Noted investor and entrepreneur Chamath Palihapitiya, founder and chief executive officer of Social Capital LP, joined the MOI Global community at the Latticework 2017 summit, held at the Yale Club of New York City in September. Brad Stone, author of The Everything Store and The Upstarts, moderated the wide-ranging keynote Q&A with Chamath.

We are pleased to share a transcript of the session.

The following transcript has been edited for space and clarity.

Shai Dardashti, MOI Global: Everybody has a copy of a book called The Upstarts by Brad Stone. Brad is also the author of The Everything Store, discussing Amazon, which is quite an appropriate topic at the moment and considers “Intelligent Investing in a Changing World”. I heard Chamath speak a year ago, and I was blown away by how he combines the worlds of venture and Silicon Valley with a Buffett-Munger Latticework appreciation. I am aware that Chamath respects his upbringing, has a unique story, and is quite humble. He embodies precisely what we’re trying to attain here at Latticework.

Brad Stone: We are privileged to welcome Chamath, a veteran of AOL, the Mayfield Fund, and Facebook. I was searching for the right word to describe him, and it’s one that is favored by a CEO we both admire, Jeff Bezos, which is “bold.” He started seven years ago at the Social Capital fund and has raised $2.5 billion. It is set out to change what raising and investing capital in Silicon Valley and technology companies looks like. When you started the fund, it looked like a traditional venture capital fund investing in early-stage companies. But you have set about almost relentlessly expanding the definition of the mission of the firm. What is Social Capital fund?

Chamath Palihapitiya: Well, it is not a fund. It’s meant to be, if we’re successful, what Berkshire was for so many years; this is what we would aspire to build for the 21st century. I view investing as three main arcs, and we’re starting the third arc. The first arc was where economies were relatively brittle and not that dynamic. That was probably the many thousands of years up until 1985 or so. In those periods, you had a lot of time to understand the business, to look at things bottom-up, where things like GAAP financials were a reasonable way to understand the business. Those businesses wouldn’t have changed even in the few weeks it took for a company to mail you their quarterly or yearly report. You could make decisions literally with pencil and paper and a calculator. Those decisions could withstand the test of time.

In the late ‘80s, we unleashed this weapon on finance called Microsoft Excel. Excel created this unbelievable tidal wave of false precision. Forecasting and predicting and knowing. But it happened on the heels of ushering in massive amounts of capital formation in all kinds of areas, from junk bonds to the private equity industry. All of it literally rested on teams of financial analysts running Excel models.

What has happened, particularly in the last five or six years, is the nature of companies has meaningfully changed. Every single asset is in some form of impairment. It is either fundamentally, obviously impaired, or it is being impaired unbeknownst to you, the holder of that asset, by some other technology that you do not know about.

If you believe that we venture the world of this dynamism, where the creative destruction of companies and things and technologies is so fast, then things like Excel are necessary, but they’re not sufficient to understand how the world works. A lot of what we do at Social Capital is to explore what comes after Excel. What is the next wave of investing?

Our view of the third wave is that at Facebook, a lot of what my team and I did was creating an infrastructure to collect enormous amounts of data. In the case of Facebook, it was user data. What we would do was model you—all of you—psychologically. It would allow us to get you to do what we needed you to do—click on an ad, share a story, watch another newsfeed clip. All of you have been subject to those behaviors, and you do it, and you think to yourself, “Wow, I’m in complete control.” Probably not as much as you think, it turns out, because everybody becomes predictive with enough data and information, especially if you can apply machine learning and data science to it.

We’ve asked the question; what if you apply that to the understanding of businesses? Instead of looking at lagging indicators like gap financials, start to look at the leading indicators of business quality. The only way you can get to those leading indicators is by being so joined at the hip with a company that they give you access to their operational data. That operational data could mean a transactional database, it could mean user databases, it could mean click streams, it could mean event logs. Who knows? And then you take it and you learn. What you’re trying to look for are signals that are predictive over time about how the company can and will perform. Eventually the gap financials catch up. My organization is about exploring that new frontier of decision-making. For example, Renaissance and Two Sigma would say they do some version of that, top-down. Effectively, let’s take some principles of Brownian motion, apply it to highly liquid contracts, lever it up, and trade frequently and violently. We take the opposite view, which is to partner with companies deeply, get access to their operational data, learn with them, and help them. As we understand their business, we do more with them. That’s why we’ve been relentless about adding different tiers of the capital structure to our toolkit, because with most other organizations—for example like Blackstone, a fantastic organization—every single sleeve of capital that they run is a strategy.

From our perspective, all of those are tactics. The strategy is built around data accumulation and deep knowledge. That strategy is born by hiring massive amounts of machine-learning folks and data scientists and product managers and engineers, individuals who would otherwise be at the periphery of an investment organization, or at the center of mine.

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