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When you hear “The Blockchain,” grab your wallet

All the “thoughtful” executive types (VCs, C-levels, analysts) now seem to share the same low-risk opinion about crypto-currencies.  (“Superficial contrarianism,” perhaps)

It goes like this: “Well, Bitcoin itself is in a bit of a speculative frenzy [knowing chuckle, transitioning to sober contemplation] … however, we think there’s tremendous promise in The Blockchain”

A year or three ago, this seemed like a reasonable stance (give or take the adjective “tremendous”). In 2014, mail-order heroin and low-stakes gambling were basically the only uses for Bitcoin itself.

But 2017 has been the year of the ICO, and the major coins have pretty demonstrably become targets of Real Money by now. So, where are all these promising applications?

Here are some real live examples of the cockamamie schemes that are purporting to use “The Blockchain” as of January 2018. Names have been withheld to protect the fatuous:

  • Copyright (or other intellectual property) registration
  • Paying people to look at advertisements on the Internet
  • CARFAX (automobile history)
  • Employment resume / C.V. verification
  • Basically all of corporate finance (M&A, debt, equity)
  • Foreign Exchange

What do all these things have in common? They are real-world difficulties that are worth paying money to solve. What else do they have in common? They are all things that can be very acceptable solved with pencil and paper, or at most, 1990s Oracle RDBMS type technology.

Why would people change their behavior and pay good money to move these processes to The Blockchain? Surely these proponents have a logic: there must be some particularly compelling piece about The Blockchain, right?

  • “It’s decentralized!”
  • “It is totally immutable!”
  • “It’s totally automatic [‘smart contracts!’] with no way to cheat!”

If you hear this level of glib bullshittery being slung your way as rationale for using The Blockchain for some application, better hold onto your wallet.

Thinking about markets, not technology

In a parallel to the abuse of terminology around the word “disruption,” where people misappropriate Clay Christensen’s theory and talk about technologies themselves as “disruptive,” blockchain cheerleaders talk about technological features as if they were ipso facto benefits.

But “decentralized” or “immutable” or “automatic” or whatever – aren’t necessarily benefits, much less unique and transformative catalysts for market value.

Starting with The Blockchain and trying to shoehorn it in to various market needs is backwards-minded and almost always going to fail. Here’s why.

The Blockchain is not a fundamental technological capability on its own. Rather, it’s a clever combination of three particular features – each of which is a well-understood [if arcane] and widely-available capability. If you need these three particular capabilities for your market application, then The Blockchain is your huckleberry:

1. Path-dependent, unchanging history,
… that works decentralized with
2. untrusted nodes and counterparties,
…and wherein you need to have
3. cheating discouraged by math, not by secrets.

What do these three things mean?

Path-dependent, unchanging history – More or less, this is a “ledger,” where the final state is dependent upon all the changes that went before. One key difference, though, is that in ledgers, you can often go back and insert transactions you forgot to record. Another is that, with ledgers, the final state doesn’t really depend on whether you cashed check #101 before #102, as long as they both got cashed before the reporting date. If you need to keep a ledger that can never be changed (fixed; or, in fairness, cooked) and where it really matters what order everything happened, you need yourself one of these. Happily, we more or less have them and we call them “append-only databases.”

Untrusted nodes and counterparties – In other words, do you need to reliably transact while also expecting that each person you deal with is trying to screw you, possibly with the collusion of at least several others? If you do, my apologies, and you should seek better friends, but at least you have the benefit of decades of academic research on things like the “Byzantine Generals problem,” along with algorithms that can be proven to keep things on the level even when dealing with a network of partially treacherous counterparties.

Cheating discouraged by math, not by secrets – Most of the time when we want to discourage cheaters or thieves, we require some secret-ish piece of information, like a PIN number, a password, or even the pattern of notches carved into a physical metal key. As long as you can make sure the non-cheaters have the secrets (and none of the cheaters have the secrets) this works well. If you can’t be sure of this, though, you can make sure that would-be cheaters have to prove that they’ve done lots of long division and shown their work longhand on paper, which takes some amount of time no matter how clever they are. This is more or less the idea of “proof of work.”

[Note: After circulating a draft of this post privately, I realized that I almost certainly read Tim Bray’s “I Don’t Believe in Blockchain” at some point last year and unconsciously plagiarized much of the above.  But, even on a re-read this is still mostly true and definitely how I’ve been thinking about this stuff.  So, although I promise I wrote all the words in the section above, let’s consider most of the ideas, right down to the use of specific phrases, to have come from Tim.]

Here’s the obligatory Venn diagram:

http://rlucas.net/crypto_currency_venn.pdf

Now, what kind of ice-cream sundae do you make with these three particular scoops? Bitcoin, of course. But what is it really useful for? Well, I would say, a medium-sized economy among participants who expect many of the others to be thieves, who are afraid of getting cheated by welchers yet need to trade with these snakes, and who have no way outside of their interaction to share secrets between themselves.

In other words, you have a technological mélange purpose-built for mail-order heroin. That’s basically it.

OK, snarky guy, are you saying there are absolutely no apps for The Blockchain?

Let’s try to be fair-minded here. What are some use cases that really could leverage (or perhaps even require) all of these core capabilities?

The Domain Name System et al. For example, Namecoin. You can imagine that the DNS might one day be (or is already) too big or unwieldy for ICANN to administer through its ICANN/Registry/Registrar/Registrant system. You might then imagine that it becomes much more practical to allow a blockchain-based system where a node can lay claim to a particular unused name after a proof of work, even if others upon seeing it would like to steal it away. This checks the boxes as being a good fit. However, for DNS (and for ARIN and BGP tables and many other things) simply having a means to definitively establish the truth isn’t enough; there’s also the operational side of giving up to date answers very quickly to billions or trillions of queries, for which the actual blockchain piece is useless.

Voting. If you want to have an actually fair election, being able to prove all the votes in an immutable and universally verifiable way, even with the vote-counters as adversaries, this could be a really good app. (Unfortunately it’s a dismal business.) Consider that here you expect everyone else to be a thief/welcher/vote-rigger, and the scale of the problem begs decentralization, plus, there are real practical issues with handing out secrets ahead of time.

Distributed Computation 1: Storage. For example, Filecoin. If you want censorship-proof storage of information, but you need to incentivize participants, Filecoin seems well thought-through. In order to serve both privacy and censor-resistance needs, you need to treat everyone as a thief, and you need to prevent anyone from changing history to be truly censorship-proof. Finally, in order to be sure someone has earned their incentive you need a proof of work. Very clever. Unfortunately, this is also a dismal business, mainly because the cost of storage keeps dropping, and the sorts of things that you really need to keep in a censor-resistant data store, at least in a rule-of-law Western society, are either truly nasty (kiddie porn, nuclear weapons secrets) or simply not that lucrative (proof of governmental wrongdoing / whistleblower leaks).

Distributed Computation 2: CPU. This isn’t built yet. But you could imagine a Filecoin-type system meant to incentivize participants to conduct computation on their own devices and send the results home – sort of a SETI@Home for the blockchain. The problem here is that to really reach venture scale, you will need to allow not just specialized processing of SETI signals, or protein folding, or various of the other specialized decomposed computation problems that are well known, but truly general computing that allows customers to reliably and securely get ad hoc compute jobs of all sorts done. This is much harder than storage; in storage, I can encrypt files or blocks and have a reasonable certainty that the actual storage nodes will never be able to read or tamper with them. In compute, this gets a lot trickier. Imagine doing, say, massively distributed OCR or video rendering. The algorithms to do the heavy lifting will require the input data in an unencrypted, unobscured form – the OCR will need to actually “see” the image in order to read the words. If you are running a malicious node, you can “see” the page I’m sending to you and you could likewise interfere with the results, without me ever knowing. It seems technologically plausible to be able to transform at least some subset of compute tasks in a way that effectively encrypts or obscures both the computation and the I/O – but to do so in a way that is efficient seems quite tricky. If this nut gets cracked, you could see something truly transformative, as it would have the functional properties of Filecoin but with potentially far more attractive unit economics.

What about applications that are partial fits, using at least 2/3 of these core capabilities?

Title plants (land ownership). In the U.S., thanks to some ancient English traditions we’ve inherited, nobody definitively knows who owns what piece of land. The way we solve for this is the quiet but giant title insurance industry, who guarantees the ownership interest. They in turn underwrite the ownership by accumulating “title plants,” which are basically databases from individual jurisdictions (counties, parishes, states, etc.) going back as far as they possibly can, showing all of the valid changes in title. A title plant is an immutable historical append-only record. It’s presently centralized (and this makes for quite a lot of jobs in county recorders’ offices around the country). But it also means that for transactions that “touch” the title to real estate, there’s a small but significant delay and hassle in recording all such transactions with the centralized keeper of the record. If title plants were maintained on blockchains, you could imagine that real estate transactions – not only sales, but mortgages, liens, etc. – could close in seconds at the swipe of a finger or the call of an API. Is this a venture scale opportunity? Certainly if you controlled it all, you could charge a handsome fee and displace the entire title insurance industry. However, it’s unclear that there is any market pressure to do this: most sales, mortgages, and liens involve many other moving parts and changing the turnaround time from one business day to a few seconds on the recordation is of questionable standalone value.

Anti-spam (and robocalls, etc.). It could be that a mix of the proof-of-work and byzantine generals capabilities might be a great recipe for collaborative approaches to stopping or reducing spam and robocalls, by imposing costs on nodes and sub-networks for bad behavior. There are lots of approaches to this problem, though, and it’s not clear that even 2/3 of the blockchain is important – proof-of-work alone might be enough (or you could also just impose tiny charges on each message without fancy crypto math).

That’s it. I’m sure there are more to be found, but not vast greenfields of more applications.

The Blockchain is more like XML than like the Web.

The Web exposed a way to connect mostly-already-existing information and transactions to millions, and shortly thereafter, billions, of people. Subsequently, and building upon that network, new kinds of interactions that were now possible became commonplace (i.e. “Web 2.0” or “social” and “collaborative” technologies).

But The Blockchain isn’t like that. The Blockchain is a technological mishmash of capabilities or features that, in the right spot, can help solve some tricky coordination problems. It doesn’t, on its own, connect people to things they largely couldn’t do before.

In this way, The Blockchain is more like XML. Does anyone remember the 1998-2003 timeframe and the hoopla about XML? At the time, a very valid point was made that markup languages (well, really just HTML) were part of a huge important wave (Web 1.0), and the thought was that this could be extended to all parts of the information economy. XML, as the sort of generalized version of HTML (pace, markup language nerds, I know “Generalized” has a special meaning to you but work with me here), was going to be transformative! After all, it was:

– Vendor agnostic! (hah)
– Text-based and human readable! (hah)
– Stream or Document parseable with off-the-shelf tools! (hah)

Well, it turns out that those things, even when they were all true, were just capabilities that were well suited for some real-world problems and not so much for others. In fact, it was mainly suited for data interchange in a B2B context, or for certain kinds of document transformations. Not particularly compelling for much else.

What was actually important then was the particular flavor of XML called HTML, and the absurd gold rush around that time surrounding it. HTML seemed approachable and it was El Dorado. Everyone and her brother were “coding” HTML and learning how to FTP GIFs to their servers. Eventually, most of those people and companies failed, but in the midst of that gold rush they created a ton of real value.

[One commenter who was early in the promulgation of XML objected a bit here.  I think this is fair.  I’m not saying HTML came from XML; rather, I’m saying that attempts to generalize the basic underpinnings of HTML/HTTP — the human-readable-ish markup for wide interop — fell short, because the tech underpinnings were less important than the entrepreneurial and speculative frenzy.]

What the real story of Bitcoin is.

The real story here is quite the opposite of the new sober conventional wisdom. It’s not the underlying blockchain technology that’s fundamental, transformative, or even particularly interesting.

What’s interesting is precisely the speculative bubble: the specific crypto-coin(s), or more importantly, the frenzy of activity by fortune-seekers drawn to this El Dorado.

The actual underlying technology happens to be a bunch of particular features and capabilities, some of which have been around decades, that happen to be very useful for the main original Bitcoin use-case (mailing around LSD blotter paper with the “B$” logo, or whatever).

The Blockchain of the dilettante investor’s imagination is some kind of brave new philosopher’s stone that can upend any business process. Bullshit.

The real opportunities here are going to be generated by lots of aggressive and more or less smart people feverishly trying new, heretofore “unfundable” things, financed by their own crypto-currency gains or more likely by the wild gambling of the pilers-on who missed the first wave. Some of these gold-rushers are going to create things of real value and of venture scale, if only by a stochastic process.

Danielle Morrill is mostly right about VC deal sourcing – here’s how she’s wrong.

Danielle Morrill has put out a fascinating TechCrunch article about the art vs. science of how VC “source deals” (find investments). It’s a rare candid peek into a side of venture capital, and from a perspective, that is foreign to most writing from outside the industry. Danielle is spot on with most of her article, but there are a few glaring holes in the picture she paints.

First, what’s right:

1. Old guard vs. new guard. Danielle is absolutely correct that in VC, as in most professions, the older cohort is in conflict with the newer, rising cohort. And in general, the older cohort is the group that controls the power and the economics: by definition, they’re the survivors who’ve made it to late-career stage and have done pretty well, and so they will tend to bring a status quo bias. Change always threatens the status quo — even in an industry that outwardly worships “disruption.”

2. Cargo cult or “pigeon superstition.” Danielle nails it on the head that most VCs — firms and individuals — refer to “pattern matching” and rely on it to a degree that is often indistinguishable from superstition. Generals are often guilty of “fighting the last war” instead of seeing new situations for what they are, and the same is true with investors.

Now, Danielle is a promoter and a hustler (and I mean both terms in the good sense), and it’s natural for her to think about the world — and to critique the VC industry — in terms of an aggressive outbound sales process. But there’s a problem with this approach. VC is not sales, and seeing only through a sales lens will give you a distorted view.

Here’s what Danielle’s article missed by a mile:

1. Deal Types, and why sourcing doesn’t suffice. From the investor’s perspective, there are two types of VC deals.

  • Type 1: Deals that will get done whether you do them or not.
  • Type 2: Deals that won’t necessarily get done if you don’t do them.


Type 1 deals
are “obvious.” Given decent market conditions (e.g. not in a crash/panic), they are going to get funded by *somebody*. For example: I just heard a pitch from two Stanford grads, one of whom had already started and sold a company, and whose traffic was growing 10-12% a week in a reasonably hot sector. They want a reasonably sized and priced Series A round. That deal is going to happen, no matter what.

If you want to invest in a Type 1 deal, you have to *win* it. You probably have to “source” it to win it, but that alone won’t do. You either need to pay a higher price (valuation), and/or bring more value to the table (domain expertise, industry connections, personal competence / trust).

    • Pricing: To be able to profitably pay a higher valuation, you need to have a pricing knowledge edge (which is, in more traditional areas of finance, *the* edge — why do you think Wall Street pays all that money for high-performance computing?). To get that edge, you must know something that other investors don’t about the industry, technology, or people.
    • Value-add: To bring more value to the table, you need to have something rare and desirable, and which you can *apply* from the board / investor level. That typically means you’ve previously made deep “investment” of skill, connections, and knowledge in the relevant industry, technology, or people.

Winning Type 1 deals isn’t about sourcing. It’s about front-loaded work: work spent building up knowledge, connections, reputation, skill, etc., and then demonstrating and exploiting that front-loaded work to add value.

Type 2 deals aren’t obvious. Maybe the team is somehow incomplete; maybe the sector is out of favor. Maybe there’s “hair on the deal,” as we say when things are complicated. Maybe there’s no actual company yet, as happens with spin-outs or “incubated” ideas.

If you want to invest in a Type 2 deal, you have to *build* it. It’s true you need to “source” it, but often times “it” doesn’t even look like a deal when you first learn of it. Maybe that means building up a team or negotiating a technology license from a corporate parent. Maybe it means helping make crucial first customer intros (and watching the results). Maybe it means “yak shaving,” getting some of that wooly hair off of the deal and cleaning it up. (I like that metaphor better than polishing the diamond-in-the-rough, but same idea.)

Almost always, it means building a syndicate. That starts with building consensus and credibility with the entrepreneurs and within one’s own firm. Then, it usually means building the co-investor relationship and trust needed to get the round filled out. (For Type 1 deals, it’ll tend to be easy to win over partners and co-investors. Not so Type 2.)

Winning Type 2 deals isn’t about sourcing. It’s about back-loaded work: building up a fundable entity and a syndicate to support it.

2. Pattern matching and non-obvious rationality.

The way that VCs approach “pattern matching” seems irrational when Danielle describes it. Why do those behaviors persist? It’s because they’re rational, in a non-obvious way.

If you lose money on a deal, you’ll be asked “what happened.” If your answer is “X,” and you’ve never encountered X before, there’s a narrative tidiness to the loss, especially if you resolve not to let X happen again.

If you lose money on a subsequent deal, and you also say it’s due to “X,” then things start to get problematic. Losing money on X twice starts to sound like folly. What’s the George W. Bush line? “Fool me twice … um, … you can’t get fooled again.”

If you lose money three times due to “X,” well, then, you will have real problems explaining to your upstream investors why that was a good use of their money. (Even if, in a Platonic, rational sense, it was.)

In an early-stage tech world swirling with risks, so many you can’t possibly control them all, you grab a hold of a few risk factors that you *can* control, which risks — if they bite you again — will have outsized career / reputation / longevity risk for you. And that gets called “pattern matching.”

(The same applies on the upside. If you attribute making money to Y once, it’s nice. But if you make money twice in a row, and claim that it was due to Y, and your early identification and exploitation of Y, you look like a prescient investing genius.)

Now, I don’t believe that the “X factors” and “Y factors” are all meaningless, or that pattern matching is a worthless idea. But even if you did believe that (overly cynical) idea, given the reasoning above, you should still consider it rational for VCs to behave exactly the same regarding “pattern recognition.”

3. Teams do work.

Although Danielle is right that sourcing, winning, and, ultimately, exiting profitable deals is the formula for individual success in VC, that ignores the very real role that firm “franchise” and teamwork can and should play.

Throwing ambitious investor types into the same ring and letting them fight it out like wild dogs isn’t the route to VC firm success. Well, in certain markets it probably works very well — but it’s incredibly wasteful of time and talent to have unmitigated, head-on competition between a firm’s own investors.

No. In fact, teams can and do work. Danielle’s own article manages to quote both Warren Buffett and his longtime partner, the less well-known but still mind-bogglingly successful investor Charlie Munger. Do you think Berkshire Hathaway board meetings are dominated by infighting as to whether Charlie or Warren deserves credit for the latest M&A deal? Hell, no.

Teams work in investing when, between teammates, there’s enough similarity to ease the building of mutual trust and respect, but enough difference to bring something new and useful to the shared perspective. That can be a difference in geographic, sector, or stage focus, as is classically the case. Or, I would argue, it can even be a difference in the part of the lifecycle of a VC investment that best suits a particular investor.

Let’s do a thought experiment. Let’s assume we have two partners in our firm, GedankenVC: Danielle Morrill’s clone, Danielle2, and Charlie Munger’s clone, Charlie2.

Assume there’s a hot new startup out there, let’s call it Software-Defined Uber for Shoes (SDUfS), led by a young charismatic team, who’s intent on building out a social media presence, throwing parties and events to attract energetic new employees, handing out free custom shoes around San Francisco, and otherwise making the best of their recent oversubscribed $2.5 M seed round.

Who’s going to source that deal? Danielle2 or Charlie2? (Sorry, Charlie.)

Now, fast-forward 3.5 years, and everything is amazing, if complicated. They’re on three continents, Goldman Sachs has done a private placement from their private client group, bringing equity capital raised to $600 M, and they’ve floated the first ever tranche of $750 M in Software-Defined Shoe Bonds (SDSBs). Revenues are forecast for $3 B next year, but there’s trouble going public because of regulatory uncertainty around the Argentine government’s treatment of their main on-demand shoe 3-D printing factory in suburban Buenos Aires, and the complicated capital structure. Underwriters and investors are skittish about ponying up for the IPO.

Who should be on the board of directors of SDUfS? Danielle2 or Charlie2? (No offense, Danielle.)

GedankenVC will do best if the person who can source that deal sources it, and if the person who can manage that complex cap structure to exit manages it. Teams do work.

(Disclaimer: I help “source deals” for Seattle-based B2B VC firm, Voyager Capital, but on this blog I speak only for myself.)

RevenueLoan meets Disneyland, capitalism, America, and God.

A family trip caused me to end up at Disneyland, the old-school Anaheim original, on the day of a Disney-sponsored half-marathon. (The surreality of that event, with its mouse-ear-bedecked joggers and tutu-clad princesses, could merit its own blog post.) But what got me thinking the most was a sight from after the race, and it made me realize just what an awesome opportunity our team has at my new startup, RevenueLoan.

Our party of runners (not me!) and fans stopped for some post-run hydration, and I happened to stand in front of a racing wheelchair owned by one of the rolling half-marathoners. As I looked it over, it was almost unrecognizable as what the word “wheelchair” brings to mind: this beaut was customized, with super-narrow
aerodynamic form, racing bicycle-style brakes, and sharply tilted, carbon-fiber mag wheels sporting slicks. What’s more, various of these clearly purpose-built parts, including and especially the specialty, high-end components like the carbon fiber wheels, sported the brand names and logos of their manufacturers.

Seeing the brand logos of these specialty components, a single thought, immediately and unbidden, came to mind: “what a shitty, small market; there can’t be more than a few tens of thousands of these units to be sold worldwide.”

A second thought followed almost immediately, as my conscious mind caught up to my knee-jerk initial thought: “What the hell are you thinking, Randall?  That’s a shitty and broken way to think about markets, business, and the world.”

Let me be clear: there is nothing shitty, or small, or unworthy, about a business that makes a great and unique product, that generates customer love, and that manages to turn a profit. No. Hell, no! In fact, I would venture to say that such a business — regardless of total market size, with a lower bound of recouping its owner’s living costs — is the very telos of the free market system, the raison d’être of capitalism.

I’ll say it again: the very reason why capitalism is justifiable, good, and to be maintained is precisely because it brings us miracles like self-sustaining inventors and producers of wheelchair racing components.

My knee-jerk “small market size” dismissal is a pathology easily traced to the years I spent in traditional venture capital. While I’m proud of several of the companies I worked with, and many of the people I knew, in the VC industry, I’m downright ashamed at the conditioning effect my work there has had on my thinking.

It’s not necessarily a conscious moral failing of the VCs: any industry or business that valorizes one category inevitably does rhetorical violence to those outside that category. Salesmen have “deadbeats” who never close, doctors have “GOMERs” (Get Out of My ER) whose symptoms don’t merit further treatment, and pit bosses have the “small fry” of the low-stakes bettors. The more self-actualized VCs might protest that they see and recognize the need for small-market-size businesses, but the plain fact is that if you spend 50+ hours a week rejecting those businesses, you are training and wiring your neurons for disdain at a deep level.

No, it’s not a moral failing, but an arithmetic one: Fred Wilson has expounded on VC Math, and my former Voyager colleague, Dan Ahn, is fond of noting that he is being paid by his investors to make 10x home runs, not 3x bunts and 2x walks. Fred and Dan are right; VC as an asset class, as it’s been run, is a necessary part of well-functioning entrepreneurial finance markets, but it demands a certain immutable probabilistic rubric: bigger returns, infrequently realized.The gap, then, that VCs leave below their market-size threshold, and that banks are loathe to touch without hard collateral and personal guarantees, is a gaping void. This is the void of financing for non-venture, non-brick-and-mortar businesses that stares back at some of the best and brightest of American capitalism (and convinces many to turn away). Pace, Geoffrey Moore and colleagues, this is the new “chasm” of the 21st century, and if I may have license to be so bold, it is the challenge of capitalism’s next chapter in America. And it is this segment of businesses — the “tweeners,” beloved by customers but shunned by financiers — that my team at RevenueLoan has the unique opportunity to embrace and to serve.

Lloyd Blankfein, take a hike: it’s RevenueLoan, not Goldman, who’s really doing God’s work for the businesses that are America’s promise and future.

(Wow. Over-the-top, God-and-America talk aren’t my usual style; cynicism, punnery, and Steely Dan are my usual stock-in-trade. But I guess this is what happens when my observations, my passions, and yes, my personal financial interests, align.)

But seriously. Once upon a time, we needed our creative obsessives, our ambitious organizers, our painstaking engineers, and our masters of persuasion to pull together in only the largest of endeavors. Anything less than a well-funded corporation, with capital in the eight-to-nine figures couldn’t possibly build a railroad, a refinery, a department-store chain, or a sophisticated manufacturing operation. In short: twentieth century entrepreneurialism was enabled by, and shaped itself to the demands of, nineteenth-century capital.

Today, though, we live in an economy driven by choice. We’re (ostensibly) wealthier for it. That choice, that variety, is a function of more flowers blooming and more companies thriving, not of more capital pumped into the same few firms. We must not let the promise of capitalism in the twenty-first century be enslaved to the death-throes of the models of money-management of the twentieth. In fact, the smaller overall capital requirements for launch and success mark a shift in kind of investable company, even from the 1980s-1990s model of “minicorp” to a true “microcorp” model (hint: imagine that finance is 30-40 years behind the computing industry, which it probably is, and consider that the merchant-bank to VC change is the parallel of the mainframe to minicomputer shift of three decades prior).

The naysayers whose only refrain is “Made in America!” ignore the fact: Lenovo buying ThinkPad from IBM was not the end of American export manufacturing, but a shift in what we create for export: America now invents IP, brands, and reputations. And to keep up with it, the answer isn’t to throw in the towel on education, and demand that we artificially keep a manufacturing underclass on subsistence wages in domestic maquilladoras, the way that some (I suspect disingenuous) progressives seem to want. No, the answer is that we as a nation and a people must step up to the standard of living we have chosen, and we must better ourselves, an individual and a family at a time.

Economically, this is by serving the wants and needs of our fellow man, tabulated and calculated as best we know, via the free market. And it should not be limited to serving the imperatives of inflexible, legacy forms of concentrated capital that blindly chase scale and eschew invention.

I’ll say it: a slightly cheaper T-shirt does not improve the world.  Just-in-time manufacturing is a gimmick. Raping a city’s tax revenues to subsidize yet another bread-and-circus stadium is theft or worse. “Better” derivative trading of interest rate swaptions or forex futures does fuck-all for peoples’ lives.

But having racing wheelchair parts means a hell of a lot for athletes in wheelchairs.

And it means a hell of a lot to the guy who makes ’em and sells ’em.

And if NYSE, NADSAQ, VC, PE, BofA, and “C” can’t help them — then who will?

That, my friends, and my patient readers, is why RevenueLoan is important. We get to make it happen. And we will.

The Secret Trick of Portfolio Effect Dominance

Smart-as-a-whip VC Sim Simeonov did some math and some simulations and came up with the conclusion that a large “portfolio effect” has a major, almost overwhelming, effect on the financial returns of e.g. angel and seed VC portfolios.

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 😉

Can a VC sit on more than 10 boards without f***ing up?

[Update: the conversation referenced below was with Scott Austin of the Wall Street Journal; he has written an article about the subject. In it, he quotes some VCs that have well over ten board seats, including Forest Baskett of NEA. I know Forest only through his and his firm’s reputations (both stellar), and I emphatically do not mean to impugn his board service, commitment, or professionalism. That said, I can’t back down from the math below and I must suggest that overloaded VCs necessarily give some of their boards short shrift.]

I had an interesting conversation today about VCs and board seats. The essential question is: how many board seats is too many?

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).

VCs passing for “soft” vs. “hard” reasons

I recently made the choice (mistake?) of telling an entrepreneur, whose business I actually liked and respected, the real reason why I was passing on investing at the time.

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.)

Newest source of entrepreneurial financing: the dole

From the VC grapevine comes word of a new innovation in startup funding in Portland (and elsewhere), Oregon: the unemployment department

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.

One-click Unsubscribe: For ALL Your Emails

I sign up for (let’s call it) 5-10 new web sites a week. It’s an occupational hazard.

(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).

The Downturn, REAL vs. FAKE VCs, and REAL WEALTH

In early October 2008 I was asked by a local entrepreneurial booster group for a quote giving VCs’ take on the state of the financial world. Here’s what I wrote (but was too busy/lazy to blog) at the time:

  • 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.

Hint: Nobody Has Any Idea How This Thing Works

In Venture Capital, we have lots of rules of thumb for assessing entrepreneurs. Some such rules are:

  • 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.)