Tag: Valuation

  • Venture Math

    Venture Math

    Creative ways to hide financial engineering

    A rough example of the logic driving investment decisions amongst the most degenerate venture investors:

    1. You’re evaluating a company with $7.5M ARR
    2. $5M is net new ARR, annual burn is $10M
    3. That’s a 2x burn multiple (BM)
    4. You invest $30M at a market-rate of 20x ARR
    5. Assuming 2x BM, $30M produces $15M in net new ARR
    6. At 20x ARR, it gets marked up from $150M to $450M

    On paper, that checks all the boxes: an investment that was subsequently marked up 3x using logic that could be decoded on an iPhone calculator.

    Indeed, the role of multiples is to produce calculations that are easier and faster; to get deals done and put capital to work.

    There are two major flaws with this approach:

    The first is that multiples are backwards-looking. By applying to current revenue or burn, they rely on past performance. All assumptions about the future are squashed down into the multiple itself. Venture capital relies on making good judgements about the future, not the past.

    The second is that multiples assume that all revenue is created equal. They ignore unit economics and capital expenditure, and nor do they fully appreciate churn. Finally, and particularly relevant today, they encourage founders to engage in creative accounting to boost ARR.

    “We’ve actually come back to saying there’s a real advantage to seeng the GAAP revenue accounting, to make sure all the money is showing up for real.

    There’s a lot of noise in that multiple, and when they were all SaaS recurring revenue businesses ā€” all seat based, all 90% or 80% gross margin with no CapEx, all enterprise sales with low churn ā€” it absolutely made sense. You could compare two companies. Thats’s why by 2019 or 2020 it almost felt like ‘fill in the form to give me the valuation’.

    None of those conditions are true now.”

    Rory O’Driscoll, Partner at Scale Venture Partners

    Consider, for example, the venture capitalist’s typical disdain for discounted cash flow (DCF) style thinking in valuation: There are too many assumptions, the future is too uncertain.

    So, instead, they price with ARR multiples, which include all of the same assumptions about the future, but obfuscates them into simple calculation. Out of sight, out of mind.

    “Some investors swear off the DCF model because of its myriad assumptions. Yet they readily embrace an approach that packs all of those same assumptions, without any transparency, into a single number: the multiple. Multiples are not valuation; they represent shorthand for the valuation process. Like most forms of shorthand, multiples come with blind spots and biases that few investors take the time and care to understand.”

    Michael Mauboussin, Head of Consilient Research at Morgan Stanley

    Indeed, multiples are a popular tool precisely because they hide all of that detail. Remember, venture capital is (unfortunately) a game of building confidence with simple stories, not demonstrating competence with complex truths.

    Financial engineering built on multiples is the bedrock of venture capital’s creeping financialisation.

    Imagine you invest $20 in a company that generates $4 in ARR from each customer, with a CAC of $20. It trades at a multiple of 20x ARR.

    • In practice, that company is losing $16 on every customer in the first year, with payback over 5 years assuming no churn.
    • On paper, every $1 into the company produces $4 in marked value for the investor. It’s a great looking investment.

    This is precisely the mechanic which incentivises insane capital consumption on negative unit economics. Investors trade financial health for faster markups, knowing that it’s a bust if the environment shifts.

    “Guess what happened once Founders realized that VCs were valuing startups using revenue multiples? They started playing a game of Hungy Hungry Hippo with the goal of accumulating as much revenue as they could!”

    Frank Rotman, Co-founder of QEDInvestors

    “When market turns, M&A mostly stops. Nobody will want to buy your cash-incinerating startup. There will be no Plan B. VAPORIZE.”

    Marc Andreessen, Co-founder of Andreessen Horowitz

    To quickly round-out a few points, lazy thinking with multiples…

    • …biases venture capital towards business that generate revenue quickly, which led to the neglect of deep tech.
    • …promotes pushing companies to scale as quickly as possible, which produces worse outcomes for everyone.
    • …contributes to VCs losing the ability to build independent conviction, encouraging herd-behavior.

    In conclusion, multiples are a tool for quick comparison across peers. Not for pricing, and not for understanding performance or potential of a startup. They include far too many important and unchecked assumptions, limiting an investor’s understanding of the specific future of a company.

    Proper valuation, with multiples used as a sanity-check afterwards, is the way.

    “We often pursue this kind of rationalization as a spot check, generally after going through the valuation process. When the multiple is implied, investors will then compare it to others seen in the public and private markets to get more comfortable. Think of it like a gut check, a way to determine if the valuation feels ‘reasonable’.”

    Alex Immerman, Partner at Andreessen Horowitz, and David George, GP at Andreessen Horowitz

    (top image: “The School of Athens“, by Raphael)

  • What is Valuation

    What is Valuation

    Whether you’re investing in mature companies in the public market, or fast-growing startups in the private market, one question separates good and bad investors:

    Do you understand valuation?

    Valuation is the rationale by which you determine which opportunities to pursue. To develop your understanding of valuation is to develop your ability to recognise potential.

    Despite the central role in investment decisions, valuation is often misconstrued as financial engineering or market-driven pricing exercises.

    Valuation is an opinion

    Here’s three things valuation is not:

    • Based on verifiable inputs
    • Provably accurate in output
    • A mirror of market sentiment

    Instead, valuation is always an opinion based on a set of assumptions about an unknowable future.

    “People act like itā€™s an award for past behavior. Itā€™s not. Itā€™s a hurdle for future behavior.”

    Bill Gurley, VC at Benchmark

    Whether that valuation is based on a detailed DCF model or napkin-math, it’s an opinion. And it’s no more or less of an opinion as your process gets more or less sophisticated; the only difference is how clearly you outline the assumptions.

    When one investor states that a company is overpriced, and another that it is undervalued, neither is right or wrong in the moment ā€” they just have differing opinions.

    Valuation can be a simple, implicit part of the process, or it can be an explicit exercise used to better understand an opportunity and check assumptions.

    Valuation is an opinion on a story

    In order to form an opinion about a particular future, you must first listen to its story.

    “The value of a stock is what people believe it is and could be. A stock is a story.”

    Lulu Cheng Meservey, Founder of ROSTRA

    All investment decisions are bets on today’s fiction.

    • Elon Musk is telling you that we must get to Mars
    • Brian Armstrong is explaining the importance of Bitcoin
    • Parmita Mishra is describing the future of medicine
    • Aaron Slodov is laying out a reindustrialisation roadmap
    • Augustus Doricko is talking about rivers in the sky

    Do you believe them, when they have nothing but a story?

    Does that story involve unleashing a huge amount of economic energy? How much capital does it require?

    Based on the credibility of that story, and the potential scale of that economic energy, is it worth paying-up today?

    “The scarcest resource isn’t capital or talent. It’s the ability to make people believe in your specific tomorrow strongly enough to fund it today.”

    Howard Yu, LEGOĀ® Professor of Management and Innovation

    Valuation is the art of developing better opinions about the future

    Valuation can be broken down into a few pieces:

    • How do you judge the credibility of a story?
    • How do you estimate the economic potential of a story?
    • How do you estimate the risk associated with a story?

    You can think about this via two extremes:

    1. You’re looking at a company you’re familiar with. You’ve got a good mental model of the industry, the technology, the market forces, trajectory, and risks. It’s relatively simple for you to make a rough judgement on value in your head. This reflects Kahneman’s “System 1” thinking.
    2. You’re looking at a company you have no familiarity with. The technology is novel, the market is emerging, and there’s no real precedent. In order to make a good judgement, you have to submerge yourself in details and scenarios. This reflects Kahneman’s “System 2” thinking.

    In the latter case, a more sophisticated valuation process can help you understand the credibility and economic potential of a story. It provides a framework for ingesting information that can control biases, while allowing you to recognise and scrutinise the main drivers of value.

    Valuation is essentially the act of running simulations of the future described in a story, focused on the numbers rather than the narrative, to explore the potential.

    Pricing is not valuation / Trading is not investing / The present is not the future

    Venture capitalists often choose to focus on relative pricing, instead of valuation, as an attempt to proxy experience through crowdsourced activity ā€” allowing for speedy “System 1” style investment decisions.

    This means analysing industry activity, which biases investment towards categories with low information friction like B2B SaaS, at a cost to sectors with more idiosyncracy, like deeptech.

    Unfortunately that focus on market data also means these investors are not developing their ability to make judgements about the future, only to pattern match today. This compounds into a ‘knowledge worker atrophy‘ problem, weakening venture capital’s institutional competence at funding creative endeavors and novel solutions.

    That would appear to be a critically weak link in the value proposition of venture capital, and the premise that it funds important solutions to humanity’s problems.

  • Risk Capital

    Risk Capital

    The history of human progress is predicated on the history of efficient risk capital formation.

    WIll Manidis

    The story of venture capital (and its precursors) is a story of risk. You can take this back as far as you like, from ARDC to Christopher Columbus. From whaling expeditions to space exploration.

    Risk is the product.

    And, essentially, it boils down to this calculation:

    The merit of any investment depends on whether the probability of success multiplied by the forecasted return is greater than the cost.

    • Investments that are perceived to have a high probability of success attract a lot of competition.
    • Investments that are perceived to have a low probability of success attract very little competition.

    Venture capital is at the far end of this spectrum, where the ‘skill’ is in recognising when the market has mispriced risk because an idea is unconventional rather than bad.

    This brings us to the first category of risk in this conversation: idiosyncratic risk.

    Idiosyncratic Risk

    (the specific risk of an investment)

    Idiosyncratic risk reflects the specific potential of an investment: the probability of success, and the assumed return if it is succesful.

    Assuming you cannot change the probability of success or the assumed return, there are two ways to handle idiosyncratic risk:

    • Making low probability investments profitable by diversifying away total failure.1
    • Making low probability investments profitable by pricing the risk appropriately through valuation.

    These are the two main levers of venture capital, which is focused on what Howard Marks refers to as uncomfortably idiosyncratic investments:

    The question is, do you dare to be different? To diverge from the pack is required if youā€™re going to be a superior in anything. Number two, do you dare to be wrong? Number three, do you dare to look wrong? Because even things which are going to be right in the long run, maybe look wrong in the short run. So, you have to be willing to live with all those three things, different, wrong, and looking wrong, in order to be able to take the risk required and engage in the idiosyncratic behavior required for success.

    Highlights from a conversation with Howard Marks

    Idiosyncratic risk contrasts with the other main category of risk that investors must consider: systematic risk.

    Systematic Risk

    (broader market-related risk)

    If idiosyncratic risk is typified by venture capital, then systematic risk is typified by index funds. Consider the extent to which index fund performance is influenced by individual companies versus major political or economic events.

    Nevertheless, systematic risk is a consideration in venture capital, and there are two ways to handle it:

    • Avoid consensus, where competition drives up prices without increasing success rate or scale.
    • Avoid market-based pricing, where macro factors can drive up prices without increasing success rate or scale.

    Exposure to systematic risk essentially destroys an investor’s ability to properly manage (and extract value from) idiosyncratic risk.

    Alpha vs Beta

    If we consider idiosyncratic risk as the source of ‘alpha’ (ability to beat benchmarks) in venture capital, systematic risk reflects the ‘beta’ (convergence with benchmarks).

    A striking shift in venture capital over the last 30 years, particularly the last 15, is the extent to which the balance has shifted from idiosyncratic risk to systematic risk. This is a consequence of prolonged ‘hot market’ conditions, where consensus offers a mirage of success.

    Consider a typical VC in 2025. They’re likely to be focused on AI opportunities, guided by pattern-matching and market pricing (aka, “playing the game on the field”). Investing, in this scenario, is reduced to a relatively simple box-checking exercise.

    All of this implies significant systematic risk; the firm is riding beta more than they are producing alpha. This creates extreme fragility.

    Systematic risk has always been a concern, but it has been amplified in recent years by cheap capital and social media. The herd has grown larger and louder; more difficult for inexperienced or insecure investors to ignore:

    • Taking systematic risk means following the crowd. It’s an easier story to sell LPs, and there’s less career risk if it goes wrong as accountability is spread across the industry.
    • Taking idiosyncratic risk means wandering freely. It’s tough to spin into a coherent pitch, and there’s more obvious career risk associated with the judgement of those investments.

    Despite mountains of theory and evidence supporting idiosyncratic risk as the source of outperformance, it’s just not where the incentives lie for venture capital.

    The Jackpot Paradox

    There are fundamental consequences of the drift towards systematic risk in venture capital:

    • The muscles of portfolio construction and valuation atrophy, as consensus-driven ‘access’ dominates behavior and idiosyncratic risk falls out of favour.
    • The typical ‘power law’ distribution of outputs collapses as few genuine outliers can be realised from a concentrated pattern of investment.
    • As returns converge on a mediocre market-rate, investors manufacture risk by feeding power law back into the system as an input, trying to create outlier returns.
    • Success is further concentrated in a system that becomes increasingly negative sum overall.

    This broadly summarises where we’re at today. A disappointing scenario that represents failure to the actual bag-holders on the LP end, failure to founders, and failure to innovation.

    A lot of the blame falls in the lap of LPs. The low fidelity interface with GPs means that LPs have a general bias towards compelling stories which invite systematic risk.

    Thus, venture capital is reduced to a wealth-destroying competition for access to the hottest deals, fundamentally at odds with the concept of ‘uncomfortably idiosyncratic’ risk and generating alpha.

    Note 1: While idiosyncratic risk can be managed through diversification, diversification doesn’t necessarily produce greater systematic risk.

    Note 2: Another way to look at the ‘venture bank’ versus ‘venture capital’ paradigm is that venture banks are deliberately set up to embrace systematic risk.

    (image source: Rembrandt’s “Storm on the Sea of Galilee”, used on the cover of “Against the Gods: The Remarkable Story of Risk” by Peter L. Bernstein.)

    1. Though this is deliberately not a post about portfolio construction, which I have written about too much already. [↩]
  • Venture Capital’s ‘Knowledge Work’ Problem

    Venture Capital’s ‘Knowledge Work’ Problem

    While GenAI can improve worker efficiency, it can inhibit critical engagement with work and can potentially lead to long-term overreliance on the tool and diminished skill for independent problem-solving. Higher confidence in GenAIā€™s ability to perform a task is related to less critical thinking effort.

    source: The Impact of Generative AI on Critical Thinking

    This article is broken down into five segments:

    1. Priorities in venture capital
    2. The importance of cycles
    3. Forcing a reset
    4. The ‘knowledge work’ problem
    5. Operating from strength

    Priorities in Venture Capital

    In colder markets, founders just need capital on reasonable terms, and it doesn’t really matter where it comes from. Value-add propositions and brand strength are less important; access to hot companies doesn’t move the needle as much for LPs. Instead they care more about differentiation through strategy.

    In hotter markets, the opposite is true. Investors will be chasing the fastest growing companies in the most attractive categories, out on the thin ice of excess risk. LPs, sold the same dream, care only about how GPs can parlay their way into those deals. How you invest is irrelevant, what matters is your network and your brand.

    Strangely, at the peak things begin to come full circle. In 2021, when there the incredible amount of capital was spread across a record 1,594 firms, there was a horseshoe effect: with such abundant opportunity for investment, LPs and VCs once again saw the opportunity in strategy-driven alpha.

    The Future of Venture Capital Early signs of disruption suggest how the industry may be impacted

    In normal circumstances, the next stage of this cycle is the crash. The firms that leaned the hardest into chasing heat would be the most exposed, with portfolios that are the most obviously out of alignment with value. What’s left are the firms who chose to focus on solid strategy, who can begin harvesting deals in the down market.

    In 2022, this shift was derailed by the emergence of venture banks, designed to escape the typical cycles of venture. The largest firms raised the most capital in subsequent years. Access remained an important part of the story for LPs, especially with the convenient rise of AI.

    In fact, you could argue that this was the second time that cycle was disrupted, as many experienced investors called the top in 2016-2018 only to be thwarted by COVID. Two years of intense, irrational enthusiasm for digital only exacerbated the problem.

    The Importance of Cycles

    Consider how much of the natural world has evolved alongside fire. Wildfires serve an important purpose in preventing ecosystems from choking themselves to death on redundant biomass, and there are even species that have evolved to use fire as a mechanism to spread their seeds.

    Humanities view of fire as a threat, and the goal of suppressing it entirely in the natural environment, has had disastrous consequences. We have seen the emergence of ‘mega-fires‘, where biomass accumulates to the point where spread is fierce and inevitable.

    There are clear parallels here in venture. The extent to which the market is suffering today is proportional to the amount of time it took to hit a correction. What’s worse, for reasons described above we haven’t yet really allowed the full cycle to complete.

    Forcing a Reset

    While venture banks steam off into the distance, and venture capital tries to figure out how to navigate this environment, there are three signs of change.

    • Increasingly, there’s talk of smaller LPs like family offices looking to pursue direct investing strategies. In theory, this affords them a similar level of risk with better economics, but questions remain about their bandwidth to do this properly.
    • There’s been a surprising number of high profile GP departures, both launching their own funds and not. In many cases, this means partners are giving up wharever carry incentive they had. This suggests some discomfort in the status quo.
    • An increasing number of founders talking about bootstrapping or ‘seedstrapping’ (one and done fundrasing), or other strategies to avoid the problems assocaited with getting on the venture capital treadmill and the expectations involved.

    For the GPs that remain, it’s time to consider what the world would look like if the cycle had completed. How would they be forced to act in a truly ‘down market’ environment. Indeed, if you consider that many smaller firms have been priced out of AI, that may already feel like their reallity.

    It is clear that the bar for performance is significantly higher in a cash constrained environment with higher interest rates. While that may not change the reality for venture banks, it is existential for traditional venture capital.

    The ‘Knowledge Work’ Problem

    In hot markets, where investors take a prescriptive approach to investment, there is a huge problem with atrophy. Completely separate to the poor investments that come out of these periods, it’s also worth examining the practices they establish.

    Investors that spend all of their time chasing hot deals based on a number of set criteria have the same basic problem as knowledge workers that rely on Generative AI solutions: they are not using their critical thinking muscles. Executing orders, not problem solving.

    Consider how little actual thinking you have to do about an investment if your process is focused on second-order factors. Is it on an a16z market map, is it on YC’s Request for Startups, are other “tier 1” investors are in the round? Will downstream investors will give you the markups you need, and will LPs will be excited about it?

    This behavior, geared towards capital velocity, is focused on second order information and pattern matching. It is a prescriptive approach that informs what gets investment, displacing the first-order considerations about things like team, opportunity, valuation, market and strategy.

    This dissertation focuses exclusively on moral hazard, which refers to a venture capitalistā€™s propensity to exert less effort and shirk their fiduciary duties to the investors to maximize their self-interest; specifically, a VCā€™s propensity to choose subjective selection criteria over more cognitively taxing objective criteria when faced with multiple options and fewer resource restrictions.

    “Venture Capitalistsā€™ Decision-Making Under Changing Resource Availability”, by Noah John Pettit

    While this approach might broadly work for venture banks, with an army of low-impact investors looking to index across new technology trends, it will not deliver the returns required by the traditional venture model.

    Operating from Strength

    The contrary to prescriptive investing is quite literally the hunt for outliers. Backing illegible companies. Being consensus averse. Resisting what have been the loudest models.

    This might sound like cowboy investing. A Rick Rubin-esque vibes based approach to venture capital. It certainly can be, and if you happen to be Rick Rubin it might just work ā€” but why take the risk?

    The way for these investors to operate from a position of strength is to build process alpha. That is, do everything you can to prevent being wrong for predictable reasons (controlling for bias), and to manage the risk of being completely wrong a lot of the time (portfolio construction). Not to overintellectualise investment decisions, but to give yourself the strongest foundation to embrace the risk of uncertainty.

    To take the analogy a bit further, for all that Rick Rubin is a total eccentric, guided by his own taste without the need for external validation, he is not cavalier about it. He pays immense attention to environment and routine in order to help him get the best return on his time.

    There’s never a need for investors to stray from this disciplined mode of operation, it just so happens that most are prey to the cycles of venture capital and the temptation to inflate fees when opportunity arises.

    Discpline is easy when opportunity is limited.

  • The Rot of Short-Termism in VC

    The Rot of Short-Termism in VC

    Venture capital is a seriously long-term game, with investments taking somewhere between 8 and 16 years to return liquidity.

    The distance to that horizon creates a lot of eccentricity.

    For example, VC does not reward following patterns or navigating market movements, neither of which is relevant to decade-long cycles. Consensus of pretty much any kind is toxic, as the more people agree with something the less profitable it becomes. Investment experience is like comfortable entropy, slowly eating-away at your ability to remain objective.

    In a sense, success itself is antimemetic: the better the outcome of an investment, the more likely you are to try and repeat it through pattern matching ā€” destroying the calibration which allowed you to find it in the first place.

    Can you imagine how maddening that is?

    This is why the best GPs are oddballs. They live with the paradox that being a ā€˜good investorā€™ is a process of constant discovery, and the more lost you feel the better you are probably doing.

    It takes a certain madness to do well, and that is not something you can pick up on the job. You cannot be taught how to think in a contrarian manner. Nobody can give you the confidence required to wait a decade to see if you have good judgement. You have it, or you donā€™t.

    This is why great VCs earn a lot of respect. The role they play in financing entrepreneurial dreams is critical. From the semiconductor origins of Silicon Valley to SpaceX and our future on other planets, someone had to be there to write the check.

    If the incentives were well aligned, thatā€™s where this story would end ā€” as a fan-letter to weirdos. VC would remain a cottage industry investing in wacky stuff, offering strong returns for LPs.

    Unfortunately, that is not the case.

    Over the past decade we’ve seen the emergence of a new type of VC: one who moves between trends with the swagger of a heat-seeking missile, investing as if their money might go bad. This behavior is contrary to pretty much everything that we know about venture capital, and yet the trend has only accelerated.

    To understand why, we have to look at VC compensation:

    The ā€˜2 and 20ā€™ structure of VC compensation is pretty well understood and has remained unchanged for a long time: You get 2% of the fund per year in ‘management fees’ to pay your bills and support portfolio companies, and 20% of ‘carried interest’ as a share in any profits made.1

    For people passionate about the outliers, carried interest is the hook. Secure enough big wins and you can make a vast amount of money, in contrast to management fees which aren’t exactly lucrative for a small fund. It’s also nice that carried interest aligns success of the firm with success of the founders.

    However, as capital flooded into private markets over the last couple of decades, and exits took longer to materialise, some cunning individuals recognised an opportunity: the 2% is guaranteed, independent of performance, and it is possible to ā€˜hackā€™ venture to maximise that income.

    You can do things the old fashioned way, raising (for example) two $100,000,000 funds in a ten year period, with the implied annual income of $4,000,000. Alternatively, you can squeeze three funds into that period, at double the size, and scale your income to a mighty $12,000,000. All without really needing to worry about underlying performance.

    To build that second scenario, you need to do three things:

    • Invest in the most overheated, capital-intensive industries, which allow you to justify raising and deploying larger funds ever more quickly. These industries are also an easy-sell for LPs, who want something to talk about at dinner parties.
    • Systematically undermine the understanding of valuation by promoting crude and illogical practices, and calling people nerds if they say things like “free cash flow”. Venture is a craft, not a science ā€” which basically gives you carte blanche, right?
    • Pour capital into brand and status building for your firm, which LPs love. Celebrities, political figures, impressive offices, big events… Anything that shows them you’re a serious institution (with the perks that entails) and not some garage-band firm.

    Instead of looking 8 to 16 years in the future with your portfolio, you want to focus on the next 2 to 3 years in order to align with your fundraising cycles. You want companies that are likely to grow in value rapidly in the near future, so hype and consensus are powerful allies.

    The aim is to invest in a company at Seed and propel it to a Series A within 2 years at a 4-5x markup, which ā€” if you can repeat it often enough ā€” will look great to LPs. If they ask about DPI just talk about how the IPO markets should open next quarter next year.2

    It doesn’t even matter if you don’t think your portfolio companies are attractive investment with that markup, as there’s no obligation to participate. You have the growth on your books to help you raise the next fund, and some compliant downstream bag-holders, that’s all that matters.

    You can even build this strategy into how you price deals. Rather than try to objectively value the business, just tell founders to think about what a reasonable Series A price would look like for them, and then divide it by 3 for the Seed. That way, you’ve got the expectation of at least a 3x markup already built-in to the investment!

    You want to make sure the heat persists, to ensure prices at later stages remain frothy and your markups get better and better. So consider a bit of thought leadership to keep interest on your chosen sector. As long as LPs believe the hype, and keep investing in other funds on that theme, capital will keep piling in. Amplify that market momentum as much as possible. Volatility is your friend, and over time it can even help you wash out smaller managers that offer an unfavourable comparison on performance.

    Obviously the actual investment returns from this strategy are likely to be terrible, unless you’ve somehow timed another ZIRP/2021 exit phenomenon and can unload all of your crap on the public markets just before the music stops. It doesn’t really matter, because the median return in VC is so poor that you might just luck your way into top quartile anyway. Keep the paper marks strong, keep bullshitting LPs about the market conditions and the insane potential of whatever it is you are investing in, and you can probably keep buying back in with a new fund.

    It’s going to be toxic to founders, as they watch huge piles of capital being incinerated chasing hype instead of genuine innovation.

    It’s going to be toxic to innovation, as founders increasingly choose to pursue ideas that they think VCs will back, rather than real passion projects.

    It’s going to be toxic to VCs, as good practices around markups, pricing and portfolio management are ditched in favour of capital velocity and short-term incentives. It’s already frighteningly clear how much basic investing knowledge washed out of VC during ZIRP.

    It’s going to be toxic to LPs as already pretty shitty performance metrics for venture capital get even worse.

    1. The management fee is often frontloaded and scales back after the investment period. The 20% carried interest may also have a hurdle rate (e.g. 8%) which guarantees some return on investment for LPs before they split profits with the VC. [↩]
    2. It might not matter though, as many institutional LP allocators collect their bonuses on markups, so their incentives are totally aligned with yours. They’ll probably have moved on to a new job in a few years anyway. [↩]
  • Adverse selection and venture capital

    Adverse selection and venture capital

    Thereā€™s a weird phenomenon among VCs where the less successful they are, the more evil they become to founders to squeeze more money out of their best startups out of necessity which then becomes a vicious cycle of adverse selection.

    Garry Tan, President & CEO of Y Combinator

    Including the above, criticism of venture capital often applies a fairly broad-brush, which might feel unfair. 

    If you look a little closer, you’ll see it’s actually a problem of venture capital’s own making. An identity has emerged over the last decade which feels like an attempt to homogenise the asset class. This has been characterised by gatekeeping, consensus seeking, exclusionary behaviour, protectionism of networks and relationships, determining the ā€˜in-groupā€™ and then restricting access to it.1

    This identity appears at the core of venture capital, thanks to the gravitational effect of extreme insecurity: with so little in the way of transparent standards, particularly on measuring performance, most managers look for implicit validation from their peer group. They adopt the same attitude, use the same jargon, invest in the same categories, and follow the same practices.2 

    Toxicity seems to be compensation for insecurity in our industry. Itā€™s not good.

    Eric Bahn, Co-Founder & GP at Hustle Fund

    Unfortunately, that group is clearly a negative force, having a chokehold on the public image of the asset class and an unfortunate influence on the overall returns.

    Adverse Selection

    If you follow finance and economics, you will be familiar with the problem of adverse selection. For those that arenā€™t, here a rough summary of the explanation from Nobel winning economist, George Akerlof, and his famous paper, ā€œThe market for lemonsā€:

    Buyers in the used car market arenā€™t typically mechanics, so struggle to judge whether their potential purchase is in good shape or a bucket of rust with a new paint-job.

    This imbalance of information between buyers and sellers creates a reluctance to ever pay full price – until eventually everyone selling good cars is driven out of the market.

    To apply this to venture capital: you have a category of managers who deal with their performance anxiety by blending into the herd – aiming for consensus, not excellence. The ones who smirk when managers set ambitious targets, despite that being the name of the game.

    These managers are the buyers in this analogy, hedging their bets out of uncertainty in their own ability, benchmarking against averages, and ultimately degrading the whole asset class. 

    Feedback Loops

    Iā€™ve written at length about why standards for measuring performance in VC are important, and how that could be addressed. But why does it matter, and what do we mean when we refer to insecurity amongst managers?

    For this, thereā€™s no better analogy than The Monkey Problem, which I believe is credited to Astro Teller, Captain of Moonshots at X:3

    Imagine you tell 100 people that their goal is to have a monkey on a pedestal reciting Shakespeare, 100 days from now. They know that you might check up on them along the way, and are concerned about demonstrating their progress.

    The first thing everyone is going to spend time on is finding or making the most impressive pedestal, because that is the most attainable and demonstrable sign of progress – even if it is trivial compared to teaching the monkey. 

    In venture capital, the pedestal equivalent is the logo hunting, where managers will seek to invest in hot deals, or invest alongside ā€˜tier 1ā€™ firms, in order to have those logos on their LP updates. Itā€™s a superficial sign of ā€œprogressā€, and has no direct relation to the real goal of generating returns. They donā€™t really know how well they are performing on those terms, and they canā€™t really compare themselves to their peers.4

    Turns out, when youā€™re building a venture firm truly from scratch (limited track record, no Ivy, didnā€™t work in venture prior, etc.), logos + investing alongside name brands matter far more than anything else.

    Eric Tarczynski, Founder and Managing Partner at Contrary

    Monkeys and Lemons 

    To join the two together: the monkey problem creates the information asymmetry (inability to understand fund performance) which results in the lemon problem (the drift towards measuring manager performance via relationships and how well they fit the stereotype).

    As a result, thereā€™s increasing gravity around that ā€˜in-groupā€™ network of VCs, and fitting into those patterns of behaviour and identity. Itā€™s that group which becomes the subject of so much (often deserved) criticism, and the target of parody. 

    Managers who do not identify with this group are de facto not the target of that criticism. They are secure enough in their ability to not need to adopt the superficial signals of competence. Through their implicit understanding that venture capital is precisely not about fitting a pattern, they are likely to outperform those that follow the herd. Unfortunately they often face an up-hill struggle when raising successive funds. 

    This has a deeply concerning impact on the performance of venture capital, and the quality of ventures they back, as well as the diversity of founders and ideas that will be funded.

    VCs may subconsciously be looking for founders who share similarities with themselves and may not be able to effectively assess founders who have exceptional but different qualities.

    Nnamdi Okike and Aaron Holiday, of 645 Ventures

    The solution to this, going back to the root of this problem, is to focus on the monkey.

    Every stakeholder in the process, from founders to LPs, need to be clear that their responsibility is generating returns. There needs to be a real shift towards making and measuring returns, rather than assigning value to relationships and hype.

    Specifically, for an informative approach with practical feedback windows (quarterly or annual, rather than decennial), that requires making TVPI a meaningful metric through standardised methodologies and transparent reporting.

    This is never going to happen without some kind of broad industry consensus, which in turn is unlikely to happen while the ā€˜in-groupā€™ VCs dominate the narrative and control what success looks like to protect their own necks.

    For those who are holding on to the belief that venture capitalists are the last bastion of smart money, it is time to let go. While there are a few exceptions, venture capitalists for the most part are traders on steroids, riding the momentum train, and being ridden over by it, when it turns. 

    Professor Aswath Damodaran, Wall Street’s “Dean of Valuation”
    1. Not to mention the patagonia vest, vacations in Mykonos, or how many times they can squeeze ā€˜grokā€™ or ā€˜rubricā€™ into a conversation. [↩]
    2. Once-upon-a-time it was popularly characterised by ā€˜VC Twitterā€™, though that weird ecosystem has become more self-aware and at least partially a self-parody. [↩]
    3. The moonshot factory, not the social media platform [↩]
    4. We also discussed this during a recent episode of the Equidam podcast. [↩]
  • “Why don’t VCs set marks with 409a valautions?”

    “Why don’t VCs set marks with 409a valautions?”

    This is a question I saw on Reddit’s often-comical /r/venturecapital, which I thought was interesting enough to write out a decent response to. It hits at the root of a few major problems in the asset class which are always worth addressing.

    A 409A valuation, named after Section 409A of the United States Internal Revenue Code (IRC), refers to the process of determining the fair market value of a privately held company’s common stock. It is often conducted to comply with the tax rules governing non-qualified deferred compensation plans, such as stock options, stock appreciation rights (SARs), and other equity-based compensation arrangements.

    A lovely summary from ChatGPT

    First thing’s first: Generally speaking, VCs don’t care about valuation, and especially not ‘fair value’.

    …and that’s quite reasonable. VCs have their own investment strategy, their own approach to calculating risk vs potential, and if it works for them (and their LPs) then great. More power to them.

    What’s important here is that while we often use the word valuation in reference to deal terms and portfolio performance, what we really should say 99% of the time is price.

    In venture capital, price factors in a number of things, including the advantages of preferred stock over common stock, but most significantly it is geared at reflecting what the market would be likely to pay for that startup at the time. This is why VCs focus so much on comparable deals when pricing rounds, even if it ends up being a bit circular, with everyone copying everyone elses homework.1

    So that is the status quo. But why are VCs interested in preferred stock in the first place?

    Venture capital is all about power law, right? The idea is to invest in many startups, expect to lose money on 80%, and make a varying amount of money back from the remaining 20%.

    So why do they care so much about downside protection, rather than maximising that upside?

    When you add a liquidation preference to a deal, the implied value of the equity increases, meaning you get a smaller % for your capital. Lower returns at exit. That kind of trade-off flies in the face of power law, so why is it of interest?

    There’s a clue in this great article from William Rice:

    Liquidation preferences insulate VC firms from losses, so they can delay markdowns until after they raise another fund. VC returns follow a J-curve, therefore losses come much earlier than returns. Liquidation preferences can serve as valid reasons to not mark-down investments as companies begin to miss milestones or donā€™t receive an exciting Series A valuation bump.

    William Rice, “Slugging Percentage vs. Batting Average: How Loss Aversion Hurts Seed Investors”

    Liquidation preferences are mostly an irratational response from loss-averse VCs, some of whom may be trying to shield themselves against reporting poor performance to LPs. Maybe that’s overly cynical; I’m all ears if anyone has a better explanation.

    The core assertion here is that in a more rational and healthy market, liquidation preferences probably wouldn’t exist and VCs would just buy common stock.

    An industry with few standards

    Now that we have some understanding of how equity is priced and why preferences exist, let’s return to the original proposition: that VC investments could be marked up or down based on 409a valuations.

    In some cases, VCs do set marks with 409a valuations, but not all. Unfortunately – as with much of VC – there are no real standards.2

    Some VCs will only set marks based on fundraising activity, some will also consider 409a updates, some will factor new SAFE caps. Some will ignore downrounds, some won’t.

    The way VCs price rounds is subjective and non-standardised, and therefore way they track the value of those investments is also subjective and non-standardised.

    It might be going too far to say that this was all designed to obscure performance and protect charlatans, but this is probably how I would design VC if that was my intention.

    Performance > relationships

    Putting aside deal pricing for now: a VC firm could use any framework that provides a systematic read on fair value, such as this one from Equidam, and apply that to tracking portfolio company performance.

    This would represent a huge shift in how VCs operate, and how they manage relationships with LPs. It’s also something that I’ve written about at some length before.

    The horizon for useful feedback could be annual (or even quarterly) rather than 5-10 years.

    LPs could hold fund managers accountable for performance, and we may see that many household names (which attrract the lion’s share of capital and startup attention) are actually dramatically underperforming. They could more confidently back emerging managers, who could provide more meaningful metrics of success.

    VCs would be able to follow portco growth more precisely and learn much more quickly about what works and what doesn’t. Good managers would be able to fundraise much more easily.

    Crucially, it would make VC an industry based on performance rather than relationships and hype chasing as it is today. It would make VC better at backing innovation, which is what the whole asset class was built around.

    Startups are volatile, but capital should be stable

    Finally, if VCs were also to price deals based at least partially on fair value, we’d avoid momentum-driven valuation rollercoasters like we’ve seen in the last two years. Much less risk of valuation bubbles and crashes, more stability for LPs and VC funds, more consistent access to capital for founders, and – again – an asset class that could better serve innovation.3

    A more objective and independent perspective on startup potential, better suited to investment in the innovative outliers that venture capital was created to support.

    I’ve spoken to a number of people – LPs, VCs and founders – about this topic. There’s a near universal acceptance that a standard for private company valuation would be of huge benefit to the whole venture ecosystem.

    Unfortunately, none of them are particularly incentivised to make a stand on it.

    Some may benefit from the status quo, and the rest are keen to maintain their relationships by not making waves.

    1. Thus bubbles, etc… more on that later. [↩]
    2. If anyone has any data on this, I’d love to see it. [↩]
    3. There are also huge second-order effects, like how it would make venture capital fairer by removing more of the bias found in less structured approaches to valuation – but that’s for another post. [↩]
  • Screening Pitches

    Screening Pitches

    There are five straight-forward questions with which you can quickly evaluate a startup pitch, combining the strength of a proposition with its delivery.

    These questions bear some some resemblance to the Scorecard Method of startup valuation, which focuses on qualitative measures for early-stage companies, but with an additional focus on quantifying the market need.

    I have applied this approach to screening accelerator applications, but it can be used as the first step of evaluation in any pitch process.

    For the sake of simplicity we can score each of these on a scale of 1 to 5.

    1) Severity of Problem

    This is a question that can vary significantly based on the market you are looking at. Emerging economies tend to have more of a focus on the (high scoring) primary problems, which is why they’ve been able to better resist economic downturns.

    1 – Micromobility, dating apps, rapid delivery (esp. red ocean)

    5 – Access to water, energy, core financial services (esp. blue ocean)

    2) Strength of Solution

    Simply, are you providing a way for people to better cope with a particular pain, or have you managed to cure it in a complete and lasting manner?

    1 – Solution alleviates the problem

    5 – Solution eliminates the problem

    3) Scalability

    There’s almost always a focus on the size of market. TAM, SAM and SOM will feature in virtually every startup pitch deck. What’s often overlooked is how easy it is to scale into that market. Regulatory barriers, poor infrastructure, or corporate customers who move slowly are always a threat.

    1 – Infrastructure or regulatory requirements, long sales cycles and onboarding (esp. in small markets)

    5 – Web or mobile based product that is available on-demand to the entire target market (esp. in large markets)

    4) Profitability

    In many markets a poor product will win if it is just slightly cheaper than a better product. This kind of price suppression can be a killer for otherwise solid businesses. Similarly, some problems require costly solutions like agent networks, physical touchpoints, or a highly involved sales and customer service capability.

    1 – Low margins (high CAC/CRC/COGS, low LTV)

    5 – High margins (low CAC/CRC/COGS, high LTV)

    5) Team

    This is the hardest part of a pitch deck to quickly evaluate, and requires the most additional research. LinkedIn, interviews, papers, Glassdoor… the number of potential resources extends as far as your willingness to do the research.

    1 – No obvious fit for the problem being solved, by education, experience, or personal background.

    5 – Exactly who you imagine should be tackling this problem, with a combination of both motivation and ability.

    Conclusion

    At the end of this fairly rudimentary process you have a score out of 25 which should give you a very broad overview of the potential of this business. It is intended to quickly take a list of some hundreds of pitches down to the 20-30 you think are worth a closer look.

    At that point you can then start looking at some of the more granular data:

    1. Existing partners, strategic relationships, etc
    2. Industry and regional context
    3. Traction and development of competitors
    4. Revenue forecasts and unit economics
    5. IP considerations