Beware, what follows is a post on startup financial modeling/ analysis. Bear in mind, I have no formal finance education. Proceed at your own risk. You asked for this.

(((𝕐𝕠𝕟𝕚 ℝ𝕖𝕔𝕙𝕥𝕞𝕒𝕟)))@yrechtman

Would people want to read a blog post about how I evaluate/think about unit economics and biz model sustainability or is that too VC inside baseball?

April 26th 2019

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When a startup gives you numbers, how do you assess what’s real, what’s good, what’s bad, and what’s possible? How should you think about not just how the business looks like today, but what could it look like in the future? It takes critical thinking, good judgement, and some pattern matching/experience. But to put that thinking to work, you have to first be able to structure your thoughts and see the picture clearly.

There’s tremendous value in model making as an analytical rather than predictive tool. 

When I’m modeling, my goal is usually not to determine what will happen, but rather to understand what would need to be true for something to happen. To my mind, the point of modeling is to ask and answer questions rigorously, and to be explicit about your assumptions. Putting things into numbers and breaking processes into discrete steps forces you to be specific in your thinking and with the story you’re telling, even if the numbers and steps are themselves unspecific.

Because startups are money-losing growth machines by design, lots of traditional financial modeling just doesn’t apply. Too often that means overcompensating and looking at top-line performance absent any more rigorous analysis of what I think of as “sustainability.” Is the growth healthy? People throw around all kinds of terms to asses the health and sustainability of startups. I think it’s mostly bullshit and doesn’t capture or describe anything meaningful.

I’ve found myself increasingly creating models (which again are thinking frameworks rather than predictive tools) to blend together all the various top-line figures into a more-startup oriented version of indicative health. I like to think about things in terms of payback in particular.

To understand why, I’ll use Harry’s as an example.

(Note: all the numbers here are waaaaay off and if this were a real example, there’d obviously be more detail. I’m illustrating a general concept, not proving a specific point.)

Harry’s baseline razor subscription costs $9 per shipment. Let’s assume that the average customer receives 6 shipments before cancelling and that it costs Harry’s $40 to acquire each customer. So each customer represents $54 in revenue and $40 in acquisition costs. Great news! For every $1 you spend on marketing, you get back $1.35 in revenue, a healthy LTV/CAC ratio (lifetime value/customer acquisition costs). You can check the glossary at the bottom for some definitions of terms:

But wait, you might ask, making, storing, and shipping all razors has to cost something too, right? Right. So let’s say all those various supply chain and logistics costs, eat 40% of the revenue (in reality for Harry’s it’s probably closer to 20%). That would mean that Harry’s only keeps 60% of the revenue from each sale, representing $32.40 over the life of each customer. Not as good as it could be but not too shabby…

This is where the math would break down. If each customer is only really worth $32.40 to Harry’s and Harry’s is spending $40 to acquire them, that’s pretty obviously unsustainable. And this is even assuming you know for sure what the customer lifetimes are. Really by the time you do know that, you’re probably not dealing with an early stage startup anymore. So the question becomes “what would have to change for this business to work?”

Here is the general framework I like to use to see all the levers in one place and begin thinking about that question:

To get that lifetime payback (think or this as CAC-burdened lifetime contribution margin or revenue minus acquisition costs minus the costs of the razors, shipping, etc.) into the black, Harry’s could:

1. Increase order values, either by raising prices or introducing add-on products

2. Improve contribution margins by lowering some supply chain cost (this is where the line items that make up CoGS matters a lot)

3. Extend customer lifetimes/improve retention

4. Lower CAC through better paid marketing or more organic growth

Obviously some of those are easier or more feasible than others. Some may tend to “naturally” (usually that really means a lot of hard work) improve over time and with scale while others may get harder or even worse over time. Where are the reasonable upper limits? What could this reasonably look like? What’s normal? What do we care about? Is this concerning?

There’s no “if X > Y then I must invest” shortcuts or hard and fast rules.

This is where it stops being “financial modeling” and becomes a more creative/intellectual/interesting exercise. But to get here and to be able to answer any of those questions with any semblance of legitimacy and analytical rigor, you have to first ground yourself in a framework. Otherwise it’s just hand-waving. That’s the ultimate point of the exercise.

What this framework also suggests is that to survive, a startup has to be great on one of those levers and to really thrive, it has to be great on two or three. So when I look at a startup, I want to understand where they are today and where they can get on each. Does the prospect of a super sticky product make me relatively indifferent for CAC? Can the margins be strong enough to support low AOVs? So on and so forth.

With the appropriate tweaks, this general framework works just as well for consumer startups well outside of subscription CPG. I’ve found it helpful for understanding startups with depreciating assets, lease obligations, software/virtual subscriptions, and one-off/irregular (non-subscription) purchases, etc. And it can work in reverse as well, not just on a per-user basis. Here’s the same type of unit economic model for Rent The Runway:

We’re not talking about top-line growth, and certainly not cash flow or EBITDA. Even once all the numbers in this type of model look good, startups still have to pay their employees, and rent, and lawyers, and consultants, and health benefits, etc. I’m not concerned about profitability as an early stage investor. I care about a path to profitability. Anyone can produce great looking growth by burning enough money. Getting to sustainability is another matter altogether.

To make sense of that and understand it in a meaningful way, you first need to do the work of modeling out both the facts as you them and your judgement as you perceive. Then you can start bending and breaking and hopefully get somewhere.

I’ve put the above models into this Google Sheet. Hopefully I can get around to adding more types of payback models. In the meantime, I would love to hear people’s alternative takes on this.

Am I dumb, wrong, or just pointing out something obvious?

Quick glossary:

• AOV: Average order value. How much a customer spends on average each time they buy.

• LTV: lifetime value (sometimes CLTV for customer lifetime value). The total amount of money a customer spends over all their purchases: AOV x number of purchases.

• CAC/CPA: customer acquisition cost or cost per acquisition. How much it costs (in advertising spend, referral codes, etc.) to get a new customer. These numbers can mean slightly different things in practice but I’m using them interchangeably.

• Payback period: the amount of time or number of purchases until you’ve paid back your CPA.

• CoGS: cost of goods sold. The cost not just of buying/manufacturing some item but also all the associated variable costs of selling it like storing, packaging, and shipping it.

• Contribution margin: the amount of revenue after accounting for CoGS.

• Depreciation: how much does the value of something (like a car) decrease over time/with use.

• Lifetime payback: this is the metric I’m making up, which works either on a lifetime or transactional basis. It measures (lifetime) revenue minus CoGS minus acquisition costs.

A couple weeks I got into a vicious, heated argument with a dear friend. We were shouting at each other about antitrust, internet governance, and the centralization of the American economy for 30+ minutes. Yes, I know, I’m a great hang.

Over the course of that conversation, a couple of ideas really came into focus me - almost like a lightbulb going off. To get there, I want to first set the table of the debate:

I was my making the case to my friend (let’s call him David) that economic centralization is a bad thing because it forces us to rely on the unilateral judgement of a very small group of people. When firms get too powerful, they can squash competition and bend markets to their will. And make no mistake, I said, our economy has gotten more concentrated and less competitive.

This figures to get worse over time as the world moves toward a more technology-driven economy where network effects compound the returns to scale.

Moreover, I said, when we have so few and such powerful firms, if any one of them fails (either by going under or by making some choice with catastrophic social impacts) the consequences would be massive. Why should we expose ourselves like that? I’ve made this case before, here in 99D in Free Speech and Fuckery:

the internet collectively decided that Neo-Nazi site The Daily Stormer would be no more. It was de-listed from Google, kicked off its cloud provider, and blocked from most of the conventional/consumer internet. That time was easy. We all agreed that the Daily Stormer was awful and best erased from the world. It won’t always be this simple […] When a rogue twitter employee temporarily suspended Trump’s account as an act of protest on his or final day, it brought this brewing problem into sharp relief once again. This was an aberration caused by poor internal controls but it nevertheless illustrates a point: single private actor (be it an individual employee or the company itself) could silence the President’s primary method of communication with a keystroke. We’ve let individual judgement become the sole arbiter of free speech. We’re betting a lot that we’re making the right call and we haven’t done much to prove it.

The problem isn’t Twitter or Facebook or Google on their own.

The problem is that we have functionally ceded the public square to a few private companies.

Better, I said, to spread that risk around by having more competitive markets with less powerful individual actors. If you wanted to make a portfolio of stocks, you certainly wouldn’t buy just one, but buying 5 or 10 isn’t that much better. The same is true for decision making or economic power. To de-risk the system, you need to spread that risk around.

David, on the other hand, argued that too much competition is not only inefficient because it creates waste on fixed costs and spurs firm-killing price wars but also because it increases systemic risk by allowing anyone other than the best and brightest minds to wield power. This is similar to the concept of “Ruinous Competition” popular with 20th century monopolists like Carnegie, who’s not exactly famous for his benevolence and sense of fair play.

For David, we have to trust that our oligopolistic technology firms will not abuse their power as free speech gatekeepers and arbiters of right and wrong. Better them the government or the mob. Large groups move slowly and chaotically, he said. Government can’t be the one regulating speech and competition because it’s too incompetent, too dysfunctional, too damn slow. When it comes to big complex issues, we need decisive action not political grandstanding from the government or mob reaction from the whole population, right?

Finally, David made the case that even if you could unwind some large firms or prevent the big from getting bigger, it would diminish the power of the internet. You’d kill what you’re trying to save. “LinkedIn would be worthless if there were 10 or 20 different LinkedIns,” he said, “the value is in the centralized, dominant network.”

“What if it’s a false choice?” I asked. “But what about email?”

This is when the light bulb went off.

Email is the perfect system precisely because no one owns it. Email is not a company or a platform like Facebook or AWS. Rather, email is a protocol (called SMTP or Simple Mail Transfer Protocol). A protocol is like a rulebook that describes a series of standards and practices.

Everyone building an email system relies on the same rules so, unlike private messaging systems like Instagram Messenger or iMessage, email is fully interoperable across systems. You can send emails from a Google account to a Microsoft account to an AOL account because they are all built on the same open and publicly available protocol.

Anyone can build their own application (email service) with unique features on top of that protocol but the basic organizing principles are the same, ensuring decentralization does not come at the expense of interoperability or functionality. The protocol itself is maintained by a non-profit which makes decisions through consensus between its members. That’s probably not an ideal process but it sure is better than the voracious thirst for shareholder value by any means.

Why should it only be email that works this way? What if instead of 1) screaming into the void at Jack Dorsey to get Twitter to ban white nationalists 2) debating the relative merits of banning or not banning them or 3) trying to migrate Twitter’s users en masse to a separate platform that wouldn’t tolerate racism in the first place, Twitter users could simply use different, interoperable clients with their own rules, features, and moderation. What if Twitter were a protocol rather than a service?

If that sounds ridiculous, recall that that’s basically how Twitter functioned for the first several years of life before it began restricting developer access and shipped its own native mobile app. The same is true of Facebook, albeit in a different capacity.

In the very first post on the new 99% Derisible site, I wrote

Most dating apps are basically a thin application layer built on top of existing Facebook apps, data, and services. Tinder works so well because it has such wide reach/network effects (see: Metcalfe’s Law). It has such wide reach because the onboarding process is nearly seamless. The onboarding process is so good because Tinder has access to Facebook’s user data. Tinder takes your pictures, likes, demographic data, friends (social graph), and profile information from Facebook and Instagram for profile creation and matchmaking. 

So it doesn’t seem impossible or even far-fetched that the social graph and underlying user data/content for social networks could be made available and interoperable via a protocol rather than a gated, centrally-controlled developer platform. If Facebook, for example, were a protocol rather than a platform, social networking could become decentralized without losing the network effects of having everyone able to connect with everyone else.

Individual clients/apps built on top of that protocol could make content policing decisions and build new features on their own (just like email), minimizing the risk of any disastrous fuck ups by ultra-powerful and largely unaccountable oligopolists. But it’s so much bigger than Facebook or social media or even communications overall. What if everything, our whole economy could be similarly decentralized?

This is when I went full galaxy brain.

Wait a minute, I thought to myself, why does this suddenly sound so familiar?

Without meaning to or even realizing what I was doing, I had basically made a full-throated and impassioned political, economic, and moral case for cryptocurrency and blockchain.

I had previously been so limited in my thinking about crypto just as an asset class, rather than a governance mechanism or infrastructure design. What if we didn’t have to choose between regulatory wack-a-mole and internet governance by billionaire fiat? What if we could directly incentivize people to work on the protocols that would replace the centralized platforms rather than relying just on their goodwill?

It’s usually the crypto crazies spouting off on the necessity of trust-less institutions, decentralized authority, and distributed systems, not normal people like me.

And yet, once I began thinking in these terms, it suddenly seems ludicrous to entrust the management of our entire economy to the 12 governors of the Fed board. At least with a decentralized currency/store of value (like Bitcoin), we can minimize our risk and lesson our dependence on the decision making of a few people because every bitcoin holder has proportional say in monetary policy. There are not just 12 points of failure (functionally a single point of failure).

I truly have no idea whether prices will go up or down, whether cryptocurrencies today are a financially viable instrument, whether the underlying technologies are sound, or whether anyone will adopt enough of it to matter one way or another in 25 years. What I do know is that it has the theoretical/rhetorical potential to enable the kind paradigm shift towards a more competitive and less risky economy that I was advocating for.

That on its own is really exciting to me.

Special thanks to Mike Demarais for being my spiritual guide on my journey to galaxy brain bitcoin maximalism.

McDonald’s doesn’t sell food. At least not to anyone that eats it. McDonald’s sells raw ingredients, software, and a brand to small business owners via franchising deals. By building a highly sophisticated supply chain, ginning up demand through marketing, and establishing exacting standards for what a McDonald’s meal and location should be, McDonald’s sells inventory, demand, and operating capacity to its franchisees, who in turn sell food and heart disease to you and me.

This is great for the Golden Arches. They don’t need to own or even run all their locations. They don’t need to hire and manage all those employees. McDonald’s just needs to optimize its “McDonalds Platform,” so to speak. It’s not fundamentally dissimilar to Uber’s relationship to drivers, to whom Uber sells demand, software in the form mapping/routing tools, and “ingredients” like auto-loans and income factoring.

Now the maturity of software as a service (renting cloud-based software rather than buying software to install locally) and the relative green fields in capital intensive areas that are traditionally difficult for startups to launch in will make/is making franchising or “business in a box” a very attractive prospect for venture investment and entrepreneurs.  I’m seeing this across a ton of concepts and industries and I think it’ll be the next “DTC” in terms of business model hype.

These opportunities go far beyond sharing/gig economy platforms. There’s opportunities in high skill white collar work on one side (medicine, law, tax, financial advising, etc) and then SMBs (home services, retail, nursing care, etc) on the other. I’m seeing this everywhere from cannabis dispensaries to dental care.

A founder might say “instead of opening a One Medical style clinic, I’ll build practice management software, a brand, and lead generation and sell that to people looking to go into private practice.”

Certainly part of the appeal is “enabling entrepreneurship” by letting you “be your own boss” but I think the real motivation is somewhat to the contrary. Doctors often don’t want to be entrepreneurs or deal with vendor management. They want to practice medicine. The same is true in lots of SMBs, I think. Consolidating those functions via a franchise makes sense for the franchisees and allows startups to innovate services (not just delivery mechanisms) more capital efficiently in traditionally cost-prohibitive markets.

The most promising opportunities that I’ve seen/can imagine are defined by a few common characteristics:

1. A long tail of SMBs making up the bulk of the market

2. Geographically-constrained businesses that cannot reasonably be virtualized or otherwise directly consolidated

3. Little to no brand affinity or modern brands at all

4. There has to be some level of organizational, logistical, compliance or supply-chain complexity that a) yields meaningful benefits to scale and consolidation and b) provides for defensibility

Let’s unpack that all a bit, using lawyers as an example. 

1. There are 164,000 law firms in the US and nearly 80% of them have 4 or fewer total employees (including non-lawyers). (Source) 

2. A startup cannot legally practice law as only attorneys can hold equity in a law firm

3. Have you seen small law firms’ ads? Come on.

4. These lawyers are responsible not just for practicing law but also for finding clients, managing billing/receivables, scheduling meetings, doing CPE courses, etc. Lawyers only spend about 29% of their time on billable hours. (Source)

So what if you could pair practice management software with a marketplace/lead generation platform, workflow tools, and CPE offerings to allow lawyers to operate locally under your brand? Theoretically, franchising allows franchisees to increase revenues in relatively fixed-margin businesses while allowing the franchisor to enjoy the SaaS margins and growth trajectories attractive to startup operators and investors. Franchisors can scale beyond geographic constraints/footprints and get more leverage from investing in technology, while more widely sharing the fruits of that investments with their customers, the franchisees.

And, crucially, this is not merely the same as selling an industry-specific SaaS offering because a franchisor creates a brand halo for its franchisees. You buy from Kylie Cosmetics not from Shopify, whereas you stay in an Airbnb not at Steve’s house.

For many companies, I believe franchising will be a path to expansion rather than a business on day one, at least for now. This will be especially true for the new class of physically based healthcare startups (like Tia and Stella) in the short term but it will radiate out from there into more “tech-enabled” categories quickly. Starting native/full stack provides you a sandbox to “eat your own dog food” and build your tech/brand before you try to go sell it to anyone else. Arguably that’s what Atrium is doing in law.

The competitive incumbents for a lot of these companies will likely be transactional marketplaces, which, though capital light, cannot adequately control quality. In many categories, marketplaces may be products franchise companies offer their franchisees, rather than standalone companies in their own right.

Yes, I know McDonald’s operates about 15% of its own storefronts. No that doesn’t undermine my general point.

• Try: Stoop, a newsletter reading app that consolidates your subscriptions into one well designed interface. I’ve talked about my admiration for Substack’s creator-facing newsletter tools before, this feels similar but for readers. Seems like a good example of “do one thing right.” (Download)

• Watch: Umbrella Academy. Good superhero show that doesn’t treat you like a dummy. (Trailer)

• Watch: The Inventor, HBO’s Theranos doc that just came out. It’s a great hang but also terrifying it you’re even remotely close to the tech industry. (Trailer)

• Listen: to My Finest Work Yet, the new Andrew Bird album that frankly lives up to the name. 

As we all know (probably not, most likely only the terrible few of us who pay attention to such crap) there’s a big glut of IPOs coming. Lots of companies are gonna go public very soon. I’ve been thinking about dipping my retail investor/degenerate gambler toe into those frothy waters. In particular, Uber and Lyft are both going public and I want in.

Long term, I really think Uber is the better company. I like Uber’s strategy of pursuing an overall transit/logistics marketplace and generally think that the whole is more valuable than the sum of its parts. Ben Thompson, using a “jobs to be done” framework, provides a very good argument for why but it basically boils down to this: things need to get moved and the job to be done is moving them. Therefore, the more ways you have to move things, the more liquidity you have/value you can provide and the more types of things you can move with that liquidity. It’s why Uber has gotten pretty good at delivering food and why they want to get into public transit. Multi-modal transit! So Uber is more forward looking, has better network effects, a more interesting business model, and an overall bigger business.

And yet, I’m not going to buy Uber. I’m going to buy Lyft.

Allow me to explain:

The last point is the key. Uber is much, much bigger than Lyft (5-10x bigger depending on where IPO prices shake out). Neither company has a path to profitability in the short/medium term. As a result, investors are really just buying top-line growth for now and for the foreseeable future. So the law of large numbers would dictate Lyft is a better short/medium term buy because it has more room, on a percentage basis, to grow.

This is borne out in Uber’s semi-public financial statements:

Conversely, per the company’s S-1 (a legal filing to go public), Lyft’s market share has basically doubled in the last two years. If you’re just buying percentage growth, smaller seems better, no?

The MBA Myth and the Cult of the CEO - Dan Rasmussen & Haonan Li, Institutional Investor

This is long and a bit math heavy but well worth it:

Journalists, investors, and boards are placing excessive emphasis on CEO pedigrees and track records. In a world that is feedback-rich, stochastic, and “fat tailed,” the simple narrative of the “great man” does not appear to have much quantitative merit — rather, it seems like yet another cognitive bias in the vein of those discovered by Daniel Kahneman.

Of course, we cannot prove that CEO credentials don’t have an effect on share price. It’s impossible to prove a negative — what statisticians call a null hypothesis. We are simply pointing out that there is no convincing evidence in favor of rejecting that null hypothesis. U.S. companies adopted Jensen’s ideas without any data suggesting that incentive pay would actually result in better stock price performance — and no evidence to suggest Jensen’s thesis was correct has emerged in the 29 years since that great experiment began.

When Did Everyone Become a Socialist? - Simon van Zuylen-Wood, New York Magazine

Anyone who is Very Online has probably seen that everyone who’s anyone is also now a pinko. This article uses the Brooklyn DSA social scene as a window into the group’s origins, ideas, and future. Sarah Leonard, one of the people profiled, was my professor for one semester at NYU, an anecdote I hope will make for a funny aside in a book about me one day.

In the middle of the dance floor I ran into Nicole Carty, a DSA-curious professional organizer I also hadn’t seen since college, who made a name for herself doing tenant work after Occupy Wall Street. (DSA can feel like a never-ending Brown University reunion.) “Movements are, yeah, about causes and about progress and beliefs and feelings, but the strength of movements comes from social ties and peer pressure and relationships,” Carty said. “People are craving this. Your social world intersecting with your politics. A world of our own.”

DSA is led by its dues-paying members, rather than paid staff. It is, essentially, bossless. That has allowed the organizers to reflect back to those members the world they’re trying to create. “It’s playing the role of a place where they seek a sense of fulfillment and rootedness that they otherwise lack in their lives,” says a writer acquaintance, Sam Adler-Bell, yet another Brown graduate and a DSA member. Socialism was appealing not because it promised equality but because it looked like liberation.

I am pretty opposed to proper socialism (longer discussion) and don’t feel super duper into the brand of democratic socialism described here but I would sure as shit rather work my neoliberal dark arts against a socialist to bring them closer to the center than try to survive another term of Trump. So if this really is what is gonna energize voters - and I think it might be - I’m here for it.

A Basketball Star Is Taking 100,000 Shots This Year. She’s in Sixth Grade. - Ben Cohen, Wall Street Journal

The app has recorded millions of shots from players in NBA, top colleges, high schools, middle schools and even the odd elementary school in 6,800 cities and 150 countries. But few players anywhere in the world have logged as many shots this year as Lanie Grant.

“It helped me be more confident about myself,” she said last weekend over chocolate milk at Starbucks . “It opened up my entire game.”

There is no other way to put it: Lanie got really, really good.

Lanie took nearly 5,000 shots in her first three weeks using the app and made 65%. Lanie has taken about the same number of shots over the last month. Now she’s an 85% shooter.

Why Do so Many Egyptian Statues Have Broken Noses? - Julia Wolkoff, Artsy

His training in Egyptology encouraged visualizing how a statue would look if it were still intact. It might seem inevitable that after thousands of years, an ancient artifact would show wear and tear. But this simple observation led Bleiberg to uncover a widespread pattern of deliberate destruction, which pointed to a complex set of reasons why most works of Egyptian art came to be defaced in the first place.

Why Apple AirPods Came to Be Everywhere - Jon Wilde, GQ

I think, the reason for the slow path to everywhereness that Apple’s AirPods have taken. They may be the best-selling product Apple makes right now, but they’re also the ones that most require word-of-mouth, or a leap of faith. With them, Apple fixed the annoying things about wireless headphones, which you didn’t realize could be fixed until you bought a pair. And Apple made the act of using those headphones tactile and satisfying and sometimes surprisingly delightful, but you wouldn’t know until you splurged on a pair. You need a beta-tester friend to rave a little before you make the leap. I’m not saying you should do that if you haven’t. But I am saying you’ll enjoy the hell out of the lid.

In VC, like most everything else, ultimately the only thing that matters is points on the board. That’s certainly not measured by sourcing opportunities and it’s not even measured by making investments (gimme that DPI, baby!). But having some kind of KPI along the way is valuable to at least hold yourself accountable and keep improving.

So here’s some direct insights from my deal activity to hold myself accountable:

With some simple pipeline analysis on Affinity, I found that in 4Q 18 I sourced ≈1.25 new deals/day. That’s held or gone slightly up thus far in 1Q 19. But the rate at which I’ve socialized deals internally dropped from 36% in 4Q 18 to just under 12% in 1Q 19.

Am I seeing lower “quality”/less aligned opportunities or has my screening gotten too tight?

That’s tough to answer and the truth is likely in between. The easiest way to start testing this is to compare the industry breakdown over the two periods. But there’s not meaningful change so that doesn’t explain anything. But a null hypothesis doesn’t seem right; the Ns are sizable and the delta is so big.

Even if you chalk this up to some messy data and haircut the delta by 50%, you’d still be looking at a ≈33% decline. Something is different.

So what’s going on?

Here’s what I’m thinking: this is very hard to precisely quantify without more work than I want to do, but my outbound sourcing volume has decreased even as my overall deal volume has demonstrably remained flat or even increased. So more stuff is coming to me even though I’m doing less work to see it. Sounds like a good deal right?

Wrong. If socialization reflects quality, quality has gone down. It's plausible that the best stuff I see, I see because I find it proactively. So even if it appears more efficient to let deals come to me, I have to be actively hunting to find and get access to the best stuff.

In short no one will do your work for you and I wouldn’t want to be a member of any club that would have me.

There’s a number of potentially confounding variables (especially the work I’ve been doing with pre-seed/founding companies) and I can explain how I define terms (just sending a cold email doesn’t count as seeing a deal) but certainly this gives me a lot to think about.