on the new category…it’s art and science. You can’t expect to plot that trajectory before you’ve even started
Not big enough of a risk — this may sound counterintuitive but we are in the business of making big bets. As VC’s we need to predict the next 10 years and find those category changing companies. Incrementalism doesn’t cut it.
Originally published at swayvc.com on May 18, 2018.
