Category: Venture Capital

A Talent Scout Mindset For VC

Outlier venture performance requires being non-consensus-and-right. Framing your role as a Talent Scout, vs. just a Picker, improves the odds of finding such opportunities.

I strongly believe in Howard Marks’ framework that for better than average investing performance (i.e. beating the benchmark), an investor needs to be non-consensus-and-right. My own derivative framework for venture investing is to look for High-Signal-Non-Consensus deals – companies where I am catching strong leading signals, but which the investor-crowd is struggling to understand.

Executing this strategy well requires consciously looking for:

(1) Overlooked markets, and/ or;

(2) Underestimated founders.

If both the market and team were hot, the company by definition, would be consensus. Consensus deals get significantly bid up in price, and as Howard Marks frequently says, high prices indicate low future returns. Therefore, through both learning from OGs like Howard Marks and observing my portfolio’s behavior over the last decade, I have gradually come to believe that entry price definitely matters in venture investing.

While evaluating teams, the role of a VC is often defined as that of a Picker. The best GPs possess a combination of 3 abilities:

1/ Analyzing tangible skills for founder-market fit.

2/ Using past experiences to pattern-match for intangibles like grit.

3/ Having a 3rd filter of intuitive judgment that may override the previous two.

While these features are cool for venture capital in general, they might still fail during the specific quest for identifying underestimated founders. By definition, many of these founders don’t have classic indicators of tangible skills such as Ivy League backgrounds, Big Tech work experience etc. Further, they can have quirky, irreverent, or misfit personalities, so pattern-matching with past venture-backable personas will also not give the right output.

The 3rd feature of intuitive judgment becomes overwhelmingly important in this scenario. Therefore, to describe a venture investor who is on a conscious quest to discover underestimated founders, I prefer the framing of a ‘Talent Scout’ over that of a Picker.

To highlight the mindset of a Scout, here’s a cricketing story once shared by the famous Pakistani bowler Shoaib Akhtar, the fastest in the world at that time who regularly hit the 150-160 kmph range. As an unknown player harboring ambitions of playing for the national team, Shoaib once turned up for trials that were being run by legendary cricketer Zaheer Abbas. More than 3,000 kids turned up so to grab Mr. Abbas’s attention, Shoaib started running laps around the 3 km cricket ground in sweltering heat. A kid hungry enough to be doing this madness caught the legend’s eyes. He asked Shoaib to bowl one ball at the nets, and the rest is history!

The mindset of a Talent Scout is to focus on developing a ‘Feel’ for talent, judge how strong this Feel truly is, and then have the courage to let it become the basis of strong conviction even in the absence of other tangible signals. What’s the source of this Feel, you ask? That’s the alpha, the x-factor of the Scout. Sometimes it’s a unique worldview of what it takes to win in that particular game. It can also be just a superior reading of human behavior. Often, Scouts can access a subconscious intelligence, built up over many years but still hard to precisely explain.

When meeting non-consensus founder talent, I have found adopting the mindset of a Scout to be immensely helpful. It’s a very different context from evaluating a typical venture-backable persona or a relatively proven team, and therefore, this change in mindset leads to an interaction of a very different flavor.

The hope is that having a talent scout mindset leads to an increased likelihood of non-consensus-and-right investments, thus positioning the portfolio for generating venture alpha.

Closing out with this line from my friend Manish Singhal who runs the deeptech fund Pi Ventures – “We don’t have proprietary deals. We create a proprietary view on the same deals everyone sees.”

PS: if you liked the concept of scouting underestimated founders, do check out my post ‘Reputations and Underdogs in VC‘ which tackles whether spending time with the laggards in your venture portfolio makes sense or not.

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One Person’s Conviction For Easier Fundraising

As a fundraising founder swimming in the rough seas of skeptical investors, sometimes all you need is a high-conviction intro from one sponsor to tip the scales in your favor.

As a venture investor, referrals from people in my network is one of my top channels of deal flow. There are hundreds of startups that reach out for fundraising discussions every month. Having someone you know vouch for a founder automatically gives initial comfort around taking a meeting.

Over the years, I have observed that these referrals fall into 3 categories:

1/ Weak intro: beyond being a friend, the referring person doesn’t know much about the founder’s idea or the reasons behind pursuing it. These referrers are usually the founder’s weak acquaintances and are only helping out with connecting to a bunch of investors.

While even a weak intro ensures that I pay attention to the startup, conversion to a live interaction is usually low.

2/ Warm intro: the referrer has deeply known or worked with the founder in the past, and has a fair idea about their personal mission, goals, and personality. Typically, these referrers are ex-direct managers, peers, college friends who have stayed in touch, and other direct collaborators. They might or might not have an understanding or appreciation of that particular startup idea but believe in the founder.

These intros are solid, especially as the founding team is the top-most investing criterion at the early stages. In most cases, I will typically schedule a 30 min. video call with the founder at the very least.

3/ Conviction intro: the referrer has spent significant time either organically or consciously, to develop a deep conviction in both the founder and the startup idea. These referrers are usually founder execs, senior operators, angels, and VCs.

In the best cases, the referrer is also showing skin-in-the-game via either investing significant money and/ or time in the startup.

Conviction intros are gold and a great signal of the quality of an investor’s deal sourcing. For almost all such intros, I end up scheduling a 1-2 hour deep brainstorming session to get into the weeds. Interestingly, by the end of these sessions, the judgment on whether to invest or not gets immediate clarity.

Adding more nuance…

I would like to go one level deeper on Conviction Intros, and talk about what I call ‘One Person’s Conviction Intro’.

Those who regularly read my blog would remember the post ‘An Investing Framework to Find Startup Diamonds‘. In it, I talk about the ‘High-Signal-Non-Consensus’ quadrant where the best startups are to be found at the early stages.

Deal ScreenConsensusNon-Consensus
High-Signal🪙🪙🪙
Low-Signal
Consensus vs Signal 2×2 ©Soumitra Sharma

(4) High-Signal-Non-Consensus – these are the opportunities we as venture investors live for. They are highly non-consensus, with the investor-crowd struggling to access, understand, evaluate risk and build a positive view on them. Yet, these startups have high-quality leading signals, which could be external and/ or internal.

  • External – eg. a respected investor, sometimes a domain expert, has taken the time to evaluate & build high conviction around the company. Or a visionary customer is taking a bet, partnering with them in building the early product.
  • 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.

This quadrant is the hardest to source for and requires having a really differentiated network of relationships (for referrals) and a personal brand that attracts interest from these types of founders.

An Investing Framework To Find Startup Diamonds

As mentioned in this excerpt, the High-Signal part comes from someone credible putting in the effort to build conviction, demonstrating skin in the game via committing any type of valuable currency, and then risking their personal reputation to socialize the opportunity with their trusted networks.

This opportunity might still be Non-Consensus, with the investor-crowd struggling to appreciate it. Yet, this referrer (or perhaps ‘sponsor’ is a better word in this context) is willing to be contrarian and follow their own conviction built from first principles.

When this sponsor refers a deal to me, this One Person’s Conviction Intro sits at the peak within the universe of Conviction Intros, simply because it has a high likelihood of being a key to the High-Signal-Non-Consensus quadrant.

However, even an investor with the highest quality deal flow can only expect a handful of such intros every year. The reason is most founder execs and operators don’t have the time and/ or incentives to build independent conviction. And most angels and VCs tend to demonstrate herd behavior, preferring to lazily piggyback on the conviction of others versus taking the time to do independent thinking.

So, even though my investing style is predicated on searching for these intros, the world is supply-constrained with respect to them. However, what I can do is swing really hard when I do get a few of these fat pitches every year, and maintain discipline at all other times. Venture investing is a very forgiving game where one isn’t reprimanded much for the losers, as long as you get a few right in a big way!

For founders, getting warm intros to investors has now become common knowledge, and frankly, table stakes. However, what could give you an edge over hundreds of other fundraising founders is inculcating that one sponsor – someone who can build independent conviction on your yet-unvalidated startup, show skin in the game, and socialize their commitment to other investors.

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When will the next venture bull run begin?

While public markets appear to be decisively reviving this year, venture activity barring AI is still very slow at large.

With founders & investors worried about when the good times will return, I turned to an age-old framework by the OG Sir John Templeton to try and answer this question.

I recently listened to the latest quarterly update podcast, “What’s Exciting in the Market Right Now?” by Miller Value Funds. I am a big fan of Bill Miller & always make it a point to deeply reflect on what he says.

In this pod, Bill cited an insightful quote by the late Sir John Templeton, the legendary founder of Templeton Funds:

Bull markets are born in pessimism, grow on skepticism, mature on optimism and die on euphoria.

Sir John Templeton

A. Templeton’s framework

Bill then goes on to apply this Templeton’s framework to explain market cycles over the last 15 years as follows:

  • During this period, the first point of maximum pessimism was in March 2009, which then birthed a new bull market. The next point of max pessimism was March 2020, which gave rise to another bull market.
  • Dec 2020 was the point of optimism, post which the market fell ~38% but then rallied again. Ultimately, the point of euphoria was reached in Nov 2021, which saw the peak of popularity for innovation bulls like Cathie Wood of Ark Invest. At this time, interest rates were at rock bottom while valuations of unprofitable growth companies were sky-high.
  • The most recent point of max pessimism was in the Fall of 2022. Since then, overlaying market performance on top of Templeton’s framework, it’s safe to say that the next bull market has already started. Markets are up ~20% since this last point of max pessimism and therefore, this new bull run appears to have reached the “grow on skepticism” phase in July 2023.

Bill then goes on to say something super insightful (man, the amount of wisdom in this 10 min monologue!). Paraphrasing a bit here:

Microstrategists try to use their view of the economy to determine where the market is going. And that’s exactly backwards.

The economy doesn’t predict the market. The market predicts the economy.

The market comprises of real people with real money at risk, and the totality of them is how the market acts.

Bill Miller

Just think about the 2nd para in the above quote. It’s an amazing thought! Intuitively, we all tend to think of the market as an analytical engine when in fact, it’s actually a prediction engine. It’s a complex system where hundreds of millions of people are looking at all the info they have, making a prediction of where the economy is likely to be headed & placing bets with real money based on this prediction.

But I digress! Coming back to Templeton’s framework, as I was digesting it in the context of public markets, I ran a thought experiment on whether it applies to the venture market as well. This is how the exercise went.

B. Applying Templeton’s framework to venture

It’s important to mention upfront that private markets differ from public markets in a few important ways, which manifest in specific behavioral characteristics:

1/ They are illiquid ➡ price discovery happens gradually & therefore, lags public markets at least by a few months if not years, due to system inertia.

2/ They have fewer (very small retail participation) but more sophisticated participants ➡ both upward & downward resets have relatively less internal momentum & are, therefore, more gradual.

3/ They have high information asymmetry ➡ takes time to gather, analyze & react to information. Given higher imperfections, probabilities & confidence intervals are assigned to conclusions more conservatively.

4/ There is negligible automated trading & auto-pilot inflows ➡ information is analyzed & acted on by real humans in a slower, more deliberate way.

Essentially, private markets are slower, more concentrated & more deliberate with longer feedback loops than public markets. Therefore, while public markets can be analyzed daily, weekly, or monthly, I believe a safe unit of time to analyze the cyclicality of private markets is a year.

To start applying Templeton’s framework to the US venture market, I looked at data for total venture capital $$ invested in the US every year since the dot-com bubble. Here’s how the data looks:

Source: NVCA Yearbooks (for years marked with *, data was sourced via ChatGPT as it was unavailable on the NVCA website)

Here are some insights I gathered from this data:

1/ During the dot-com bubble, 1997 and 1998 look like the years when the venture bull run entered the “grow-on-skepticism” phase. It then hit the “mature-on-optimism” phase in 1999, achieving the “point-of-euphoria” in 2000.

As per the Templeton framework, the point of euphoria is when the bull market typically starts its journey toward death. This is exactly what happened to the dot-com bull run between 2001 and 2003, hitting the point of maximum pessimism in 2003. Interestingly, going back to the earlier point of a lag between public and private markets, this 2003 point of max pessimism for US venture was a year behind the same for public markets (they bottomed in Oct 2002 when the S&P500 hit a 5 and a 1/2 year low).

2/ Moving forward, the US venture market again followed Templeton’s argument of “bull markets are born in pessimism”. The seeds of its next bull run were sowed in 2003, subsequently entering grow-on-skepticism during 2004 and 2005. This bull run entered mature-on-optimism in 2006 and 2007, growing 25%+ y-o-y.

But before it could hit a real point of euphoria, the housing crisis happened in 2008. The US venture market hit the point of max pessimism in 2009, and similar to the dot-com run, lagged the public markets by a year (their point of max pessimism was in Sep 2008).

3/ With the tailwinds of the Fed’s zero interest rate policy post the ’08 crash, the US venture market saw a secular bull run between 2010 and 2021. Barring a few corrections and a brief Covid hiatus, this was an almost uninterrupted, decade-long, dream bull run.

Fueled by massive liquidity injection by the Fed to counter potential Covid-driven economic distress, on top of astonishingly low levels of interest rates, the US venture market hit the point of euphoria in 2021. As I wrote in my post “Making Hay During Market Peaks“, this was the year of “Crypto shitcoins, ape NFTs, meme stocks, IPOs of unbaked tech companies, and real estate boom in as far as Denver & Raleigh”.

C. Where are we now in the current venture cycle?

Consistent with Templeton’s framework, the recent decade-long venture bull run started its downward spiral from the point of euphoria in 2021 and subsequently hit a point of max pessimism in 2022 (~30% y-o-y decline in VC $$ invested).

But this framework also tells us that the seeds of the next venture bull run were also sown simultaneously at this point of max pessimism in 2022.

As we stand today, I get the feeling that the US venture market is close to entering the Day 0 of the grow-on-skepticism phase of its next bull run (I wrote about how the excesses of 2021 are now winding down in my post “Cheetah in the Rainforest: 2021 Vintage of Venture“).

Per Bill Miller, public markets have already entered the grow-on-skepticism phase decisively, showing ~10% gains in H1 2023, and are likely to continue on this trend in H2. Assuming a ~1-year lag between public & private markets like in previous cycles, my expectation is that the next venture market bull run will decisively enter the grow-on-skepticism phase in 2024.

C. Closing thoughts

As a disciple of Charlie Munger, while I don’t believe in macro forecasts (especially by economists & equity research analysts), I am also a disciple of Howard Marks and therefore, a strong believer in the importance of studying market cycles across asset classes. Where we are in a cycle should be one of the important inputs for deliberation on an optimal investment stance, including what mix of offense & defense to aim for.

Hence, my fascination with Templeton’s framework, and how well it works as a tool for studying cyclicality in both public & private markets.

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Cheetah in the Rainforest: 2021 Vintage of Venture

“A firm writing seed checks without specific competence in that stage is like a cheetah in the rainforest. The beast is a wonder of nature that can run at a top speed of 60-70 mph in the African grasslands. But place it in the Amazon rainforests, and all its wondrous capabilities will amount to zilch. It’s just not built for it!”

Most 2021 vintage startups got VC ‘cheetahs’ on their ‘rainforest’ Boards. Surviving the new reality that faces them, will require a cathartic reboot.

Had an interesting conversation with a Bay Area-based founder a few weeks back. His startup is in the high-ACV enterprise space wherein the product is solving an intense and wide-ranging problem that is especially applicable to large companies. He got off the blocks in 2021 with a mid-single digit $Mn pre-seed round by a top-tier VC at the idea stage itself. A start that most founders dream of!

However, now two years down the road, the situation on the company’s Board is far from rosy. The company has gone through tumultuous times that are typical for any 0-to-1 startup. While the founder has kept his chin up during this phase, he is very disillusioned with the VC’s advice, behavior & general stance so far. When he shared some specific examples of this with me, my first reaction above all else was that this firm clearly has little past experience of portfolio management at the seed stage & in particular, what founders need in order to navigate its inherent complexity.

As I started relating this to many other founders I have met this year, a pattern is clearly emerging in the 2021 vintage of startups. Specialist VCs who have mainly invested in the Series A & beyond space in the past, went upstream & wrote massive pre-seed & seed checks with minimal or no traction. They were probably under pressure to deploy or get early dibs on the best teams as later stage valuations were going to stratospheric levels.

Seeing these companies now, after most of them have almost consumed their 24-month runway, I am seeing how the lack of milestone-based capital sequencing & strong stage-firm fit has created many fundamental issues with their core:

1/ Armed with big checks from large AUM firms, founders ignored the scrappy, capital-efficient approach right out of the gate. Instead, they bulked up teams & spent disproportionately on go-to-market even before problem-solution fit. Now in hindsight, they have ended up creating fragile organizations that are at the mercy of the macroeconomy & availability of follow-on capital.

2/ Many of these VC firms have put relatively inexperienced team members on the boards of these companies. My guess is because in their overall AUM game, these types of really early investments are probably considered highly risky “option bets” with low stakes in general & therefore, good learning opportunities for more junior members.

While experience by itself doesn’t make anyone a good or bad VC, pre-seed & seed stages of venture capital demand much more art & judgment in company building from all stakeholders. A firm writing seed checks without specific competence in that stage is like a cheetah in the rainforest. The beast is a wonder of nature that can run at a top speed of 60-70 mph in the African grasslands. But place it in the Amazon rainforests, and all its wondrous capabilities will amount to zilch. It’s just not built for it!

It’s a bit counter-intuitive but in my view, the best VC talent (best = strong fit from a personality & skills perspective) needs to be involved in the earliest stages of company building. There is a reason why YC has a strong moat in that stage, & why while most fresh MBAs can invest & do portfolio management at Series A & growth funds, pre-seed & seed needs artists like Paul Graham & Semil Shah that are few & far between.

One of the things I would like to see coming back into the startup ecosystem foundation post this venture downturn is the importance of “capital staging” – rigorously thinking through how the company should be capitalized at the earliest stages, what kind of investors should be assembled for it, the mindset, approach & time a specific company would need to iterate towards problem-solution fit & eventually, product-market-fit.

I would like to see the return of angels, domain operators & specialist boutique VCs partnering with founders at the earliest stages of venture. We need some version of the Arthur Rock & Ron Conway models but modified for this age. These types of stakeholders in turn, would educate and/ or encourage founders to be scrappy, agile and perseverant during the 0-to-1 stage, supporting them in building the most optimal path to the next base camp.

Closing thoughts specifically for the 2021 vintage startups – while it’s not easy to rewire the foundational DNA of a company, it’s not impossible. While the lesser gritty teams will flame out, I am also seeing founders who are acknowledging both the mistakes of the past as well as the new reality that faces them and are determined to learn & re-invent themselves. Even though as an investor, I am not too excited about the 2021 vintage the way it looks & is behaving right now, I will be more than eager (& rightly so!) to back its re-invented & re-wired v2.0.

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An Investing Framework to Find Startup Diamonds

As a venture investor dealing with high volume deal flow across sectors, stages, and founder personas, how does one effectively screen for the diamonds amongst the rocks?

Sharing a deal screening framework to help improve any venture investing process.

As an operator-angel, I consciously follow a “tech-generalist, founder-first” style of investing. It both suits my background (which is very cross-sectoral & cross-functional) as well as helps me cast a wide-enough net.

I believe one of the core advantages of being a solo investor is not being boxed in a niche fund strategy or sector focus. As tech evolves rapidly across geos, I like the freedom to be able to seek out the best founders in whatever vertical they might be building in, as well as be opportunistic in terms of participating across stages & in special situations too. This is the model that the likes of Elad Gil & Jason Calacanis have followed.

Of course, one has to still identify the game where one has an “edge” in, to have the best odds of outlier returns. For me, that’s focusing on what I call the “Global Indian” founder persona. It includes:

(1) India based founders building for the world (eg. cross-border SaaS, enterprise, deeptech etc.), and

(2) Indian immigrant/ Indian-origin founders building tech cos. in large markets like the US & SE Asia.

This is the persona where I have high-quality access, where I am able to understand & relate to the founder’s journey & motivations, as well as add value with empathy, given I am myself a Global Indian.

With this strategy, I end up with a massive top-of-the-funnel of deals across a wide variety of sectors, stages, geos & check sizes. Over the last few months, I have been trying to think of some sort of a screening framework to be able to quickly figure out where a new investment opportunity fits in my deal universe. Ideally, this framework should help easily visualize a deal’s preliminary fit with my strategy, before taking it into deeper diligence & running my entire check list on it (my core IP!).

While any such framework can involve many types of vectors, I have been experimenting with a “consensus vs signal” 2×2.

Deal ScreenConsensusNon-Consensus
High-Signal(2)(4)
Low-Signal(1)(3)
Consensus vs Signal 2×2 ©Soumitra Sharma

These vectors abstract out 2 important elements of venture investing:

  • Consensus – what is the investor-crowd’s opinion on whether this startup* makes sense or not.
  • Signal – what is the quality of people** who believe in the startup & have skin-in-the-game.

*”Startup” here means an amalgamation of team, market & product.

**”People” here includes founders, employees, customers, existing investors etc.

Let’s look at what each of the quadrants in the 2×2 mean:

(1) Low-Signal-Consensus – these companies lack high quality operating signals around the business and who the investor-crowd agrees will find it hard to make it big. A typical example would be an idea stage founder with no educational or career spike, going after an established (highly competitive?) market but with weak founder-market fit, and yet to demonstrate any early validation or traction around the startup’s hypothesis.

These opportunities will usually have negligible investor interest. When I come across such companies, my instinct is to first check if I am seeing any positive signal that the crowd is missing. This could be a behavioral characteristic of the founder, something from their personal backstory or from their startup journey so far. Idea is to see if there is some sort of high-quality leading signal hiding in plain sight.

If I sense a likely positive signal, I try and maintain a thread with the founder over coming months, attempting to see if subsequent execution can help build some conviction.

Note: most cold inbounds on LinkedIn, as well as startups from college incubators/ accelerators/ b-plan competitions fall in this bucket.

(2) High-Signal-Consensus – these companies have high quality signals around team pedigree, investor interest, customer traction etc., and who the investor-crowd agrees are potential winners. A typical example would be a repeat founder building in an established market that is universally understandable, has a large TAM and a past history of large outcomes.

While these deals are understandably hot, high investor FOMO around them creates 2 risks:

  • High entry valuations, bringing down future returns.
  • Because these deals look so obviously good on paper, it drives investors to overlook asking hard questions around the business. Does the repeat founder have fit with the space? Is there hubris at play from past success? Is the company being over-capitalized & therefore, not being set up for capital efficiency?

Therefore, whenever I see a High-Signal-Consensus deal, my antennas go up & I consciously try to keep FOMO at bay while increasing the rigor of the evaluation process.

Note: most deals that I see in angel syndicates or groups fall in this bucket.

(3) Low-Signal-Non-Consensus – these companies lack high quality operating signals around the business. But interestingly, the investor-crowd also doesn’t have a consensus yes/ no view on it yet. Reasons could be the space is esoteric so hard to understand, team’s background is non-traditional, or location is non-top-tier, founder is bad at pitching etc.

While looking at these opportunities, I am conscious of these being potential “non-consensus traps” – companies that look good to someone trying to invest against the crowd just for the sake of it, without building first-principles conviction.

I have an inherent positive bias for underestimated founders & overlooked assets. That’s why I try to be consciously careful in this bucket of startups as with experience, I have learned that bad companies are in most cases, just bad companies.

(4) High-Signal-Non-Consensus – these are the opportunities we as venture investors live for. They are highly non-consensus, with the investor-crowd struggling to access, understand, evaluate risk and build a positive view on them. Yet, these startups have high-quality leading signals, which could be external and/ or internal.

  • External – eg. a respected investor, sometimes a domain expert, has taken the time to evaluate & build high conviction around the company. Or a visionary customer is taking a bet, partnering with them in building the early product.
  • 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.

This quadrant is the hardest to source for and requires having a really differentiated network of relationships (for referrals) and a personal brand that attracts interest from these types of founders.

When I meet startups in this quadrant, I immediately get to work, spending time with the team & together unboxing every facet of the market. Generally, these deals have relatively less investor FOMO so I can take the time to run my conviction-building process with rigor.

The risk in this quadrant, and purely from my personal investing style & behavior perspective, is that I tend to get positively biased on them very quickly. After many such experiences, I now consciously play devil’s advocate during the evaluation process. Btw this is where running a rigorous conviction building process and avoiding a trigger-happy mode really helps.

Hope you found this screening framework interesting & perhaps helpful for your own venture process. Of course, evaluating an early-stage venture opportunity is much more multi-dimensional than this. But having such a framework really helps in effectively allocating bandwidth while managing high volume deal flow.

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Reputations & underdogs in VC

In venture investing, there are obvious stars in the portfolio that generate returns. But what about the ones that are struggling?

I believe that spending time with the underdogs offers the opportunity to learn & build reputations. Here’s why.

During a recent brainstorming session with one of my VC friends, the topic of bandwidth allocation between high-performing “stars” and struggling “underdog” portfolio companies came up. In the flow of the conversation, I ended up saying this:

Star portfolio companies will likely generate returns, while the struggling underdogs offer the opportunity to learn & build reputations.

There is an inherent dichotomy in managing a venture portfolio – the best-performing companies require little investor bandwidth & yet, have high probability of success while the ones struggling demand an inordinate amount of effort & yet, have low odds of success. Brad Gerstner of Altimeter said this in a different way during a recent fireside chat with Mubadala:

If this founder relies on us to succeed, then we chose the wrong founder. Our job is to increase the probability of success, not create the success.

Brad Gerstner, Altimeter Capital

Given this dynamic, it’s natural that purely from an opportunity cost optimization perspective, venture investors will be drawn to divert bandwidth away from struggling companies & towards forward-looking activities like triaging & protecting likely winners or sourcing new deals.

However, as an operator-investor focused on the pre-seed & seed spectrum of financing, I tend to view this tradeoff differently. Personally, I believe in spending time with struggling portfolio companies & supporting their founders as they guide the ship through choppy waters. Not for emotional or moral reasons, but because it makes execution sense in really early stages of venture investing:

1/ Because it’s unclear who will eventually win: till Series A, which is typically an acknowledgement that the company has reached product-market-fit, both “high performing” & “struggling” are loosely defined, temporal phases of company building. Companies will move in & out of these buckets during the up-and-down journey towards PMF. Only by spending enough operating time can an investor develop independent judgement on each company’s potential, quality of execution & what all stakeholders should be doing to tip the scales & increase the probability of achieving PMF.

I call this “building conviction” – something that Paul Graham clearly did for Airbnb by closely observing how the founders were building & iterating on the ground. This is what gave him the conviction to bat for the team in front of top VCs even when a majority of them were just not seeing it.

The alpha of OG venture investors like Paul Graham is their ability to see the kernel of a “top” company within a “presently struggling” one. This happens only by spending the time to closely track the founder’s execution approach & mindset. Reproducing some of the email exchanges between PG & Fred Wilson of USV, to highlight this (Source: Paul Graham’s post from March 2011)

_______

_______

2/ Because you learn what is not working: venture investing is a feedback loop business. It’s an infinite game where the goal is to keep improving daily by learning what works & doesn’t as the world evolves & incorporating the lessons back into your systems.

In my experience, spending time with companies in troubled waters helps absorb lessons not available anywhere in the physical or digital world. Be it co-founder conflicts, screwed up cap tables, botched hiring or excess spending, these human experiences are worth their weight in gold, and reflecting them both in front of other portfolio founders as well as in your own investment process going forward, is key to tilting the playing field a few degrees in your favor. Cumulatively, this can add up to a huge competitive advantage over a long period of time.

3/ Because fighting till the last breath is a DNA: while what Brad says above is true, especially for growth stage companies which is where Altimeter operates, even the best founders pre-PMF need a lot of support & coverage for their gaps & blind spots. The best venture investors strive to create delta on the “increase the probability of success” part of the job, which is why while capital is a commodity, individuals GPs that move the needle during a company’s long lifecycle are rare & so in-demand.

I remember listening to Doug Leone of Sequoia at an event a few months back where he mentioned believing in fighting alongside the founder till the last day of the company (also reflects his tough New York Italian upbringing!).

My organic investing style is cut from a similar cloth, wherein I focus on bringing a company-building DNA to every cap table I have been a part of. Though, it hasn’t been without some self-doubts, as there is no immediate fruit to show for all the labor this approach demands.

Case in point being an erstwhile portfolio company in queue management software. I was literally the first check into the company as an angel way back in 2015, and also helped syndicate that first round. About 2 years in, the company was out of cash, all employees had to be let go, 2 co-founders jumped off the ship, and the remaining 2 founders were trying to engineer a pivot from a consumer app to an enterprise use case.

On paper, this would look like a dead duck to any sane person barring 3 people – the 2 remaining founders and me! We kept pushing on, literally on fumes. I remember having many late-night operating sessions with the founders every week for almost an year, in parallel to my day job at Alibaba & also being an expecting first-time father. In fact, I remember my better half asking me more than once – “why are you burning yourself up over a small angel check? Is this worth the opportunity cost of your time as a Director at Alibaba?”.

As I now reflect on these questions, I feel it’s all about the DNA of doing whatever it takes alongside founders. Long story short, the company pivoted successfully, crossing $1Mn ARR at high profitability. The business started throwing up so much cash that investors got multiples of their investments back via dividends, with founders also receiving significant cash-payouts, and deservingly so, for their grit & sacrifice. It didn’t become a unicorn or a household name but left everyone net-positive.

This experience left me with many operating learnings & a lifelong friendship with the founders, whose next company I have promised to back again. Even till today, I use the mental model from this investment while looking for both positive & negative leading signals in any new team I meet. I have no doubt this experience is helping me sow the seeds of future success.

After more than a decade of experience both as an institutional & individual investor, I have only now come around to accept my nature of not giving-up on people & companies that are struggling. It’s part of who I am and perhaps, my alpha as an investor.

I don’t know if this is the smart way to do venture investing or not, but I would like to leave you with this idea – fighting for the underdog companies will at the minimum, help you learn some valuable lessons & build your reputation as an investor that in turn, will create future value in more ways than you can imagine.

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Three unicorns & a VC

In my 1st year as a VC, I was fortunate enough to source 3 of the best enterprise startups built out of India over the last decade.

Reflecting on what these companies looked like before they became massive successes and the lessons that taught me about the best way to approach venture investing.

In my first year as a VC Associate in 2011, I started supporting a GP who was native to Chennai, already had some portfolio companies there and was informally leading coverage for the region. Naturally, I started visiting the city regularly and was perhaps one of the few VCs at the time who was spending significant bandwidth in the ecosystem there. And mind you, this is way before the city became the SaaS powerhouse it is today. I spent the most time in events around IIT Chennai, especially in the Rural Technology & Business Incubator (RTBI) there. This is the time when Zoho wasn’t a household name yet, and a few interesting startups like Stayzilla and Ticketnew had just started to emerge.

Candidly, I used to feel a little foolish every time I boarded the flight to Chennai. Was I just wasting my time by not covering Bangalore & Delhi? Which venture-backable company could I realistically hope to find in an IIT’s incubator, that too one which had the word “rural” in it? While my colleagues were neck deep in sourcing hot eCommerce deals from Tier 1 hubs, was I missing the boat by spending time with boring enterprise software & niche consumer Internet companies started by these humble, grinding-type founder personas?

What I didn’t know at the time was that meeting founders in an under-covered but growing hub like Chennai was actually a competitive advantage, a potential “edge” that was there to be leveraged. It led to me meeting two of the best enterprise software founders from the last decade, at a time when both companies were fledgling – Girish Mathrubootham of Freshworks and Umesh Sachdev of Uniphore. My guess is I was also one of the first VCs to ever meet them.

I met Girish during a really nondescript startup event in Chennai. He wasn’t even pitching there, and the organizer randomly introduced us after the event. I still remember Freshdesk had 25 beta customers at the time. I took the deal back to the senior team; we had one call with him but didn’t end up investing for a variety of reasons. Talk about missing the deal-of-the-century!

While meeting Girish was more serendipity, I give myself more credit for spotting Umesh. I was the only godforsaken VC who had built a deep relationship with the RTBI team at IIT Chennai. As part of one of my visits, the lead there introduced me to Umesh & Ravi. They were building Uniphore out of the lab there, with the active support & guidance of Prof. Ashok Jhunjhunwala. I don’t remember the exact traction they had at the time, but it was really early. They were building voice technology keeping rural/ vernacular use cases for India hinterland in mind, which was nicely aligned with RTBI’s mission.

While I didn’t get to interact much with Girish, Umesh and I spent a bunch of time together. I brought him in 2 times to meet the Fund’s senior team, once just before I was about to leave VC and move to the Bay Area. Fortunately, Uniphore didn’t become an anti-portfolio like Freshworks. One year after I had left the Fund in early 2014, it ended up investing in Uniphore. Cut to Feb’22, Uniphore raised a $400Mn growth round at a $2.5Bn valuation, becoming a trail-blazing Indian startup story of grit & perseverance.

As I write this, another similar story comes to mind. Again, in my first year of VC, I had a chance to meet Baskar Subramanian, co-founder of Amagi. This was the most non-intuitive play ever. At the time, Amagi’s flagship offering was a platform to insert regional, localized ads in popular TV programming. For example, say during a national TV soap telecast on Sun TV, viewers in Chennai & Coimbatore would see different vernacular ads of local brands from their specific locations.

If one went by the classic VC playbook of pattern matching, Amagi wouldn’t make it beyond the first meeting (perhaps why most funds passed on it at the time). The company’s existing market didn’t seem like it would support a venture outcome. On top of it, Baskar came across as the polar opposite of a typical VC-backed founder archetype. He was a bit nerdy, a bit fidgety, a bit unpolished around the edges but really smart & always with a big smile.

As expected, while the Fund passed on investing, two things stood out to me even then:

  • Amagi had signs of early product-market-fit in the use case it was going after.
  • Baskar and team were gritty, grounds-up entrepreneurs with a humble vibe, strong belief in their overall market thesis & the energy to play the long game.

Candidly though, I was still in my 1st year of learning the craft of venture investing & even though I caught these signals from 1st principles, I didn’t have the experience & chops to convert these signals into conviction & fight for the deal internally.

Cut to Nov’22, Amagi raised a $100Mn Series F from General Atlantic at a $1.4Bn valuation, with the company hitting $100Mn ARR! From its origins of inserting local TV ads in the Southern states of India, it has now become a global software platform for cloud broadcast & targeted advertising.

These and many other stories that I have experienced over a decade of early-stage investing, have taught me a valuable lesson – given the inherent randomness in outcomes, a terrible way to do venture investing is to be dogmatic. While frameworks, heuristics & pattern-matching do help evaluate deals more efficiently, you can’t become a slave to them.

Outlier venture outcomes typically come from unintuitive & unpredictable places. If one studies the history of the biggest wins in both public & private markets, they mostly emerge from “non-consensus-and-right” situations. Spotting these, by definition, requires an independent & radically open mind.

When Tim Ferris asked legendary VC Bill Gurley of Benchmark about why he thinks he missed investing in Google, Bill had a tremendously self-reflective response:

Essentially, Bill is saying that at the time, Google was the exact opposite of a classic VC template deal. And that’s exactly what should have pushed him to evaluate it more deeply as a non-consensus bet. In the words of my friend Nakul Mandan of Audacious Ventures – “the pedigreed, buttoned-down, big logo’d, all-bases-covered teams often end up generating a 1.5-2x return while the maverick, underdog, underestimated, headstrong, quirky founder ends up creating the 100x bagger”.

Marc Andreessen has a great expression around the optimal mindset for venture investing (also applies to starting a company) – “Strong opinions, loosely held“. I like to call it having a radically open mind while evaluating any opportunity. In my head, this approach includes:

1/ Turning over every rock to find deals.

2/ Not discounting any vertical/ space upfront, irrespective of general ecosystem biases.

3/ Not underestimating any founder, irrespective of age, pedigree, or track record.

4/ Trying to probe further when the gut feeling is positive but misaligned with VC thumb rules.

5/ Listening to co-investor feedback but making up your mind independently.

6/ Trying to imagine “What if everything goes right?”.

7/ Finally, getting super-excited when a company seems non-consensus.

This is the behavioral North Star I am chasing & where, I believe, the real Alpha in venture investing lies.

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Doing more with less

As an angel, one of the strongest leading signals I look for in a startup is progress per unit of capital – how much forward movement has the team achieved & the resources it has consumed for it.

My thoughts on why a capital-efficient mindset is so important for early-stage tech founders.

Having seen 1000s of deals across a decade of investing my own as well as institutional money, I rarely cringe while evaluating a new company. As an investor, I have often seen the same goods-and-bads in other deals several times before. As an ex-founder, I have walked the path & made the same unforced errors so almost every time, I can empathize & almost pre-empt why a founder is doing things a certain way.

However, there is one specific thing that is guaranteed to make me cringe – a founder attempting to raise an amount that is totally out-of-sync with where the business is. In many cases, this is accompanied by other precursors:

  • No intent to bootstrap from idea to “some” traction.
  • Wasteful handling of the last round.
  • Coding & building product for months at a stretch without putting anything meaningful in front of customers.

Personally, one of the strongest leading signals I look for in a startup is progress per unit of capital – how much forward movement has the team achieved & the resources it has consumed for it, especially when evaluated relative to other comparable startups.

I remember an interesting learning from my time at IDG Ventures (now Chiratae). Sudhir Sethi, the Managing Partner & the lead investor who had backed Myntra (Zappos of India at that time; was eventually acquired by Flipkart for ~$300Mn in 2014), often cited how when he went to meet Mukesh Bansal (the founder) for the first time at the Myntra office, he observed they were working out of a dingy space in a classic Indian neighborhood market with the ground floor occupied by a fruit & vegetable vendor. Sudhir used this as one of the positive signals for the team’s ability to execute in a cut-throat eCommerce vertical like fashion.

Fast forward a few years, and I got a similar insight yet again in the retail context. While working with Alibaba, I saw how frugal the Group was in terms of saving every dollar of operating cost. eCommerce works on wafer-thin margins, especially in highly competitive & price-conscious markets like Asia. And one could see this by comparing the bare minimum facilities & perks we got at the US HQ in San Mateo vs even well-funded growth startups, which were offering everything from catered meals to draft beer stations at that time.

Why is a capital-efficient mindset so important for early-stage tech founders? It’s because they are playing a game where the odds are hugely stacked against them. Where 9 out of 10 new startups fail on average. Where the starting point and end point of companies are vastly different, with each year choked with iterations, a major pivot every few years, and team members jumping on & off the ship.

Setting yourself up to have even a remote chance of winning such a game requires many shots at the goal, many course corrections, and many resets. At the same time, capital is scarce at the pre-PMF stages even for the best teams. Capitalism is brutally efficient, throttling money when relative risk is high, & opening the faucet once success is highly certain (typically post-PMF).

Building even a decently sized company can take anywhere from 6-8 years, & up to 15+ years. In such a long period, both the overall economy as well as your specific market will go through several cycles. The key is surviving long enough, even with limited capital, to be able to walk this arduous path.

This is what the best founders bring to the table – using investor capital like their own, each dollar wisely deployed towards only what’s truly necessary for the stage, raising each round with specific milestones in mind, and realizing that ownership is everything, with each bps of dilution being the costliest trade shareholders can make. To me, this mindset & building approach is perhaps the biggest signal of perseverance in a team.

Come to think of it, in the non-tech world where starting a business isn’t called “doing a startup”, entrepreneurs typically use their savings to get going, & once there is enough business confidence & profitable revenue flowing-in, grow using either internal accruals or debt. Initial bootstrapping creates skin-in-the-game, profitable revenue creates high confidence that customers want what you are making, & debt creates financial discipline around managing cash flows while preserving the founder’s ownership to compensate for all the risk they have taken.

This model has been used by everyone from Sam Walton to Richard Branson, & continues to survive in all parts of the SMB economy. While the venture capital model definitely works for building tech companies, which are asset-light, highly scalable & operate in winner-takes-all dynamics, I believe the founders who are in it for the long run build with a similar philosophy – planning for the next basecamp & raising conservatively, maintaining discipline around cash & giving high importance to ownership.

On a related note, I wanted to share something I recently wrote on Twitter regarding a fundraising pitfall specifically for serial founders:

Often see serial founders who have seen success before (scale and/ or exit), raise large rounds at high valuations at the idea stage!

From what I have seen, even the most successful founders have operated in phases where a lack of capital could have potentially killed their startup. That’s probably why on the 2nd attempt, they try and take that risk out of the equation at the beginning itself.

Oddly enough though, having a capital-rich Plan B to fall back on reduces the scrappy iterativeness, discipline & underdog mindset that startups usually need to succeed. And which probably contributed to their success the 1st time too.

In asymmetric bets like startups, to reference The Dark Knight Rises, “the way to climb out of the pit is without a rope”.

Hopefully, as this cycle resets, all of us founders & investors will go back to the drawing board & start appreciating Benjamin Franklin’s age-old virtue of frugality as a key to success in business & life.

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Conviction vs Randomness in Venture Investing

Photo by Nigel Tadyanehondo on Unsplash

Recently came across a fascinating Twitter thread from June 2020 by Dave McClure, ex-founder of 500Startups, where he talks about how “investing with conviction” is a myth. This tweet captures his sentiments well:

I agree with several arguments in this thread:

1/ Picking winners in early-stage investing is really hard. Power laws govern the best venture portfolios, driving down the hitting %. Per Horsley Bridge data, even for a top VC firm like Sequoia, ~4.5% of portfolio companies generate 2/3rd of aggregate returns.

2/ Intelligent venture investing, by its very nature, involves making both Type 1 and Type 2 errors. Therefore, even high-conviction deals are likely to exhibit unexpected outcomes, both positive & negative.

3/ There is a lot of hindsight bias in the way investor narratives are created around companies that turned out to be successful – “Look, I had high conviction on this deal & it turned out exactly as I expected. Ergo, I can predict the future”.

So in games like this where outcomes are random & often uncorrelated with the level of effort that goes in, does it make sense to discard the input process?

Based on more than a decade of venture experience, I tend to view it differently. I believe it’s still important to have a rigorous process of building conviction and to keep improving it bit by bit with each experience. Even though eventual outcomes might still be random, this approach helps tilt the playing field a little in your favor every time. Over a long enough time horizon, as one keeps taking more shots at the goal & with continuously improving odds, the hope is that a home run arrives sooner than later.

Particularly at the earliest stages (angel/ pre-seed/ seed), especially with the advent of small check investments ($1-5k via syndicates/ SPVs) attracting a new generation of 1st-time investors, it’s easy to assume that outcomes are randomized & therefore, fall into the trap of doing spray-and-pray that isn’t backed by an intelligent investment process.

It’s important for new angels to first deeply study the asset class & build their personal investment process – areas of expertise, focus sectors, stages, target founder persona, deal flow engine, unique value-add to get into best deals etc. Post which, the odds of success are significantly better.

While being a champion of a “conviction-building” investment process, I also agree with the 3 takeaways that Dave closes the thread with, regarding having enough shots on goal:

Even with the most intelligent investment process, venture investors need to acknowledge their limited picking ability & therefore, keep taking enough intelligent shots at the goal for the odds to work in their favor. Semil Shah of Haystack wrote a great post titled “Shots on Goal” on this idea a while back.

Equally important as portfolio diversification via numbers, is making asymmetric investments – ensuring that the few winning bets have huge outcomes so that even with a high loss ratio, the returns math still works at the portfolio level. The smartest thing a venture investor can do is to befriend the power law, and work towards being on the right side of it!

To summarize, acknowledging the randomness of venture outcomes doesn’t need to be at odds with running a rigorous & continuously-evolving investing process. In fact, such a system should be intelligently designed to account for this randomness, combined with other considerations like power laws, compounding, economic cyclicality etc. Even a few points of “edge” that is systematically created with each experience, can slowly accumulate into a sizable alpha over the long term.

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The futility of Plan B

Image Source: LinkedIn

Growing up in India, where inherent chaos makes sure most things don’t go according to plan, I got organically trained to always have a Plan B. The classic fallback option – the bylane you take when the main road is clogged because a minister is scheduled to pass through, the backup college seat you block in case you ranked low in the entrance exam for your top preference, or the autorickshaw you hail when the car refuses to start.

Look, I get it! Now that I am a father to 2 boys, I see the instinct parents have to ensure their children are tangibly & emotionally “safe” in all situations. So, I can appreciate why my middle-class upbringing was designed this way. To top it up, my technical education & early analytical jobs further pushed me into the world of scenario analysis & fail-safes.

Down the road, as I entered the risky world of startups, I naturally brought this instinct with me. While building, operating & investing in high-risk-high-reward endeavors, my animal brain would always push me to have a Plan B in my backpocket:

  • If this startup doesn’t work, I can always go back to Company X.
  • What if this investment fails? Let me spread my resources & take a smaller bet.
  • If I don’t like living in Country Y, I can always go back to India.

A few years into taking these asymmetric bets (presumably backed by Plan Bs), I expectedly started encountering failures, both big & small, one after another. They ranged everything from major projects going South & unforeseen external risks coming to the party to unexpected company restructurings & gross misjudgment of certain people’s skills & intent.

During a recent introspection of these adverse experiences, something interesting jumped out – every time I attempted to call on a Plan B for a specific situation, more often than not, it wasn’t really there. In some cases, the “backup” companies had changed their strategy & weren’t a fit anymore. In others, I had grown in a different direction & going to a fall-back option would be a negative step. Many times, people I was relying on to help materialize a certain Plan B had either fallen out of touch, were themselves dealing with adversity, or had changed their context & therefore, relevance.

So this was my lightbulb moment that inspired this post – in high-risk-high-reward situations, Plan Bs are….fictitious. The very nature of extremely risky situations is that they take you in unpredictable directions, change your context in unimaginable ways & leave you with baggage that’s hard to foresee. And all this happens in parallel to a rapidly-changing external environment that in most cases, becomes increasingly incongruent with your endeavor (most asymmetric projects are by definition, contrarian in relation to established rules of the game that the majority operates by).

This complex system renders even the most thought-through Plan Bs useless. Given asymmetric bets are driven by power laws (a few will drive a majority of the total outcome) & compounding (need a long enough timeline for ideas to mature, which is when outcomes start growing exponentially), positioning yourself to be on the right side of these rules requires going all-in for a significant period of time.

While having a Plan B provides the initial psychological space to initiate a risk, in my experience, it unfortunately also creates a mental mechanism to cop out of it, & even worse, often doesn’t provide the safe landing space it initially promised.

Going forward, my aim is to ditch the “Plan B” mindset in all asymmetric bets. A fall-back instinct comes from a place of fear, and while controlled fear can be a useful tool to drive alertness & urgency, it becomes adverse when acting as a roadblock to going all-in & persevering on a thoughtfully-chosen path.

It’s important to add here that while ditching the Plan B outlook, I will still proactively focus on avoiding the Risk of Ruin at an overall life level. Asymmetric bets require multiple shots at the goal & therefore, safeguarding the ability to keep playing is paramount.

On a related note, a mental heuristic I have recently started using while making asymmetric decisions I am 50-50 on – “which option is the fear side of my brain asking me to choose?”. In most cases, I then lean towards the other option!

I have found the following quote by Swami Vivekananda to be hugely inspiring in driving this mental transformation:

Take up one idea. Make that one idea your life – think of it, dream of it, live on that idea. Let the brain, muscles, nerves, every part of your body, be full of that idea, and just leave every other idea alone. This is the way to success.

Swami Vivekananda

As you consider this approach, I want to leave you with this outstanding scene from Christopher Nolan’s ‘The Dark Knight Rises’. As a frustrated Bruce Wayne is trying to catch his breath after yet another failed attempt at climbing out of the pit (he was using a rope each time), an old & wise prisoner gives him the mantra for successfully making the climb:

You do not fear death. You think this makes you strong. It makes you weak.

How can you move faster than possible, fight longer than possible, without the most powerful impulse of experience – the fear of death!

Make the climb…as the child did. Without a rope!

The Dark Knight Rises (2012)

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