TL;DR: This book is a great reference for the following things (some well-summarized in this YC talk):
- Various aspects of running an enterprise tech company in the valley.
- How to hire execs. Contains a comprehensive checklist of things one should think about hiring a VP of enterprise sales.
- How to handle performance reviews, firings, demotions.
- What a good HR organization should do, and help you with.
- How to design your organization (think of org. design as a communications architecture for the company).
- How to conduct effective 1:1s as an organization (followed by a great list of questions for a manager ask).
- Misc. tricky situations to handle as a founder – hiring from your friends’ company, promote from within or bring external candidates, when to sell etc.
Part I is here. In a hurry? Italics in the post represent key dos and don’ts for founders.
How VC firms work
- One management company (franchise) – this is the name of the VC firm you hear.
- Under them are several “general partnerships” (no longer a “general partner” i.e. single person, this is a separate legal entity of its own ). Each “general partnership” has different funds – LPs (limited partnerships) under it.
- Interest of VC firm != interest of the GP/LP always, particularly when new people join or MDs leave.
- How VCs raise money
- LPA – limited partnership agreement
- Fund amount is not actually with the VCs. A capital call is made each they want to invest in a startup, and the LPs are obligated to respond to the capital call in two weeks.
- Capital calls can fail or result in lower funding than expected .2008-like situations: LPs include HNIs who may be struggling with illiquidity themselves, banks who, like in 2008, may be dissolving themselves, endowments/pension funds etc who are facing capital crunch due to general market conditions.
- Average total fee over a 10 year period: 15% of the fund. VCs are expected to make capital gains and recycle those gains to cover up for the fees.
- Partners see base compensation with every additional fund raised.
- “It takes 10 years to kill a venture fund.” – additional funds / rounds can be raised while the performance of the first few isn’t clear.
- Carry: VCs get a 20% of the profit cut, which is known as “carry”. This can be reinvested (and is expected to be reinvested, at least till it covers the management fees).
- Friction within a VC firm – Firms don’t equal allocation between partners- seniority matters. An individual partner can make X times the amount allotted, but still get no carry because of allocation style and poor performance of the overall firm or fund.
- GP Commitment: LPs want VCs to invest a cut as well – 99% money comes from LPs, 1% from the VCs. Has gone up to 5%.
- Clawback: VCs can pocket the carry in the middle of the fund (say 20% of 50 mn in profit) and then the overall fund turns out to not do so well. VCs have taken more than the deserved carry and LPs demanding for this back is ‘clawback’. Harder to pull off across multiple partners.. (e.g. one partner got divorced, paid half to spouse. All partners paid taxes on the carry).
- Time impact of fund activity
- If you are raising with a VC fund that closers to closing, higher pressure for an exit.
- Wary of ‘zombie’ VC firms (no new funds to raise, carrying on their existing funds). Just ask when their last investment was.
- Wary of ‘secondary sale’ – VC can sell their entire portfolio to someone in a secondary sale.
- VCs close to end of the fund can also redistribute the portfolio to LPs – hassle for founder if there are too many LPs.
- Reserves – VC have a fraction of the fund (30-50%) in ‘reserve’ i.e. for future investments with their portfolio companies. Ask upfront for details on this.
- Cashflow – how does the VC maintain their cashflow? Are they recycling the carry appropriately to make up for the management fees? ([KR]: How does this affect the founder?)
- Cross-fund investing – bad idea, since there are multiple sets of LPs and multiple kinds of terms involved.
- Figure out what happens if and when the partner who invested in you departs – does it trip a ‘key-man clause’? (LP can ask for recall of funds).
- Understand your VC’s fiduciary duties – they are serving you/your board, the VC firm, their own GP/LP and a bunch of other people. Not all VCs are direct about what they have on their plate, making their behavior confusing.
- Understand your investors motives and financial incentives. Have an open, if difficult conversation about it now, to avoid surprise and trauma later.
In a hurry? Just skim over the italics in this post – they represent key dos and don’ts for founders. Part II of the post is here.
- Typically 8-ish pages (~2012).
- Two key aspects, everything else is secondary, don’t waste too much time on other terms:
- Economics terms
- Control terms.
- Signs of the VC not being entrepreneur friendly appear during the term-sheet negotiations.
- Early VC example: AR&D: 70k for 78% of the company. Post-money valuation becomes 90k.
- Individual VCs today own less than 50%, no effective voting control. They negotiate provisions that give them control over the major decisions made by the company.
- VCs investing at different stages in the company => different ownership percentages, varying rights, diverging motivations.
- Founders should direct and control the process of financing – leave as little as possible outsourced for the lawyer.
- Capitalization-table (Cap Table): spreadsheet that defines the economics of the deal.
- MD/GP: Managing Director or General Partner. They make the final decisions and sit on the boards of the companies they invest in. Prefixes “executive” or “founding” may be applied to indicate seniority.
- Principal/Directors: Have deal responsibility, need a MD involved to take the final decision. These are junior partners making their way up to MD.
- Associates: Not deal partners, they work for the partners. They do: scout new deals, due diligence on existing deals, write internal memos about prospective investments. Associates likely spend the most time with the cap table.
– Many VC firms have a 2 year associate program – after that, the associate leaves to go to B-school, work for a portfolio company or start up her own company. Star associates may go on to become principals.
- Analysts: Bottom of the ladder, crunch numbers and write memos.
- Other people involved in VC:
- Venture partners/Operating Partners: Experienced entrepreneurs who have a part-time relationship with the VC firm. May take an active role in managing the investment as chairman or board member.
- EIR (Entrepreneur in residence): Experience entrepreneurs who park themselves at a VC firm while figuring out their next company. Help the VC with intros/networking and due diligence. Last 3-12 months typically. Some VCs pay the EIR , some just offer office space and an implicit agreement to fund the next company.
Caveat Emptor: Great book, but throws in way too much Christianity/religion in the face of the reader. IMHO, it is much easier for humans to place absolute confidence and faith in an abstract higher power, than it is to place faith in their innate prowess. Substitute “prayer” and “God” in this book summary for something similar that works for you.
- Six point action plan to stop fuming and fretting:
- Get in a relaxed physical position.
- Visualize: Your mind is the surface of a lake, tossed by waves and in tumult. But when the waves subside, the surface of the lake is placid and unruffled. This imagery should help you calm down.
- Spend two-three minutes thinking about the most beautiful and calming nature scenes you’ve witnessed.
- Repeat, slowly to yourself, words along the lines of “tranquillity”, “serenity”, “peace” and let the effect of them sink in.
- Make a list of times in your life when you were worried and anxious, and things turned out fine (for the more religious, “God took care of everything”).
- Rely on a higher power to take charge of the situation and fix it.
“Bill O’Reilly who precedes me on our channel, is like a superhero. Because if you meet him in person, he is kind of shy, quiet. He would never dominate your dinner table. But you put that guy behind that desk, and he grows into this larger than life personality. And I have a little bit of that. When I sit in front of that desk, I don’t care who’s across of me, I don’t care if its a Republican or Democrat or President. It doesn’t matter. I only have one master and that’s my audience. I will serve that audience and if you try to dodge or weave, you will get pinned down. So I feel very empowered. In person, I am not a shrinking violet, but I don’t have quite as much, uh, power.”
– Megyn Kelly, 2014 interview
This post is a collection of insightful concepts and statements I found in Daniel Kahneman’s Thinking Fast and Slow. Apologies for the lack of coherence towards the end – the volume of the book ensured I got down to just jotting down the meat of the matter without any context or detailing.
- Fundamental premise of the author’s work: Economics says humans are mostly rational and their thinking is sound. The departures from rationality only occur due to emotions such as fear, affection and hatred. The author documents systematic errors in the thinking of humans – these are errors due to how our cognitive machinery is designed, not a corruption of our thoughts by emotions.
- Expert intuition: Thousands of hours of practice in anything (mostly your work) in a controlled environment with a good feedback loop can set you for taking good decisions just by “blinking” instead of having to “think”. A good example is a firefighter anecdote, where an experience guy ordered his team to head out of a house with no visible signs of danger. Only in hindsight did he realize that his subconscious was processing subtle danger signs related to smoke and fire. Note that this only works with controlled environment, with no underlying randomness (cases of firs are different, but there is an underlying pattern to the kinds of houses and kinds of fires they deal with, and the behavior of materials reacting to fire) as opposed to environments with fundamental randomness, such as stock markets. The stock traders doesn’t have a reliable, non-random feedback loop – so he cannot develop such “blink”-style judgement expertise.
- Notion of two Systems: A human mind has two systems – System 1 is intuitive, guided by associative memory (and hence affected by feelings) and FAST. System2 is deliberate, responsible for complex logic, reasoning and calculations, any kind of decision-making that needs effort, but it is also SLOW and LAZY. Much of the book focuses around understanding these two systems, how most humans rely more on System1 than they need and the errors arising due to biases wired into System 1. System 1 is flawed, yet it also very good at constructing coherent stories.
- Notion of two selves: The “experiencing self” and the “remembering self”. Human memories are not perfect reconstructions of reality. Humans are guided by the remembering self and this makes them expose themselves to unnecessary pain.
- Limited attention power of humans: As demonstrated in the selective attention experiment.
- “We can be blind to the obvious and we are also obvious to our blindness.”
- Illusions: Muller-Lyer illusion is a famous example of how our cognitive machinery is flawed (even after understanding the concept, it presents a reality that is hard to accept). Not all illusions are visual – many are cognitive, and those are the costly ones.
- Example of a cognitive illusion: Psychotherapists often have a strong attraction for a patient with a repeated history of failed treatments, thinking that they may be the ones to succeed in curing him. (Hint: the patient is a psychopath!).
- Flaws of System 2: System2 is lazy and reluctant to invest more effort than is strictly necessary. It believes it has chosen thoughts and actions, but these choices can be, in reality, guided heavily by System 1. The concept of priming is an example of this.
- On pupils and psychology: The pupil of the eye is a window into one’s soul – if you perform a slightly non-trivial calculation with a periodic frequency with a camera focused on your eye, it will record very regular pupil dilation and contraction events. The pupil dilation is an indication of mental effort – pupils contract immediately when a person gives up or finds the solution.
- On why training matters for System 2: Unlike a house’s circuit breaker, which completely breaks down in case of overload, System2 will focus its attention on the most important activities, letting go of the rest. The selective attention test video linked to above is proof of that. With training and over time, as you get more and more familiar with a task, fewer brain regions are involved.
- State of flow: Flow is a state of effortless concentration, so deeply focused on whatever one is doing at the moment that one loses a sense of self and all one’s problems. Flow leads to optimal experiences. All variants of voluntary effort – cognitive, emotional or physical – draw atleast partly from a shared pool of mental energy.
- “Ego depletion”: This demonstrates the “shared pool of mental energy” concept. People instructed to stifle their emotional reaction to an emotionally charged film will later underperform on a test of physical stamina. Another example – studies show that favorableness of results from judges increases in the short time after lunch. Tired and hungry judges tend to fall back on the easier default possibilities of denying requests for parole.
- Over-riding intuition takes hard work: The insistent idea that “its true, its true” coming from System 1 makes it difficult to check the logic. Lots of mental effort goes into training your System 2 to kick into action more often, whenever needed, but its worthwhile. Some lucky people are more like System2, most of us are more like our System 1.
- Strong link between self-control and cognitive aptitude: The Stanford marshmallow experiment is a good example of this.
- Concept of Priming: If you saw the word EAT and then saw SO_P, you are more likely to complete it as SOUP. If you saw WASH and then saw SO_P, you will complete it as SOAP. The experience you are subjected to (reading a word) triggers a portion of your associative memory, and so now your retrieval is biased.
- Priming as applied to experiences: Priming is not just about words, ideas and thoughts. In an experiment, young people who were asked to assemble a sentence from scrambled words related to old age, walked slower than the others in part 2 of the experiment when they had to walk down a hallway.
- Influencing of an action by an idea – the ideomotor effect. Clasp both your hands together and index fingers of both hands pointing at each other, now think of the line joining the tips of the two fingers and see how your fingers twitch!
- Reciprocal priming: Thoughts/ideas/words influence actions – that is priming. The inverse of it is reciprocal priming. Smiling naturally invokes positive, optimistic emotions and thoughts.
- “Act calm and kind regardless of how you feel” – you are likely to be rewarded by actually feeling calm and kind.
- Useful resources on priming: understanding how you are less in control of your actions than you think, and how priming affects your performance.
- Money-priming leads to increased self-reliance – money-primed people (exposed to thoughts of money) persevered almost twice as hard in trying to solve a very difficult problem. Money-primed people are also more selfish.
- “They were primed to find flaws and this is exactly what they found.”
- Cognitive ease – when things are going normally. Cognitive strain – when you need more help from System 2.
- The cognitive ease inflow-outflow machine: Things that lead to cognitive ease are repeated experience, favorable conditions such as a clear display and good font, primed idea (such as, being introduced to the concept through a nice subtle watermark in the background) and a good mood. What comes out of cognitive ease is the following feelings/emotions – “feels true” , “feels good”, “feels familiar and effortless”
- “Cognitive easy is good and recommended in some cases, but dangerous in other cases (where it prevents System 2 from kicking in and makes the wrong judgements via System 1).” As an example, the performance of Princeton grads in puzzles went up by a notch when the font worsened, causing cognitive strain and system 2 to kick in.
- Cognitive Ease: Pros: More creative. Cons: Makes judgement errors due to familiarity.
- Cognitive Strain: Pros: More vigilant, suspicious, invests more efforts. Cons: Feels less comfortable, leads to less intuitiveness/creativeness.
- “Illusions of remembering”: You think David Steinbill (made-up name) is a celebrity just because the experimenters exposed you to his name in a casual setting before the experiment!
- “Illusions of truth”: If you are put at sufficient cognitive ease by the mood and environment around you and by previous similar questions, you may agree to the phrase “chicken has 4 legs”. It takes a while for System 2 to kick in and tell you this is not true.
- “Anything that makes the cognitive machine run smoothly will also bias beliefs”
- “Familiarity is not easily distinguishable from truth”
- “If a statement is strongly linked by logic or association to other beliefs or preferences you hold, or comes from a source that you trust or like, you will feel a sense of cognitive ease.” This is because the lazy System2 will just accept the suggestions of System 1 and march on.
- Awesome example of cognitive ease effects: Stocks with pronounceable tickers perform better than the tongue-twisting ones! (like PGX or RDO).
- Mind is biased toward “causal thinking” and doesn’t understand statistics or regression to the mean easily. Good example of regression to the mean – ask a bunch of people to take 2 attempts at darts. The ones who did the best in the first attempt will get worse (relative to themselves) in the second attempt. This causes instructors to (faultily) conclude that admonishing leads to better performance in the next attempt and praise leads to worse performance in the next attempt.
- Intensity Matching: Humans unknowingly transfer evaluation from one situation to another (which merits a different way of thinking/evaluating) applying “intensity matching”. Trivial example – give a long description about a school girl really sharp at reading and then ask the audience to predict her college GPA. Reading skills at age 7-10 have nothing to do with GPA, yet instinctive answers from the audience indicate “intensity matching”.
- Common human fallacies while making predictions (or forming “intuitions” about situations): neglect of base rates, and insensitivity to the quality of information.
- Intuitive predictions tend to be overconfident and overly extreme.
- Moderating the extremeness of intuitive predictions is not always a good thing – example, venture capitalists need to call extreme cases like Google correctly, even at the cost of overestimating the prospects of many other ventures.
- Consider the range of uncertainty around a most likely outcome. (KR note: This is reminiscent of Aswath Damodaran’s recent lecture at Google about valuation – where he defines a range of variation on every single parameter in his valuation, so his end prediction for the stock price of Apple is a large histogram)
- The most valuable contribution of the corrective procedures that the author proposes to fix “wrong” intuitions is that they force one to think about how much they know.
- WYSIATI – Human mind’s bad fallacy – what you see is all there is.
- Asked to reconstruct our former beliefs, we often bring up our current ones instead and many cannot believe they ever felt differently.
- Hindsight bias – people cannot reconstruct their past beliefs accurately. This makes it difficult to evaluate a decision properly – in terms of the beliefs that were reasonable when the decision was made.
- The worse the consequence, the greater the hindsight bias (KR note: reminiscent of parents saying “I told you so” when things go south in a marriage they were arm-twisted into agreeing to).
- Hindsight and outcome biases foster risk aversion.
- System 1 makes us see the world as more tidy, simple, predictable and coherent than it really is.
- Halo effect: Depending on whether the company has been doing well or not recently, the same CEO will be called “flexible, methodical and decisive” or “confused, rigid and authoritarian”.
- Therefore, you can’t do pattern mining to identify what works for successful companies. Examples of this kind of failure are “Built to Last” and “In search of excellence” (companies/theses mentioned in both the books melted down in a short period following the book).For some of our most important beliefs, we have no evidence at all, except that people we love and trust hold these beliefs!
- Amazing experiment the author does with 25 top financial advisors – he gets a spreadsheet that has them ranked (with data on how much returns they generated), on an annual basis, for 8 consecutive years. He studied correlations between year 1 and 2, year 1 and 3…. and so on until year 7 and 8 (28 correlation coefficients, one for each pair of years). The average of the 28 corelation coefficients was 0.01!!
- People with the most knowledge are poorer at forecasting than people with some knowledge of the field/domain/situation. With knowledge, the person develops an enhanced illusion of skill and becomes unrealistically overconfident.
- Simplicity is often way better than complexity. Paul Meehl’s “little book” – simple, statistical rules are superior to intuitive ‘clinical’ judgements. Book by Gary Klein – “Sources of Power” – Analyzes how experienced professionals develop intuitive skills. Malcolm Gladwell’s book “Blink” is along the same lines.
- Emotional learning is similar to Pavlo’s experiment – the dog had “learned hopes”. Learned fears are even more easily acquired (KR note: perhaps more applicable to women, being the more emotionally susceptible gender).
- Lesson learnt: Train yourself hard, in a regular environment with a good feedback loop so that the “expert intuition” that you are developing, actually holds true.
- When you see data that seems to define a BASE RATE, ACKNOWLEDGE IT, LET IT CHANGE YOU.
- Planning fallacy – overestimate benefits, underestimate costs.
- How to overcome the planning fallacy – Develop an “outside view” by involving a ton of “reference class data” about similar projects.
- Sunk-cost fallacy – You didn’t have a reasonable baseline prediction when you started out, and when you get the baseline you ignore it because it’s too late in the game and you’re already invested.
- More optimistic people are the ones who are inventors, politicians, military leaders etc. They take more risks than they think they are capable of.
- Entrepreneurs are inherently more optimistic. Chances that a small business survives in USA for > 5 years are 35%. 60% of new restaurants are out of business after 3 years.. yet people still open new ones and are optimistic about them.
- Study shows CFOs are grossly over-confident about their ability to forecast the market.
- Pre-mortem: Just before an important decision has been finalized but not committed – you imagine you are in the future, the decision has failed, and look at what could have wrong. The main virtue of the premortem is that it legitimizes doubts.
- “What rules govern peoples’ choices between simple gambles and between gambles and sure things?” Amos and Kahneman set out to understand humans make choices, without assuming anything about their rationality.
– Econs (perfectly rational, selfish, stable taste) & Humans (WSYIATI, tastes change, not fully rational or fully selfish).
– Bernoulli’s experiments/conclusions: “A risk-taker with diminishing marginal utility for wealth (which is most of us) will be risk-averse.”
– Flaw in Bernoulli’s theory: You need to know the reference before you can predict the utility of a given amount of wealth.
- “People become risk-seeking when all their options are bad.” :-) This is insightful. Simple example – which would you pick – lose $100 for sure or lose $200 with 50% probability?
- Loss aversion ratio for most people is in the range of 1.5-2.5 (potential gains have to be that factor higher than potential losses).
- Brains of humans and other animals contain a mechanism that is designed to give priority to bad news.
- Goals are reference points. Avoiding the failure to meet a goal is a stronger motivator than the desire to exceed it.
- Perceptions of fairness are based on our reference points.
- “Altruistic punishment” (punishing a stranger for behaving unfairly towards another stranger)
- Smart negotiation tactic: falsely hold on to something as very precious or important to you, thereby showing that you’ll stand to be pained a lot by giving it away, when in reality, you were prepared to give it away all along.
- Consistent overweighting of improbable outcomes – a feature of intuitive thinking, leads to inferior outcomes.
– Opportunities to frame a fact differently, such that one way of framing evokes a different mental/emotional response. (e.g. probability of DNA testing failure – defendant will say “1 in a 1000”, accuser will say “0.01” – because accuser wants to show DNA testing works for certain, defendant wants to create doubts in the jury’s head).
- Human nature tends to be risk averse for gains and risk-seeking for losses – it is COSTLY to do so! You should favor taking risks in gain-scenarios and reduce risk-seeking when it comes to losses.
- Countering the “loss aversion” mentality that you were wired with – take a $100 loss with 50% chance, $200 gain with 50% chance gamble. Offered one gamble you will probably pass it ($100 loss will feel more painful than $200 gain). However, if offered 100 of these, no fool should reject it (compute the expected value there – the chances of you losing money are insanely low- like 1 in 32000).
- So, the next time you think of loss aversion, think of life as a bunch of these small gambles – you win a few, you lose a few, but the chances of you losing overall in the long run are slim.
- Be rational enough to avoid your loss aversion.
- “Combination of loss aversion and narrow framing is a costly curse.”
- Mitigating loss aversion: evaluate your portfolio only a quarter, else loss aversion will make you overtly sensitive to minor fluctuations and make you react on daily lows.
- Investors sell more losing stocks in December, when taxes are on their mind. The tax-loss harvesting advantage is available all year, but then mental account prevails more during the other 11 months (“disposition effect” -think you did well by selling a gainer instead of a loser).
- The “sunk cost” fallacy is both identified and taught as a mistake in business and economics courses, and there is evidence that graduate students in these fields are more willing than others to walk away from a failing project.
- “Losses evoke stronger negative feelings than costs.” e.g. “Would you accept a gamble that offers a 10% chance to win $95 and 90% chance to lose $5?” or “would you participate in a lottery ticket worth $5 where you have a 10% chance of winning $100 and 90% chance of winning nothing?” The two problems are identical but people like the second one way way more.
- Interesting example: Credit card industry lobbied hard to make vendors say it’s a “cash discount, not a credit surcharge.” (if you are paying different amounts for cash v/s card). People will much more easily forego a discount than they will take a surcharge.