Tag: Contrarians

Anti-Social Proof

In the words of the great Fred Wilson – “If you can’t figure out why you like an investment and why it will be successful, don’t make it”.

Recently, I came across this awesome (like always!) 2012 post from Fred Wilson (Union Square Ventures) – Social Proof Is Dangerous. Quoting a line that captures its essence:

If you can’t figure out why you like an investment and why it will be successful, don’t make it.

One of the big investing ideas I have distilled from studying the best investors across asset classes – from Charlie Munger and Howard Marks to Bruce Flatt and Vinod Khosla, is that to outperform the average (the index), one has to be “non-consensus-and-right”.

In fact, in my July’23 post ‘An Investing Framework To Find Startup Diamonds‘, I outlined a Consensus vs Signal 2×2 and argued that the outlier venture returns opportunities tend to be found in the High-Signal-Non-Consensus quadrant.

Source: An Investing Framework To Find Startup Diamonds

It was only in 2022, almost a decade after I first started my career as an institutional VC, that I truly embarked on this journey of trying to become a non-consensus-and-right venture investor. As I have outlined in the above 2×2, molding my mindset toward this approach has required consciously working on the following 2 elements:

1/ Having a unique world-view and trusting my instincts to be able to spot ‘Signal’.

2/ Totally ignoring any social proof noise while doing this.

I have observed that while it was really hard to ignore social proof early on in my career (eg. which VC is leading the deal), having seen so many Tier 1 VCs across geos do such foolish things over a decade, I must say with much humility that as of today, I find it much easier to ignore their POVs on something.

A few months back, I also came across comprehensive LP data that validates this organic learning. David Clark of VenCap shared with Jason Calacanis how loss ratios are surprisingly similar across various percentiles of funds, and even the best strike out a lot.

That’s why in my view, it’s foolish to do one-off deals purely on the basis of the social proofing of a lead investor in that deal unless one is actually replicating their entire portfolio construction (which is a benefit only LPs in their Funds get).

This idea also explains why I remain skeptical of loose angel networks, angel communities, and syndicates that really don’t have a unique, grounds-up world-view and right-to-win, and therefore in most cases, do spray-and-pray on allocations in deals being done by VCs.

These deals often suffer from major adverse selection (“if the founder/ startup is so good, why are they raising from you?” OR “what specific value are you bringing to the table because of which a star founder is giving you allocation?”) and are therefore, likely to be on the wrong side of the loss ratios of major funds.

Coming back to the point of social proof, let me neatly summarize my POV on it:

  • If the best Tier 1 VCs are striking out as much as an average Joe VC, there is no value in blindly following them.
  • There could be value in investing in the “best” companies of a Tier 1 VC portfolio but especially at the seed stage, it’s impossible to know beforehand which company will turn out to be this “best” company. Also, companies keep going in and out (and back in) of this “best” bucket multiple times anyway during a Fund’s 10-year lifecycle.
  • Even if there was a way to know which company is indeed the best company in a Tier 1 VC portfolio, why would they give me allocation in it? The best VCs want to keep every bps of ownership in their best companies only for themselves.

Hence, what’s the point of doing a deal purely because of social proof? I would rather spend that effort looking for the best contrarian deals in places where no one is looking, doing the work (and trusting my instincts) to spot Signal in them, and investing in them as early as possible, driven only by my strongest conviction and nothing else.

This approach is already starting to reflect in the early Operators Studio Fund 1 portfolio. In a majority of recent investments (eg. Soulside, Confido, Loop, Astrophel Aerospace, and a recent one in Stealth), I was literally the first investor to build conviction and say “yes” even before the round started coming together with other VCs. In several of these deals, I ended up catalyzing the round itself, making intros to eventual lead investors and even sharing my customer diligence notes with VCs evaluating the company.

In a way, this approach is Anti-Social proof and Pro-Signal. What is Signal, you ask? It can be of two types, as I explained in my July’23 Investing Framework post (quoting from it here):

  • Internal – extraordinary founder-market fit eg. the founder has spent a decade just going deep in the field. Or a backstory that provides an authentic “why” behind pursuing this idea. Or an execution track record in the startup’s arc that is outstanding on important elements like capital efficiency, iteration velocity, or organic customer acquisition.
  • External – eg. a visionary customer is taking a bet, partnering with them in building the early product. Or a domain expert, skilled operator, perhaps even a specific GP in a venture firm, has taken the time to evaluate & build high conviction in the company.

As you can see, there is a little bit of social proofing baked into evaluating Signal too, but it’s much more oriented around operating and execution-oriented conviction vs deal FOMO and an investing herd mindset.

As you churn on this post, here are more POVs on this topic from some really distinguished venture investors over the years (Source: a 13-year-old Quora post titled Is social proof a rational approach to investment selection?)

1/ Roger Ehrenberg (Founding Partner – IA Ventures, one of the best-performing seed funds of all time)

2/ Naval Ravikant (Co-founder – AngelList, one of the best angels of all time)

3/ Dave McClure (Founder – 500Startups, now running PracticalVC)

Additional readings: The Death of Social Proof by Hunter Walk (Co-founder of a very successful seed VC Homebrew).

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Making Money by Understanding the Crowd

During a recent train ride in London, I observed an interesting pattern in the crowd that “rang a bell” in my head.

Here’s why understanding patterns in crowd behavior is important for successful investing.

For those of you who regularly follow my writings, am sure you have observed by know my fascination with behavioral economics/ finance & the psychology of crowds. One of my major insights from studying the work of OG investors like Charlie Munger, Howard Marks and Bruce Flatt is that the key to superior (i.e., above market average) returns is to be non-consensus & right. Getting a read on how the crowd is behaving at any point in time is one of the important analytical tools necessary to achieve non-consensus behavior.

To simplify, a crowd is a set of largely independent & uncoordinated entities, though you can define it in many other ways as per your context. There are many mental models to visualize the properties & behavior of a crowd. These include the Madness of Crowds, Herd Behavior, Social Proof, Incentives etc. However, during a recent trip to London, the city’s “Tube” train system brought back the most fundamental of these models right in front of my eyes – the normal distribution, popularly called the bell curve.

So, here’s the story. Last week, I landed at Gatwick on a busy morning, and boarded the train to Heathrow. The first thing I observed is how significantly better the London transit system is compared to anything I have experienced in the US. Even the NYC subway is nowhere close in terms of quality, multi-modality & cleanliness.

This particular train (I think it was called the Southeastern) had a very cool feature wherein it displayed how crowded each carriage was in the train, so people could shuffle around. Check out the below pic I took of the display in my train – do you notice an interesting pattern within it?

The distribution of the crowd across carriages is very close to a bell curve. Out of 12 carriages, the middle 5 are “standing room only” (yellow), 3 on the right and 2 on the left are “few seats available” (dark green) and the 2 carriages on extreme left & right are “plenty of seats available” (light green).

Seeing this pattern in a random, real-life event involving hundreds of independent & uncoordinated strangers blew my mind. I couldn’t resist taking its picture even while hanging on to 2 large bags while getting jostled in a..wait for it..middle carriage (see the bottom part of the above pic, it says “you are in coach 7”). I was myself in the middle bulge of the bell curve!

Now, besides this being a nerdy but cool anecdote, is there anything to learn from it? The applicability or importance of a normal distribution is not the main point here. The real insight is that attempting to decode & model how the crowd is behaving in a certain environment, as well as its potential implications, can by itself give investors a massive head start.

As Howard Marks says in his latest memo “Taking the Temperature“:

So, to be successful at contrarianism, you have to understand (a) what the herd is doing, (b) why it’s doing it, (c) what’s wrong with it, and (d) what should be done instead & why.

Howard Marks (Taking the Temperature)

The importance of rigorously decoding crowd behavior (or what we often call “the Market”) can’t be emphasized enough due to the simple reason that the crowd is right most of the time. When the investor-crowd is signaling that a company is un-fundable, most of the time it has correctly identified a weak business. If the market is predicting an interest rate cut by the Fed in the next few quarters, its combined wisdom is likely to be more accurate than most experts. If investors at large are investing in the AI wave or piling into an EV stock, they are indeed spotting a market opportunity that is likely to be exponential. If investor interest is low in a particular real estate location or type, most of the times it’s due to the right reasons.

While going blindly against the market consensus is flawed, first-order thinking, asking the right questions around “what” the market is doing & “why” is the first step of rigorous, second-order thinking.

The difference between “the market has spotted/ rejected an opportunity correctly” vs “the market is overly optimistic/ pessimistic on the said opportunity” is a fine nuance that can create a big delta on long term returns.

In particular, second-level thinkers understand that the convictions of the masses shape the market, but if those convictions are based on emotion instead of sober analysis, they should often be bet against, not backed.

Howard Marks (Taking the Temperature)

Abstracting this idea of understanding patterns in crowd behavior a bit more, I believe there is tremendous value in seeing various aspects of life as a distribution of outcomes. Personally, I find probability distributions more helpful in understanding how the real world works in a continuum, as opposed to statistical distributions, which are like static snapshots of reality & more academic in their usefulness.

Probability reflects how life operates in the “grey”. I have found viewing the world probabilistically to be immensely helpful in managing risk & uncertainty in every aspect of life. Too bad they don’t teach these applications while covering the subject in school!

Btw, coming back to the earlier train story, I practically used the bell curve pattern in how Londoners board trains by myself lining up either in the extreme beginning or extreme end of the platform during subsequent trips. Oh, the joy of boarding an empty carriage from the busy London Bridge station. Just goes to show that being a bit nerdy can sometimes be useful in practice!

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Do this to become a true contrarian in your career

Taken from Talk at Google presentation by Bruce Flatt, CEO of Brookfield Asset Management

“Contrarian” is one of the favorite words of Silicon Valley. Investors want to be contrarian in their picks, founders want to be contrarian in their ideas, employees want to be contrarian in the company they choose to join. In today’s age of near-perfect information flow, one has to be a contrarian to generate any sort of “Alpha” as a professional. This is in terms of both spotting opportunities, as well as timing your entry and exits. Of course, just being contrarian isn’t good enough. As Howard Marks (legendary value investor and Founder of Oaktree Capital) cheekily says, “you have to be a contrarian…and you have to be right!!”.

Over my career, I have made several moves that, at least at the time, I thought were fairly contrarian. Left a Partner track VC job to move to the Bay Area and start from scratch as a startup operator in a brand-new ecosystem. Had 2 startup offers — one from a pre-IPO enterprise software company and other from a maverick Series B startup trying to beat Google in search; joined the latter. Left a meaty role at Alibaba to start Workomo at a tricky mid-stage of my career. Invested in several companies at Operators Studio, where the businesses were (and are) considered “unsexy” from a VC perspective. Whether the above moves turn out to be right or wrong, I need a decade more to find out 🙂

Am a believer in what Robin Sharma says “if you do what everybody else is doing, you will get the results that everybody else is getting” (which is, being average). Through-out my career, I have consciously sought risk and tried to keep myself uncomfortable.

Since early 2018, when I started institutionalizing the Operators Studio investing thesis as well as ideating for my startup, I noticed something interesting. When I discussed some of my previous contrarian moves with friends & colleagues, while they perceived them as “hard to understand” or “highly risky”, I was able to naturally see those opportunities as “an obvious gap” or “the downside is really quite limited”. Clearly, these choices were taking me down a different path compared to my peers, and therefore, perhaps I was being contrarian in spotting & evaluating those opportunities. But I hadn’t articulated the mental model that I was intuitively using while making those decisions.

Over last year or so, I have tried to de-construct the above decision-making process, and then put it together again to arrive at what I call my “Zone of Real Contrarianism”. One caveat — this is my deconstruction of how I attempt to act in a contrarian way during big decisions. Not claiming this as a universal mental model but perhaps, you might derive some value out of it.

The diagram is pretty self-explanatory — to me, real contrarianism is at the intersection of what you have really high personal conviction on, and what the majority are unable to see or agree with. However, it’s important that your personal conviction is:

  1. Authentic — needs to come from an authentic place inside you; represents your personality, values, ideals, and what you stand for (not copied or overly influenced/ inspired by others)
  2. On-the-ground — original beliefs result from exhibiting skin-in-the-game in this world; being out there, understanding & playing the game (not deriving ideas & conclusions from being a desk-jockey or paper-pusher)
  3. Execution-led — observing your environment as you execute; the unpredictable, unplanned & idiosyncratic nature of execution makes it a prime breeding ground for non-obvious ideas & gaps

Nassim Nicholas Taleb defines complex systems as where the behavior of individual elements doesn’t explain the behavior of the collective or the ensemble (eg. while people are individually sane, they are prone to exhibiting irrational mob behavior as a collective). My thesis is that due to this very nature, complex systems are a gold-mine for contrarian ideas, provided you operate with skin-in-the-game in it. As a professional, I seek them out proactively (starting companies, venture investing, white space opportunities in large companies, operating in radically-new geographies & markets) to at least have a shot at generating career alpha.

Would love to hear your feedback on this mental model, and your thoughts on how to be a true contrarian in one’s career (& life).

PS: am currently building Workomo, a smart & simple professional relationships management hub for the new-age professional. If you find it intriguing, do sign-up for free private beta access.