The Open Startup Pro-Forma Capitalization Model

TL;DR: In the earliest stages of a startup, paying for a proprietary cap table tool, or simply dealing with the hassle of a 3rd-party intermediary software layer for modeling your capitalization, is not really necessary. We’re publishing the Open Startup Model, an Excel-based “open source” cap table and pro-forma that startups and their lawyers or other experienced advisors (if they don’t already have their own tools) can use for free. It’s based on the pro-forma structure we’ve used for hundreds of deals, and is flexible, editable and auditable.

Background reading:

In the beginning, there was Microsoft Excel, and it was good (enough).

For decades, startup cap tables and pro-forma financing models were maintained on Excel. It wasn’t perfect (nothing is), but it worked well enough. Then as the ecosystem matured, we saw the emergence of specialized cap table software, like Carta (pricier incumbent) and Pulley (leaner alternative). These tools make a lot of sense at moderate (not low) levels of cap table complexity – based on our experience at Optimal, typically around Series A or post-Seed.

But somewhere along the way some founders got the impression that these tools might be needed as early as the incorporation of the company, when there are only a handful of people on the cap table. The argument, certainly made by the cap table software vendors themselves, is that Excel is too clunky, and too error-prone. There is also a land grab dynamic here, in that it isn’t necessarily profitable for these tools to have tons of very small companies on them, but they have to build super early-stage offerings to prevent their competitors from owning the pipeline. There’s no simple way for the tools to agree to leave young companies alone, so we get these silly value-destroying attempts to onboard everyone.

All of this is, candidly, nonsense. I’ve seen seed-stage companies spending thousands of dollars a year and getting absolutely nothing extra of value that they couldn’t get from a basic excel spreadsheet maintained by someone moderately competent.

What makes old-school Microsoft Excel a still-used tool in startup finance is its flexibility, auditability, simplicity, and affordability (free, essentially). It’s really only once you’ve crossed about 20 cap table stakeholders that in our experience, as counsel to hundreds of VC-backed companies, a third-party tool starts to make sense. Before then, I often see more mistakes when founders try to use an inflexible outside tool than when they simply collaborate with a sharp outside advisor to keep things clean and simple on a spreadsheet.

That being said, one thing that has happened is the complexity of seed funding instruments has grown over time. See the Seed Round Template Library and Seed Round Educational Articles.

In the really early days, before the entire seed ecosystem even existed, most financing was in equity rounds. But as the SaaS revolution got started, financings both shrunk in size and exploded in volume, with equity rounds no longer making sense in many cases. So we got seed-stage convertible notes. Then we got notes with pre-money valuation caps, discounts, or both. Then you got pre-money SAFEs. Then you got post-money SAFEs, and various flavors of them. Then you got post-money convertible notes. Time-based discounts and caps. Milestone-based caps. Don’t forget friends & family SAFEs, which are slightly different. Oh, and let’s not forget seed equity v. NVCA equity. Even within these categories there are various nuances and flavors.

It is not surprising to us at all that the ecosystem has resisted all attempts to hyper-standardize fundraising instruments, notwithstanding the valiant (even if self-interested) attempts by high-profile VCs or software tools to centralize all fundraising terms. This reflects the decentralized reality of the startup ecosystem. Startups are not uniform commodities, nor are their investors. In the latter category, think of bootstrapping, friends and family, angels, super angels, angel syndicates, pre-seed funds, seed funds, family offices, crowdfunding, accelerators, VCs with seed fund arms, strategic investors.

Couple that organic diversity on the investor side with the extremely diverse industries, business models, geographies, team compositions and cultures, risk tolerances, and exit expectations of startup companies. Do we really expect all of these sophisticated business people playing with millions and tens of millions of dollars, gunning for hundreds of millions to billions, to fit into one or two template financing structures because some VC, accelerator, or cap table software says they should? Because of some childish aversion to actually reading a contract and tweaking a few terms?

The only people misguidedly trying to hyper-standardize this complex ecosystem are (i) specific VCs who profit from controlling terms, with their preferred templates, and (ii) specific software companies (often funded by the aforementioned VCs) who want to build some centralized proprietary tool on which all startup financing would at some point become dependent (surely with juicy margins to them as a result). Neither of these types of rent-seeking gatekeepers are looking out for the ecosystem itself, and its diversity of preferences and priorities; certainly not for entrepreneurs. They’re looking out for themselves (for which, as market actors, I don’t fault them).

Many entrepreneurs and startup teams in particular have lost huge amounts of equity and money by being misled into signing inflexible contracts that they thought were “standard,” but really aren’t. The smallest bit of tweaking and negotiation can produce enormous differences in financial outcomes.

Given the diversity of businesses and investors in the startup ecosystem, which inevitably leads to a diversity of funding instruments, flexibility of any viable wide-reaching startup capitalization model is key. That’s why MS Excel still matters, because of how flexible it is. Flexible and transparently auditable in the way that open source code is flexible; and proprietary “no code” tools are not.

Led by a Partner colleague of mine, Jay Buchanan, we’ve published the Open Startup Model. Free, Excel-based, flexibly customizable and auditable, even “forkable” if others want to iterate on it. “Open Source” effectively. It’s based on the same model we’ve used hundreds of times at Optimal, with clients backed by elite VCs like a16z, Sequoia, Accel, Khosla etc. and dozens of “long tail” funds across the world as well. It works from the formation of the company through Series A (or a Series Seed equity round).

Jay will be writing periodically at OpenStartupModel.com, with info on how to take better advantage of it. Just like open source code isn’t intended to be handled by untrained end-users, this model is not intended to be entirely self-serve by founders. We are modeling very high-stakes and complex economics here. Rather, it’s meant to be a potential starting and focal point for various experienced market participants (including lawyers) to work with founders on.

Just as we are big believers in the thoughtful integration of elite legal industry values and lean tech values, we think an “open” startup ecosystem, with its enormous organic diversity of market players, is far healthier and more sustainable than misguided attempts to centralize everything behind a handful of rigid proprietary structures and tools. An open pro-forma model, together with our open-source contract templates that we’ve published here on SHL, is part of that vision.

In that vision, it’s not necessary that dozens of different actors come to agree on some “standard.” These templates and models will look extremely recognizable to all the serious law firms and other key players in the market. That alone saves time if startups or lawyers want to use them, and as institutions get more “reps,” efficiencies follow as institutional knowledge is gained.

We hope everyone – founders, lawyers, investors – will find this helpful, and welcome any feedback on improving it; particularly if “bugs” are found. As a final legal tech tip for lawyers, the ability to redline excel models, much like how you redline contracts, is super important and improves efficiency in reviewing model changes. Litera Compare is our favorite redlining tool for excel files.

As a separate tip for startup founders, if you need a 409A valuation, but don’t want to pay extra for a third-party cap table tool (because Excel is fine for now), Eqvista and Scalar have lean 409A-only (no extra software) offerings.  Some seed-stage companies go this route, combining Excel and a 409A valuation without the extra bells and whistles of the pricier cap table tools, until their cap table has grown more complex (typically post-Series A).

Finally, once you get to the point of needing to onboard to Carta or Pulley (if you’re successful, you will get there eventually), the following may be helpful for saving on their costs.

Startups, Politics, and “Cancel Culture”

I wrote The Weaponization of Diversity a little over a year ago. It was a combination of both my personal story growing up as a low-income latino raised by a single mom and eventually making it into the elite strata of the legal profession, combined with a more philosophical expression of how I see a lot of the rhetoric around diversity initiatives in high-stakes fields (law, startups, tech) leading to counter-productive consequences. It is an extremely complex, sensitive, and nuanced issue that doesn’t lend itself to easy summarizing, but nevertheless a quick break-down of my viewpoint is:

A. Growing up in a low-income Texas neighborhood filled with American latinos, but excelling in advanced coursework from an early age, I was criticized regularly by latino peers for my discipline in academics; referred to often as a “coconut” (brown on the outside, white on the inside). This was a tacit acknowledgement that my family’s home culture was a very different “Mexican” from what American latinos themselves consider the norm.

B. History and geography have led to various selection mechanisms that have made cultural values, including about early academic effort in childhood, significantly varied across ethnic groups in America. That variance correlates dramatically with relative performance and representation in high-performance careers, most of which are reliant on compounding education and skills; and in the case of the highest risk careers (like entrepreneurship), generational building of wealth and resilience.

C. With respect to American latinos specifically, the strata of latin american populations that place a high emphasis on advanced education are far more likely to stay in their home countries, with lower-income and working class latin americans far more likely to emigrate to the United States. The exact opposite dynamic has been the case for the most successful ethnic groups in America, such as Indian or Taiwanese Americans, who on average place extreme emphasis on childhood education. Nevertheless, pockets of very successful sub-cultures within under-represented broader groups in America  – like Nigerian and Cuban-Americans – reveal how ascribing low representation to racism in high-performance industries is too simplistic, and how family culture is a significantly under-discussed variable.

D. Our unwillingness to allow honest people to bring issues like this up in diversity discourse, and instead weaponize accusations of racism against anyone who won’t toe the dominant line, has caused the entire discussion to stagnate around more politically correct, but far less impactful policies; like “trying harder” to find qualified candidates.

E. Large organizations with dominant market positions are privileged in this whole dynamic relative to smaller orgs facing extreme competition (like startups), because a substantial buffer of resources allows them to absorb the negative consequences of non-meritocratic recruiting (while enjoying the PR benefits) without substantially threatening their companies.

F. Very elite orgs with attractive compensation packages (including equity) are also privileged in that they can attract the more limited number of high-performing URMs in the market, even when “inclusiveness” has nothing to do with why URMs join those companies. Thus the logic that “greater diversity (in the sense of more under-represented minorities) leads to higher performance” often gets the causality backwards, in that the (already) best companies can use their weight to recruit away high-performing URMs from lower-performing companies.

G. There is also often a sleight-of-hand with the term “diversity” because much of the data on high-performing diverse teams is not speaking specifically about URMs, but about a broader definition of “diverse.”

H. While the high-performance startup world is extremely diverse in the broad sense of the term “diversity” – including all nationalities, ethnic groups, gender and international diversity – it also reflects the under-representation of specific groups (including American latinos) that we see in other fields like law and medicine.

I. But unfortunately the fierce competitiveness of early-stage business competition, and the lack of buffer resources that large organizations have, make startups unable to play the politically correct politics of larger and more elite orgs. They simply cannot afford to hire – especially among their executive teams – for anything other than merit, and yet they can’t compete on compensation for the high-merit URMs who are taken up by A-level companies. This makes the more nuanced aspects of the diversity discussion unavoidable when discussing startups.

J. Just as in other areas of the economy, overly aggressive “diversity” initiatives – like diversity startup accelerators – have unfortunately in many cases backfired, with highly visible under-performance of the teams/people actually reinforcing negative stereotypes. Failing to address the real (even if uncomfortable) issues thus hurts, instead of helps, many under-represented groups.

K. Politicized warmongering over diversity, instead of balanced and fair discussion, is thus not only damaging to under-represented minorities like American latinos, but it’s particularly damaging to highly competitive early-stage startups in ways that it’s not for larger businesses.

The point of this post is to tie the above perspective into another issue that has been coming up lately; “cancel culture” and political disagreement within an employee roster. Some very large tech companies, like Apple and Google, are known for having pockets of employees who are extremely politically vocal during their employment hours, and in some cases have even gotten other employees fired not because of any behavior by the terminated employees on the job, but because of what amounts to disapproval of political values or other issues. Thus one segment of the employee roster “cancels” the hiring of someone that they don’t want to work with.

In response to this issue of hyper-politicized employees, companies like Coinbase and Basecamp have come out with clear policies that attempt to shut down this dynamic, by emphasizing that work is for work, and that political discourse should be left out of it. This has understandably led to – and they knew it would – some loss of talent as employees who would prefer the ability to vocalize their political views more openly move to more accommodating companies. Nevertheless, the executives at those companies felt the upfront pain was worth avoiding more long-term misery of low productivity and chaos within the employee ranks.

I think an important point to make to all who follow this issue is that, at some fundamental level, “cancelling” certain people for behavior that many others, but certainly not everyone, find abhorrent is unavoidable at any meaningfully-sized company. If you fire someone for wearing a swastika on their shirt, or for catcalling women, or telling a gay employee that they’re a sinner, a million protestations about how this may be “cancel culture” doesn’t change the fact that it’s the decent, right – and in many cases legally required – thing to do.

In reality, “cancelling” is not the problem. Ambiguity is. Ambiguity that gets filled by certain people on the employee roster who really should not be authorized to perform that role. The reason countries have things like unambiguous constitutions and laws, and hardened hierarchies to enforce them, is that the alternative is unpredictable and chaotic mob rule (even if democratic mob rule) that destroys value and makes it impossible to build the kind of stability that promotes society. The tragedy of what many people call “cancel culture” isn’t so much that certain behavior can get you canceled (it most certainly can), but the vacuum of leadership within organizations that allows termination decisions to be so surprising, erratic, and seemingly driven by unaccountable mobs.

Why is it that the most democratic countries in the world never have militaries run as internal democracies? Because democracies have all kinds of benefits, but meritocratic promotion and speed of execution – which are essential when losing means you are “game over” dead – are not among them. In a hyper-competitive environment, you do what has to get done to win and survive, and that’s often not the “popular” or “fair” (in the judgment of the masses) choice. In competitive business, as in war, hierarchy beats democracy. Every single time.

That being said, remember that not every company has to compete in the same way. Very large dominant companies with fat balance sheets and margins can afford to be a little more political than hierarchical, for PR reasons. Just as companies like Apple, Google, etc. can afford to promote various initiatives that may put democratic popularity above hard meritocracy, they can also afford a little more politicized chaos and employee mob rule “cancel culture” in their companies. If 5% of their employees devote substantial time to politicized initiatives, or even getting certain unpopular new hires fired, it’s not going to change the overall performance of a trillion-dollar company.

But for an early-stage startup, completely different story. Ambiguity in the values and culture of the company, and resulting chaos from certain lower-level employees taking it upon themselves to decide who should be hired or promoted, can quickly sink a young startup with limited resources facing stiff competition in the marketplace. Freedom of association and at-will employment mean your employees can simply choose to leave if they disagree strongly with a decision you made about hiring or promoting someone. There’s no getting around that. The only sustainable defensive measure is ensuring everyone understands on Day 1 what your company’s values and policies are, so this kind of reckoning day hopefully never materializes.

This is not a left/liberal or right/conservative politics issue. It’s a general business issue. Young startups need well-understood and enforced (hierarchically) values, and (as they grow) in many cases written-out policies, as to what merits an offer letter, a promotion, or cancellation (termination) in their company. This leaves plenty of room for pluralism, as different companies can sort themselves out as to what they find acceptable in their business environment, including the level of political discussion that’s acceptable. There’s no single answer, but not having any answer definitely won’t work.

I don’t believe more liberal, conservative, libertarian, or highly apolitical startups will have a universal competitive advantage in the market. But I do believe that those who don’t put much thought into this aspect of their culture at all, and don’t enforce (or defend) their chosen culture with a clear hierarchy, will lose (as a result of internal disagreement and chaos) to companies with a more cohesive identity and power structure.

Whether you want to be more like Google, like Coinbase, or something in-between in building your company’s culture is up to you and the rest of your founders. Just be clear and unambiguous about it, so that the employees who choose to join you know what they signed up for. The greater long-term alignment will allow your team to focus more on executing the mission, instead of executing fellow colleagues.

Moving (Too) Fast and Breaking Startup Cap Tables

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As I’ve written many times before, the “move fast and break things” ethos, which makes absolute sense in a software environment where fixing “bugs” is quite easy and low-stakes, becomes monstrously expensive and reckless when applied to areas where the cost of a mistake is orders of magnitude higher to fix (if it’s fixable at all). Silicon Valley got a very visible and expensive (to investors in terms of capital, and founders in terms of legal errors and terrible legal advice) lesson in this reality a while back with a very well-funded (but ultimately failed) legal startup heavily promoted as enabling (via over-hyped vaporware) startups to “move faster” and save significant costs. That legal startup was, perhaps unsurprisingly, controlled by money players with all kinds of reasons to profit from startups (that they invest in) getting weak legal and negotiation guidance. No one wants an in-experienced founder to move fast and mindlessly do what investors want more than… those investors.

That fundamental point is one that inexperienced founders need to keep their eye on throughout their entire fundraising and growth strategy. Notice how, for example, certain Silicon Valley groups adamantly argue that SV’s exorbitant rents and salaries are nevertheless worth spending capital on, and yet simultaneously they will howl about how essential it is that startups minimize their legal spend (a small fraction of what is spent on rent and salaries) in fundraising, and move as quickly as possible; usually by mindlessly signing some template the investors created? Why? Because they know that the one set of advisors most capable of “equalizing” the playing field between inexperienced startup teams and their far more seasoned investors is experienced, independent counsel. Aggressive (and clever) investors say they want you to adopt their preferred automation tools and templates because they care so much about saving you money, but the real chess strategy is to remove your best advisors from the table so that the money can then, without “friction,” leverage its experience and knowledge advantage.

At some obvious level, technology is an excellent tool for preventing errors, especially at scale when the amount of data and complexity simply overwhelms any kind of skilled labor-driven quality control mechanism. But there is a point at which people who sell the technology can, for obvious financial incentives, over-sell things so much that they encourage buyers to become over-dependent on it, or adopt it too early, under the delusion that it is far more powerful than it really is. This drive to over-sell and over-adopt tech for “moving really fast” is driven by the imbalance in who bears the cost of fixing “broken things.”

Ultimately the technology seller still gets paid, and puts all kinds of impenetrable CYA language in their terms of service to ensure that no one can sue them when users zealously over-rely on their products in ways clearly implied as safe by the tech’s marketing. Founders and companies are the ones who pay the (sometimes permanent) costs of a poorly negotiated deal or contract, or in the case of cap tables incorrect calculations and promises to employees or investors.

In the world of cap tables, automation and tracking tools like Carta (the dominant player, justifiably, by far) are enormously valuable, and doubtlessly worth their cost, in helping the skilled people who manage the cap tables keep numbers “clean.” In the early days of Carta’s growth (once called eShares), there was a general understanding that cap tables rarely “break” before the number of people on the table exceeds maybe 20-30 stakeholders as long as someone skilled at managing cap tables (in excel) is overseeing things. That last part about someone skilled is key.

There are in fact two broad sources of cap table errors:

  • Using Excel for too long, which creates version control problems as the number of stakeholders grows; and
  • Management of cap tables by people who are simply too inexperienced, or moving too quickly, to appreciate nuances and avoid errors.

Technology is the solution to the first one. But today it’s increasingly becoming the cause of the second one. The competitive advantage of technology is speed and efficiency at processing large amounts of formulaic data. But the advantage of highly-trained people is flexibility and ability to safely navigate nuanced contexts that simply don’t fit within the narrow parameters of an algorithm. In the extremely human, and therefore subjective and nuanced, world of forming, recruiting, and funding startups in complex labor and investor markets, pretending that software will do what it simply can’t do –  delusionally over-confident engineers notwithstanding – is a recipe for disaster. The combination of new software and skilled expertise, however, is where the magic happens.

The Carta folks have been at this game long enough to have seen how often over-dependance on automation software, and under-utilization of highly trained and experienced people in managing that software, can magnify cap table problems, because it creates a false sense of security in founders that leads them to continue flying solo for far too long. Sell your cap table software as some kind of auto-pilot, when the actual engineering behind it doesn’t at all replace all the things skilled experts do and know to prevent errors, and you can easily expect ugly crashes.

That’s why Carta very quickly stopped promoting itself as a DIY “manage your cap table by yourself and stop wasting money on experts” tool and evolved to highly integrate outside cap table management expertise, like emerging companies/vc law firms and CFOs; who spend all day dealing with cap table math. They realized that the value proposition of their tool was sufficiently high that they didn’t need to over-sell it as some reckless “you can manage cap tables all by yourself!” nonsense to inexperienced teams who’ve never touched a cap table before. The teams that use Carta effectively and efficiently see it as a tool to be leveraged by and with law firms, because startup teams are rarely connected to anyone who is as experienced and trustworthy (conflicts of interest matter) in managing complex cap table math better than their startup/vc law firm.

But as is often the case, the cap table management software market has its own “race to the bottom” dynamics – but a better name may be the “race to free and DIY.” If I’m a company like Carta, and I know that truthfully very few companies need my tool before maybe a seed or Series A round (excel is perfectly fine, flexible, and simple until then), I’m still extremely worried that someone will use the time period before seed/Series A to get a foothold in the market and then squeeze me out as their users grow. That someone is almost always a “move fast and break things” bottom-feeder that will, once again, over-sell founders on the idea that their magical lower-cost DIY software is so powerful that founders should adopt it from day 1 to save so much money by no longer paying for expertise they don’t need.

Thus Carta has to create a free slimmed down version, and they did. But they’ve stuck to their guns that cap tables are extremely high-stakes, and even the best software is still extremely prone to high-cost errors if utilized solely by inexperienced founders. That’s why Carta Launch has heavy ties to a network of startup-specialized law firms. It’s free as in beer, but honest people know that it still needs to be used responsibly by people who fully understand the specific context in which it’s being used, and how to apply it to that context.

But the bottom-feeders of cap table management are of course showing up, with funding from the same people who were previously happy to impose costs (errors, cleanup) on inexperienced teams as long as their software gets adopted and their influence over the ecosystem therefore grows. The playbook is tired and predictable.

Why are you using that other (widely adopted and respected) technology that still relies (horror of horrors) on skilled humans? It’s 2020, you need :: something something automation, machine learning, AI, etc. etc. :: to stop wasting money and move even faster. Our new lower-cost, whiz-bang-pow software lets you save even more time and manage your cap table on your own, like the bad ass genius that you are.

We know where this is going. Many of us already have our popcorn ready. While before I might run into startups who handled only a formation on their own, and show up with a fairly basic and hard-to-screw-up cap table, I’m increasingly seeing startups who arrive with seed rounds closed on a fully DIY basis, and totally screwed up cap tables involving investors and real money. They also often have given up more dilution than they should’ve, because no independent, skilled expertise was used to help them choose and negotiate what funding structure to use. Clean-up is always 10x of what it costs to have simply done it right, with a thoughtfully chosen (responsible) mix of technology and skilled people, on Day 1.

Technology is wonderful. It makes our lives as startup/vc lawyers so much better, by allowing us to focus on more interesting things than tracking numbers or inputting data. The stale narrative that all VC lawyers are anti-technology really gets old. We were one of the first firms to adopt and promote Carta, along with numerous other legal tech tools. Not a single serious law firm views helping their clients manage cap tables as a significant money driver. But that’s like saying no serious medical practice views X or Y low-$ medical service as a significant money driver. Something can be a small part of a professional’s expertise, and yet still way too contextual, nuanced, and high-stakes to leave to a piece of software pretending to be an auto-pilot.

When the cost of fixing something is low, move as fast as you want and break whatever necessary. But that’s not contracts, and it’s not cap tables. In those areas, technology is a tool to be utilized by still-experienced people who regularly integrate new technology into their workflows, while maintaining skilled oversight over it. Be mindful of software companies, and the clever investors behind them, who are more than happy to encourage you to break your entire company and cap table as long as you utilize their half-baked faux-DIY tool. Their profit is your – often much larger than whatever money you thought you were saving – loss.