Techstars, the hybrid VC fund and startup accelerator, raised $42M in capital to assist its efforts in doubling down on its international growth strategy. Currently, the company operates 49 accelerator programs in 35 cities across 16 countries and expects to expand these programs across Asia, Latin America, and Australia, among others.
Connecting the global economy has historically been a fruitful exercise for public markets as it increases liquidity, opportunity, and opens channels to new sources of capital and customers. By taking an existing and successful model for incubating and growing private companies, Techstars has a great opportunity to tap into global resources and develop network effects that stand to benefit entrepreneurs, markets, and future generations across the globe.
Amazon is investing upwards of $700M in training programs to provide additional skills and resources for a third of the company’s employees, with the goal to ‘upskill’ both tech and non-tech workers. Programs will range from Amazon Technical Academy, which aims to help non-tech employees succeed in an increasingly tech-dominated work environment, to more advanced technical programs focused on machine learning and the AWS infrastructure.
At first glance, an upskill program at a company such as Amazon, which relies on a substantial contribution from non-technical roles, may come across as training for the aged population of its workforce to handle the incoming use of robotics in warehouse roles, for example. Interestingly, (and wisely) Amazon is creating a wider-reaching initiative to upskill all over it’s skill spectrum – and why not? Why only be as strong as your weakest member when you have the opportunity to strengthen all your teammates?
Funding for AI startups reached a new peak of $7.4B in the second quarter of 2019, eclipsing the previous high water mark set in the second quarter of the prior year, and the trend is continuing. The number of funded AI companies last quarter, 488, is a slight decline over the year-prior same quarter, 513, suggesting a combination of larger investments per company or larger, later rounds investments.
Long a nascent corner of computer science, AI applications have exploded in the recent decade and appear to follow a Moore’s Law trajectory as cost and time to develop these technologies, combined with the continued adoption of open-source operations, continually fall. This echoes a broader trend in tech development for startups: champions of The Lean Startup Methodology similarly benefit from the low cost and rapid ability to spin up web apps and develop MVPs, making demand testing and market size estimations both more accurate and faster. Still in it’s relative infancy, AI startups are benefitting from a more robust community thanks to programs such as Google’s Tensorflow that make training machine learning algorithms and developing AI-based applications faster than ever. More deal flow and investment will surely follow.
What are the megatrends in VC as we wrap up the first half of 2019? Highlights include the growth of the healthcare tech sector, a rise and focus on female-founded ventures, and the potential for investment in earlier stages to pick back up (now that capital previously tied up in later stage companies is coming back to LP’s with the proliferation in long-awaited exits in companies such as Uber, Lyft, Slack, Chewy, and others).
The trends in recent years have seen concentration in later stages (i.e. more money to fewer, larger opportunities), as seen in a drop in the absolute number of deals done combined with a rise in mega-rounds. These mega-rounds, however, have begun to plateau in size this year, alongside a general slowdown in earlier stage investment volume and later stage deal size in 2019. Are we witnessing the beginning of a prolonged slowdown in VC investment or the bottoming of a cycle? Have the coasts become saturated? Now that LP’s have exited from mega-IPOs, will these profits be put back to work in earlier stage investments?
The Venture Capital industry is to many opaque and often misunderstood, as are many of the key functions of the private companies in which VC funds invest. This can in many cases lead to certain aspects of these companies being ignored, and culture may be one of those areas. Why, in an era where corporate culture can generate multiple news articles a day for the wrong reasons (Facebook and Uber), do VC’s often have a blindspot when it comes to assessing culture? Here’s a framework for VC’s to assess it.
Company culture, and the practices which stem from it (hiring, firing, training, customer service, among others) can create a sustainable competitive advantage in many instances (or a lack thereof) – just ask Nike, Zappos, AirBnB, and Hubspot as the author alludes to. When asking questions that generalize or frame an entire community (Venture Capital for example), it is also important to be wary of recency bias (adding emphasis to more recent events) or availability bias (emphasis on more easily-recalled events) – the news can be biased toward negatives (it wouldn’t be news in most other cases) but developing a framework to assess a very un-quantifiable thing should be part of every VC’s due diligence program. Looking for a recommended read on understanding company culture? I suggest The Culture Code (Coyle) – mandatory reading for all VC’s!
The Real-Estate focused fund has closed what it calls the largest real estate venture fund to date. The GPs note the fund’s focus will be more so on B2B applications than past funds, adding that tokenization of real estate assets is, “probably one of the most interesting thing(s) we think about on a daily basis.”
No VC newsletter would be complete without the requisite blockchain shout-out, but when you step back and think about the potential for the application of blockchain technology within the largest asset class in the world, it makes you stop and wonder. The real estate sector, compared to many others, has been a relatively slow adopter of technology, which has begun to change over the past five years – and appears to not be slowing down. Tokenizing illiquid assets could open doors for new forms of investment in the asset class (partial ownership and therefore purchases and sales of a property), greater liquidity (sales executed via smart contracts), access to unique housing affordability options (more advanced rent-to-own or aforementioned partial-parcel ownership), among so many others. In a country where wealth is often predicated on home ownership, revolutionizing this industry could have widespread positive impacts.
Asymmetry is a defining hallmark of the VC industry according to Scott Kupor, GP of a16z, given the fact that VCs pour through thousands of investment opportunities per year relative to the single opportunities most founders develop in a lifetime. This, as Kupor notes, creates challenges on both sides and partially explains the success of programs such as Y-Combinator, who attempt to solve this problem by acting as a deal-funnel and match-maker.
Efficiency is required on both sides in Venture Capital. For entrepreneurs it means building the most valuable company with the minimum amount of resources and costs necessary (and retaining equity ownership!) while the other side of the table tries to balance generating solid deal-flow that supports the time necessary to perform due diligence on enough opportunities to not miss out on the next unicorn. Ironically, VCs may need to turn to technologists to develop platforms and tools to assist in these efforts, expand team sizes, generate better screening processes, focus on niche markets and offerings, or other ideas. How will mega funds whose economics almost require being generalists in order to both source enough deal flow and invest at later stages where check sizes are bigger handle these challenges? How can funds who specialize generate enough deal flow to find enough sizeable opportunities?
As the company who revolutionized coworking prepares to go public, some are questioning the health of the company’s pending IPO given the company’s internal perception as a(n existing) tech company but perhaps public perception as a (boring) real estate company.
Tech companies often garner higher valuations given their higher growth rates, especially compared to real estate companies (which, as primarily a real estate holding company, WeWork arguably is). Fortune concludes that dividend-seeking investors may therefore be disappointed (but should not be surprised) when WeWork the real estate company fails to act like one (by paying predictable dividends based on more predictable income streams from office rents, for example – like publicly traded REITs). The massive dividend-prohibiting losses themselves, however, combined with a potential re-valuation from a hot tech startup to a real estate company – which could dictate a much lower valuation that what the private markets have assessed – would be my primary concerns.
Compass, the hot new tech-driven and high-growth real estate brokerage is similarly facing the same issue (more insights here, subscription required). Likely prepping for an IPO in the next 12-24 months, the company’s private market valuation stands nearly 4x that of it’s public market peers (Realogy and Keller Williams). Should it be valued like a tech company or a real estate company? Should WeWork? How WeWork is valued may be a good indicator for Compass, FYI.
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