English translation: make a LOT of small bets in order to win. (Even if most of those bets are losers.)

Now, this sounds somewhat counter-intuitive to a lot of folks who have been trained to “think like investors:” after all, the more deals you do, the less of a special snowflake you must be, right? (And we all know, Private Equity Professionals are the Specialest Snowflakes of All.) Furthermore, doing more and more “losers” in order to scrape together more winners (rather than trying to avoid losers altogether) just grates the wrong way at the investor mindset.

Well, Sim Simeonov has rejected that mindset with his Simeonov sim. (Forgive me.) But the point of my post isn’t just an emulation of Sim’s simulation. It’s that he’s right despite his simulation math. Rational VCs should be doing as many deals as possible, true, but it’s not due to portfolio IRR; it’s in spite of IRR.

No, the real reason that rational VCs should be doing as many deals as possible is that, to a large extent, VC firm survival has been dependent more on appearance than on financial reality. Specifically, assume two similar firms on their 2nd or 3rd funds, and assume they both, 5 years in, go out to raise funds with a 20% IRR. However, Firm A has earned that IRR through a risk-averse, lower-beta type strategy, while Firm B earned that IRR with a much larger “shotgun” portfolio chock-full of duds, but with a tiny sliver of a Google or similar mega-hit. Which firm is going to be able to raise the next fund with more certainty?

How things have worked to date is that LPs fall in love with great stories, and so it’s more important (in general) that you have one great story in the portfolio (even if it’s for a small investment) than that you have a bunch of sleepy, boring stories that average out to the same return.

Now, I’d love to see what savvy upstream investors like the Super LP, for example, think of this theory: it’s certainly not very flattering to the LP community if you suggest that they make investments solely on “stories” and not on “math.” In the LPs’ defense, I don’t think they’re being lazy or stupid; on the contrary, for the first several decades of the VC industry’s life, the market was so inefficient, and the data were so very sparse, that “stories” were the only reasonable data to look at.

However, we now have a VC (and super-angel, and micro-VC, etc.) industry that is chock-full of history, overflowing with data, and crowded with participants in the marketplace who will (relatively) quickly compete for new niches (especially as the squeeze of a denominator effect and general anti-VC enantiodromia are felt). I no longer feel as strongly as I once did that we’d soon have algorithmic VC decisions, and I doubt that we’ll see a “robot uprising in venture capital.” But I do hope and believe that we will see a more disciplined industry, and one where VCs’ incentives get rearranged to align better with actual financial returns (rather than with “stories” that drive fundraising).

(I do happen to know that there are institutional investors who realize the “great story bias” and are seeking to exploit the inefficiency it creates… let’s just say that if you were going to exploit it, you might look quite hard at Revenue-Based Finance as the way to do so

Happily, the math involved here is pretty low-key (algebra, the highest level of mathematical reasoning to which VCs are required to aspire).

One of the best VCs I know always aspires to be the lead investor. Being the lead investor means you’re the de facto coach, quarterback, and ringleader for that round’s investor syndicate (and likely the entire board). He also tries, both as lead investor and as board member in general, to be a coach, if not confidant and mentor, to the CEO. This is all in addition to the normal duties of a good board member: meetings themselves, prep for meetings, often board dinners the night before, regular if less frequent contact with non-CEO executives (diligence and prudence), recruiting etc., and of course, any audit/comp committee work.

What kind of time does this take, on a monthly basis (4.3 weeks/month)?

• Weekly CEO calls: 4.3 * 30 min = 2.15 hrs
• Board meetings q 6 weeks, plus prep: (3 hrs + 1 hr) * (4.3 / 6) = 2.87 hrs
• Massaging the egos of other board members before/after: 30 min * (4.3 / 6) = 0.36 hrs
• Monthly CFO or other exec calls: 1 * 30 min = 1 hr
• Executive recruiting (2 major searches a year, taking 10 hours min. each): 2 * 10 hrs / 12 = 1.67 hrs
• Committee work (2 meetings a year, taking 3 hours min. each): 2 * 3 hrs / 12 = 0.5 hrs
• Go to one industry conference a year: 8 hrs / 12 = 0.67 hrs

This is the bare minimum theoretical lower bound that you can consider as the time requirement to be a good, lead investor VC board member: 9.1 hours per board, per month, or just about 2.1 hours a week.

That is for the perfect, steady-state, frictionless world: board meetings are in your town at your firm’s offices (no travel), you do not raise a round, and there are no crises. A more realistic assumption would be to add:

• Meeting travel q 6 weeks (MINIMUM, even driving up the 280 from Menlo Park to the city takes some time): 1.5 hr * (4.3 / 6) = 1.1 hrs
• One crisis OR new round per year: 20 hrs / 12 = 1.7 hrs
• Actually “adding value” like you said you would (soliciting customers, buyers, investors, etc.): 2 hrs /month = 2 hrs

So the real-world minimum adds another 4.8 hrs / month, bringing us to 13.9 hrs /month or 3.2 hrs / week.

How much do VCs really work? I think it’s fair to suggest that VCs work at least as much as other ambitious but affluent, socially-encumbered, and non-hourly-billable professionals: probably on the order of 50-60 hours a week. Let’s call it 55, which would reflect the combination of 10 hour days, 5+ hours each weekend, and a long and/or exotic-enough vacation each year to brag about with the other nouveau-affluent in your social circle.

The real-world catch here is that VCs have to spend a minimum of 5 (and as high as 12) hours at weekly partnership meetings. Let’s call it 6 hours/week to be charitable.

55 hours total – 6 hour partner meeting overhead = 49 workable hours.

49 workable hours / 3.2 hours per board (real world minimum) = 15.3 boards.

So there we have it: 15 boards is the upper bound of what a VC can probably sit on. HOWEVER, this assumes 100% of his working capacity is devoted to board work — nothing here for new deals or fundraising (or for other exotic and occasional pursuits, like strategic planning, learning and research, or leadership and mentoring of junior personnel). That estimate of 15 boards also has what I call the “conceit of optimality,” or inverse-Murphy: it assumes that the crises, new rounds, etc. do not overlap and create impossible time-crunches.

Given that fundraising is THE existential requirement of VC firms, and given that new deal work does have to happen somehow (after all: how did those 15 investments get made??), you’ve got to make significant provision for the working time of a VC to those other, non-board priorities. I personally think that non-board work is at least HALF of the workable hours, but I could be convinced that a board-seat-heavy partner might spend 2/3 of his time on board work.

Therefore, I think that 10 is the maximum realistic board seat capacity of a VC partner who wants to do a reasonably diligent and good job on boards, while also doing the minimum to stay in business as a VC. In practice, I think many boards will take more-than-average time, and I think most VCs will need to spend more time on non-board work, so 7 or 8 is probably a better number to set as a prescriptive maximum.

One could exceed ten board seats without f***ing up in exceptional cases:

• Independent angel investor (no “firm” overhead)
• Exceptional geographic and/or industry concentration
• Evergreen fund, wind-down of a fund, or other nontraditional partner role

Otherwise, you are going to be dropping packets on the floor like a Cogent router in a SQL Slammer epidemic.

One probably needs to hold significantly FEWER than ten (or even fewer than 7) if the following hold:

• Geographic diversity (have to fly to board meetings)
• Industry diversity (trying to stay up to date and mine contacts in diverse fields)
• Series A/B/C rather than later stage weighting (hypergrowth, “chasm,” hiring, and fundraising challenges).

In this case, there was a new CEO recently signed up to work with a technical founder, there were some family relationships on the team and board, and there were some international complexities (overseas offices). I also believed that there were some cultural issues in the company that needed work (especially around customer service / customer experience issues).

Now, compare these things to the usual, “hard,” “objective” issues that VCs take: market size, defensibility / patents, growth rate, capital requirements — things that can generally be reduced to numbers. My concerns looked pretty “soft” in comparison: seasoning of the team working together, culture of customer satisfaction, family dynamics. I took a risk and laid it out there, adding that I would be happy to check in in a few months to see how things were shaping up on these “soft” issues (but I acknowledged the risk of losing the deal to a faster moving investor).

The entrepreneur’s reaction was mixed. At first he told me he appreciated the candor, but then, in a follow up email, objected pretty strongly and negatively contrasted our communication with other VC “passes” he’d received, each of which had a “hard” reason (like raising too much / too little, outside of geography, etc.). I thought about this for a bit.

If you were pitching, and the VC declined to proceed at that time, would you rather get a “hard” or “soft” reason for a pass?

I’d say “soft.”

If a VC tells you, “ah, you’re raising 10-12 million from two VCs, but my fund size will only let me put in 2-4,” or conversely, “you’re raising 2-3 but I have to put 4-6 to work in each investment,” what have you actually learned? With due respect, you’ve been told that your would-be date has to wash her hair on Friday. Perhaps, in fact, she is going to wash her hair, but if she was really attracted to you, she’d rearrange her shampoo schedule.

Likewise, total market size, IP, or the elusive “traction” are all “hard” reasons for a pass. They’re likewise convenient: they are impersonal / objective, deficient to some extent in all startups, and theoretically required for success. Each is a seed crystal around which a swirl of “soft” reasons can easily and apparently crystallize. And they all sound good, well-reasoned, prudent — things we can easily feel OK about mentioning to our partnerships or to you, the entrepreneur.

(Not that this is disingenuous or untruthful in any way on the VC’s part; since we must reject literally 99% of deals we look at, sometimes one reason is as good as another.)

BUT: if you can find someone willing to take a risk and share the “soft” reasons with you, have a close listen. Soft items include team dynamics, opinions about “direction” or “strategy,” or “pattern recognition” stuff. Sometimes it’s about a “smell factor” or something else that just makes a VC uncomfortable. Always, it’s a complex cocktail of different perceptions, judgments, and opinions (from the discounted cash flows to Lord Keynes’ “animal spirits”), and the true contents are much more varied and harder to describe than a single crystallized hard reason that’s dropped out of solution.

These things are risky for an investor to try and describe. They can be personal or interpersonal, and talking (or listening!) directly about one’s own self is hard. They often include a personal value or judgment call on the investor’s part, and those calls can prove wrong. However, in fundraising as in so much of startup work, perception is (or at the very least strongly feeds back into) reality. Getting an honest assessment of what one investor really, truly thinks at the “soft” and complex level is likely to be more helpful in shaping the business and the pitch than a pat “hard” answer.

Sometimes, things just don’t align and the real answer is: no fit, let’s both shake hands and move on quickly. And sometimes, there’s a complex swirl of doubt but the time and effort of dissecting and parsing it isn’t worth the likely yield: crystallizing on a “hard” rationale for a pass is fine. But if an investor takes the time to dig in, to do the “mass spectrometry” on the trace elements of his doubt, please listen. He’s taking a risk, and though the soft observations may be wrong, the mere fact of their existence and elicitation, as well as their details, should be valuable to the entrepreneur.

(The next step is getting VCs to solicit, appreciate, and iterate/improve based upon “soft” feedback from entrepreneurs. Which I am trying, the reader may have concluded in surmise, myself to do. The entrepreneur I describe is real and gave permission for me to mention him anonymously.)

From http://www.oregon.gov/EMPLOY/UI/ui_special_programs.shtml#Self_Employment_Assistance__SEA_

The Oregon Self Employment Assistance (SEA) Program helps eligible unemployed workers set up a business on a full time basis and still receive full unemployment benefits.  …
To qualify for the SEA program, you must:

• …
• have a viable business idea,
• be willing to work full time in developing the business, and
• have or be able to obtain the financial backing needed to start and sustain the business until it becomes self-supporting.

Kind of cool.  Normally, I’d understand that there’s a hazard here (given that I am an investor in several Oregon companies that all pay unemployment insurance premiums, which could be raised if this gets exploited).  But unfortunately, I paid enough premiums immorally required on myself (which payments I could never collect, because I was the entrepreneur and would have been ineligible had I quit) during my Oregon years that I feel a bit justified here.

(In fact, there’s an even weirder effect where sometimes there are web sites I know only from Webex demos or slide decks, and not from visiting the site itself. But I digress.)

As a startup, you SHOULD be sending retention and call-to-action emails. It’s a no-brainer. I don’t fault you for it. In fact, if I were an investor or advisor, I’d insist that you do it. (So many Web services naturally get more valuable over time, with the addition of users, data, events, etc., that you are often literally doing your users a favor the first time you harass them to come back.)

And, inevitably, the day comes when I tire of your appeals, and I want to pull the plug (or at least turn up the squelch knob).

BUT: when your “unsubscribe” link prompts me to sign in to your Web site — with a username I don’t remember (not even pre-filled in for me), with a password I even more certainly have forgotten, into your unfamiliar interface — in order to stop those email from coming in, then you are doing wrong.

Your “unsubscribe” link should have enough of a unique auth token in it that I can manage my email preferences. At the very most, it should be a two-or-three-additional-click process to verify with a round-trip email and link combination.

Instead, after two or three times trying to play nice and click your crappy “unsubscribe” link, I will just start clicking “report spam.” Enough of that, and your email throughput will suffer, and with it, all of your retention/CTA messaging.

So please: make it easy to unsubscribe (or at least to manage email prefs). Short-term minimization of your unsubscribe rate is not clever, and will ultimately kill your other metrics (not to mention incur user wrath).

• REAL VCs have committed funds from stable, liquid, institutions who are not going away (state governments, universities, pension plans, countries).
• REAL VCs have partnership agreements that last 8-10 years and aren’t tied to the current level of the NASDAQ or the price of anyone’s house.
• FAKE VCs are everyone else who claims to be a VC but isn’t like the above.
• FAKE VCs may be nice people but since they aren’t REAL VCs, you don’t know what you’re dealing with in working with them. So be cautious and “know your investor” if you are going to rely on them for your short- to mid-term capital needs.
• Don’t sweat it; unlike the financial economy, early stage firms are inventing and creating and building things to sell in the real economy. Yes, you’d rather sell your company into a bubble. But great companies are often built in downturns and sold in upturns. Keep building and selling.
• All the REAL WEALTH that humanity has ever created has been the result of new invention and teamwork. All of this CDO/MBS/hedge fund nonsense is just pushing around money. You, the entrepreneurs and inventors, are the real engines of true wealth creation and we VCs are honored to play a role in helping you do so.

All of this seems at least as true and relevant today as in the first days of October. So let’s all take a deep breath and keep this in mind: human ingenuity (Founders, CTOs, Visionaries) conceives new wealth; human effort and discipline (Engineers, Salesmen, Managers) bears it into the world; and the acceptance of it by markets (Customers, Sponsors) makes it viable and sustainable. VCs play our own humble role by advising the foregoing and making calculated risks of our (and our investors’) wealth and time. This is a GOOD THING, and furthermore, this is a cycle that despite its rough edges CREATES NEW WEALTH. That is not the case with all of the now-trashed asset classes (which were largely about flipping the same old bad ideas to one another) and the whining rent-seekers who (mis-)managed them.

If you’re reading this, you’re almost certainly a geek or a startup-world person. And that means you, like me, have a unique opportunity and burden to do the right thing in this crappy economic time.

So, please. (This goes for me too.) Turn off CNBC. Close the browser window for Yahoo! Finance. If at all you can, block out this volatility and pandemonium among the wealth-re-arrangers. And, please, focus and redouble your efforts on creating wealth and value that ultimately will be what allows our humble race of tool-wielding mammals to conquer ignorance, disease, malnutrition, isolation, Malthus, and generally the heat-death of the Universe.

• Invest in guys who are already rich, because they have fewer distortions in their motivations.
• Invest in guys who aren’t already rich, because they’re hungry.
• Invest in guys who have put their own wealth at risk, because they have “skin in the game.”
• Invest in guys who have raised outside capital from credible investors.
• You gotta outsource the tech stuff — it’s too expensive.
• You never outsource the tech stuff — it’s too important.
• Entrepreneurs should not come from a big company (because they have the wrong culture).
• Entrepreneurs should come from a big company under a big-ego boss (because they want to make their own name out from the shadow of the big cheese).
• Only young guys get this new (social networking, Web 2.0, whatever) stuff.
• Only seasoned old guys will make any money.

When you’ve got guidelines like this, many of which are quoted with nary a trace of irony by the practitioners of our art, it’s fairly clear that you actually don’t have any useful guidelines.

Except one: invest in guys who’ve done it before.

The only person you know has a shot at creating a company with an exit value over $100 M (which is about the minimum exit value that most VCs would admit to wanting in any case, so I’ll use this as the threshold for my definition of a “star entrepreneur”) is the guy who’s already done it. Everybody else hasn’t yet proved it.

However, we have a major signal-to-noise problem here. When you look at an entrepreneur, even if he’s a star, you don’t know to which causes and in what proportions to attribute that stardom. Certainly, the quality E of star entrepreneurship could be the cause. But it could also be quality L (for luck). With only one exit, you just don’t know. But with no exits, you know even less.

If you were a statistician, you might try doing something with a Chernoff bound or a Z-test to figure this out. But a few things confound this approach. The main problem is that your number of trials is usually one. You can’t just keep tossing the coin to see if it comes up heads 51% of the time; you have to somehow guess the bias after only one flip (no pun intended!).

Another big source of error is that successful exit events are fairly rare. Most venture funded companies don’t have successful exits. (The old chestnut about VC is that a fund makes ten investments; five fail, 3 or 4 return 1x capital, and 1 or 2 make a 10x return. That’s hardly accurate, but it’s a good enough schematic for understanding the rarity of successful exits.) So if the probability of any given entrepreneur having a successful exit is 10%, then even a “rock star” who is five times better than the average is still only even money to exit big.

So, we have lots of both Type I and Type II errors. Finally, successive startups are not independent trials. That is, unlike rolling the dice, each startup you do is affected by the previous ones (both the experience of doing them and the ultimate outcome).

Even when an entrepreneur has been successful in the past, we don’t know if he’s likely to be successful again (though we can say, on average, he’s more likely to succeed than a newbie). But often, we fail to reject the guys who “hit the lottery” with their previous success. And even more often (almost by definition), we end up rejecting highly promising entrepreneurs who haven’t yet had a home run.

Yet, somehow, VCs continue to invest, and the returns (compressed due in large part to excess capital seeking a home in alternative assets / private equity) have continued to be good (if less princely than in the early years of VC). So VCs aren’t just monkeys throwing darts; we do have some discrimination ability.

Another chestnut in the VC industry is that “it takes $X million (e.g. $30 million) to make a general partner.” That is, to get a venture investor to the level of a seasoned senior investor, he needs to have led $X million in deals. This amount of deal flow (or, as it’s sometimes told, losses) is required to build up the black box of intuitions, gut feelings, sixth sense, etc. that a good general partner should have.

To me, this is a bunch of horse hooey. Yes, any good seasoned professional in any field will have some pre-rational judgment abilities that appear to be a “black box” — but these should only come into play at the margin. The core of any professional discipline must be reducible to a teachable, coherent syllabus. Take, for example, Malcom Gladwell’s example in Blink of the use of the Goldman algorithm for diagnosing acute myocardial infarction (heart attack). Essentially, the algorithm kicks the ass of expensive cardiologists and other “professionals” at doing one narrow thing, which is telling whether a heart attack is happening.

Now, the human body is a system, replicated and observed over billions of instances, with trillions of dollars cumulatively spent on measuring and exploring it. It provides feedback continuously on a second-by-second basis. And a heart attack is a fairly catastrophic and disruptive event — the death of part of the most important muscle. So the fact that a relatively simple algorithm can discriminate that event with great specificity is perhaps unremarkable.

But what is remarkable is that it took until the mid-eighties to promulgate the Goldman algorithm, and even today it’s not the gold standard. (Hey, at least medicine has the Goldman algorithm: in VC, nobody yet has validated such an approach.)

Doctors and VCs both have acute cases of what I call “special snowflake syndrome:” both groups tend to believe that they have special, irreducible talents and skills at doing whatever they do, and that they could never be replaced by a dumb machine. It is no coincidence that special snowflake syndrome tends to strike those in high-income jobs; folks who’ve seen automation or offshoring put downward pressure on their wages tend not to subscribe to this conceit. We also see special snowflake syndrome in industries where there are relatively high barriers to entry, such as regulatory (medicine) or timing / liquidity (10 year partnership agreements in VC).

In both cases, special snowflake syndrome will inevitably lead to heartbreak as people without the illusion of snowflakeness find and implement things like the Goldman algorithm (and the coming, immodestly named Lucas algorithm for VC). Unfortunately for the doctors, they won’t be capturing the economic surplus that results — it will be the middlemen in the hospitals and insurance behemoths that soak up the savings. (Doctors: save yourselves now, by demanding economic ownership of your patients’ well-being, the only humane and just way to allocate costs and risks in your profession!)

Fortunately for VCs, the implementation within a partnership of the Lucas algorithm will enhance that firm’s ability to identify and make successful investments with greater certainty and less manpower. And since VCs, through the carried interest portion, are compensated on financial performance, this will ultimately benefit the adopters. Yes, there will be some Schumpeterian woe for the old-school hangers-on as the snowflakes of their egos are melted in the sunshine of the new day that will be ushered in. And yes, a certain few of the old-school VCs — the ones with really great black boxes and/or Rolodexes — will continue to enjoy their maverick road gambler reputations. But by and by, rationality is coming to our market. Our black boxes will help us make decisions at the margin, but our algorithms will drive our core activities.

Does anybody want to work
on the algorithm with me? (I’m willing to hyphenate the name of the algorithm.) Drop me a line or give me a call at Voyager, +1 206-438-1822. (There will, of course, be several variations for different industries, geographies, stages, and firm preferences — so much so that each firm will likely need its own implementation — which is why I’m not too concerned about giving away competitive advantage by discussing with others in the industry.)