From Experiment to Product: Capital-as-a-Service One Year Later
I recently saw a tweet that blew my mind:
Mike Moritz, the famed Chairman of Sequoia ruffled some feathers recently by opining even more pointedly about this topic by comparing the future of Chinese vs U.S. tech ecosystems. The old narrative was that Chinese technology companies copied what they saw in the U.S. Those days are long gone. Today, companies in China have access to massive compute resources, a strong talent pool, and troves of data, and are finding product-market fit at massive scale. And we’re more likely to copy them than they are us.
So what, exactly, is happening?
I’ve spent my entire adult life and career in Silicon Valley, and the answer to me is clear. Even just a decade ago, when venture capital and technical talent were already plentiful, the friction that stood behind a good idea and a willing customer was too high. Today, the exponential growth in both scale and scope of public cloud providers has turned this reality on its head. The relentless pace of innovation and price competition among Amazon AWS, AlibabaCloud, Microsoft Azure, and Google Cloud means the barriers to entrepreneurship are now lower than ever. With the proliferation of affordable cloud infrastructure, initial costs have fallen close to zero. There was never a shortage of compelling ideas and driven entrepreneurs. There was just an uneven distribution of resources and capital. Now that the barriers to resources have fallen, it’s time for capital to follow suit.
This is why, a little over a year ago, we started working on a new model for capital allocation designed to keep up with the pace that ideas all over the world were being converted into successful businesses, and to put the entrepreneur at the center. Our bet was simple: that as more and more founders around the world begin building their businesses on top of a small number of consistent public clouds, the operational data from running these businesses would become increasingly comprehensive and accessible. In this world, you could understand a company not based on broad intuition or low-fidelity graphs in a PowerPoint presentation, but rather based on real-time data about how successful that business was at turning prospects into engaged customers.
As in so many other domains from medical diagnostics to transportation, software could also begin to do parts of the job of a venture capitalist. We could complement human judgement with data science. Validate anecdotes through machine learning. Replace all of the bias and limitations of a human-based process with all of the precision and reach of software.
Then comes the fun part. If you can understand any business from any corner of the globe, then you can begin to compare and contrast. You can invest in the best of the best. If you can measure any business relative to its category, you can improve it. You can offer unique insight and value to founders. A year ago we launched the alpha version of Capital-as-a-Service (“CaaS”) to do just this. Founders engage with us online and self-select into our queue for diligence and funding. Without so much as a plane ticket or a coffee chat, entrepreneurs submit their transaction data to our automated diligence engine and we can make funding decisions in a matter of hours. Overnight, through software, we were open for business on six continents (no submissions from Antarctica… yet!), 24 hours a day, 365 days per year.
With CaaS, our goal was to launch a new operating system for early stage investing, built on the principles of data-based decisions and architected for global reach and scale. A platform that would enable any founder, anywhere in the world, to short-circuit the arcane frictions of the traditional fundraising process and get straight to the heart of what matters: the product-market fit and the compounding value created for customers. We sought to make decisions that were transparent, consistent, and unbiased, and to offer a feedback loop to entrepreneurs based on the predictions of our models.
A year ago, CaaS was a radical experiment. Today we evaluate this effort in the same way we evaluate startups: with data. Below is an infographic of the first year’s progress of CaaS. In short, the demand and reception from entrepreneurs has exceeded our expectations.
A few things to note:
- The fund is already out of the J-curve, which is quite rare one year into a (mostly) seed stage portfolio.
- The companies are quite diverse in sector, geography, and demographics.
- The portfolio is starting to build momentum with other investors who value the accreditation that our diligence gives a company, as they seek to raise additional capital or are going through an M&A transaction.
I am excited to see where this ultimately goes. And at Social Capital, we are committed to augmenting our high-touch venture business in Silicon Valley with the automation, tools, and software to help entrepreneurs everywhere improve the lives of those around them, both locally and globally.