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There are many analogies for the hardships of starting a business; when you’re in the trenches of trying to get it to work, the one about building a plane as it’s taking off can feel eerily accurate.

But from the vantage point of an investor, working with many teams trying to do versions of the same thing in different sectors, we’ve gravitated toward an image of someone getting dropped in the middle of a desert. With limited resources, you have to find your way to civilization before you starve. In that scenario, survival is determined by two factors: (1) choosing the right direction and (2) moving efficiently enough to arrive at your destination before running out of supplies. Our previous piece is meant to speak to the former factor, while this is about the latter.

A marketplace model

In general, it’s fair to say that few founders are experts at building financial models. That’s probably for the best — other traits are generally more useful for starting a company — and this is an area where we can help. In fact, we’ve built so many versions of the same model that we’ve designed an off-the-shelf template to jumpstart the process. It’s tailored to Airbnb since it’s a business many recognize and we obviously understand, but we’ve made it as straightforward as possible to customize.

Having lived the pain of synthesizing a story using dozens of business reports — P&L, marketing metrics, cohort analyses, TAM estimates, product conversion rates, etc — the key feature of this model is simplicity. We need to see all the building blocks of the business at once, and oriented in a way that is digestible. It needs to be driven by the north star (defined in the previous post), but linked to the company’s business metrics and financials. We like to think about it as the executive summary of a board deck.

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This isn’t meant to replace critical business reports or a more nuanced understanding of what’s going on. Rather, it’s meant to serve as a bridge between these sets of data. The ideal use case is a board setting, where we’re trying to set a strategy that maximizes the impact of our limited bandwidth and capital before we run out of cash.

Here’s a quick overview of the four components:

North star: the model is driven by the north star, moving it from wherever things stand when we invest (usually 0) to whatever we set as our goal 24 months out. At first pass, we build a monthly plan with a linear progression to the goal, but as we learn more about seasonality and other factors, we tweak the growth curve. The key point here is that we use this metric above all others to hold ourselves accountable to progress.

Investments: it’s an easy mistake to discount expenses a startup faces as unavoidable but that line of thinking lacks a sense of agency. We prefer to view costs as investments that are both strategic and within our control. Through that lens, it should be possible to group together categories of investments into the results they’re meant to accomplish. Each business has to define the set of investment pillars that are appropriate for what they do, but there should be as few as possible while remaining mutually exclusive and collectively exhaustive. We like to call one of the pillars ‘enablers’ where we group things like legal support, office space, and the CEO’s salary. :)

Objectives: A sanity check on the investment pillars is that they should each be easily tied to a business metric. And those metrics in turn should add up to the north star (aside from enablers). The earlier exercise of building the experience map is useful here.

We use the term ‘Objectives’ deliberately here, as a link to OKRs. Many teams we work with like using OKRs but they have a tendency to result in lists of ‘key results’ that are sometimes hard to prioritize. If the ‘objectives’ portion of OKRs is highlighted here and linked to the north star goal, it becomes easier to walk back and forth between tactical projects and the overarching quarterly goal.

Financials: Finally, it’s important to sanity check how aggressively to invest in forward progress relative to cash runway. This last piece of the model weighs growth in revenue against growth in investments to validate that the business isn’t getting over its skis.

A typical board conversation involves walking back and forth between different scenarios for the quarter ahead, balancing how aggressively to invest in different sides of the business relative to their expected impact on our north star goal and cash reserves.

Calibrating the model

With the model in place, you have a view of the different levers of the business. The remaining step before it’s really useful is to calibrate it around an end point. Circling back to our desert analogy, the question here is how far you need to stretch your resources to arrive back at civilization.

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We generally like to use series A readiness as the goal post for this exercise. It’s imperfect because a variety of factors can blur the line for what will get investors excited (see, for example, a good post on this by our friend Marc McCabe) and what might have been true in the past is in the process of changing.

Nevertheless, you can start with something directionally right, like $2m ARR, and then meet with a few series A investors you respect to validate whether they agree. Since the north star is tied to transactions, it should be easy to do the math on where the north star needs to be in order to hit that revenue figure 18–24 months out. You can then work backwards through the model to set monthly milestones to track your progress.

There’s a great story that came out of Facebook’s growth team about their progression from 200 million to 1 billion users. At the time, it wasn’t clear that such a feat was even possible. But the team decided to set an audacious goal anyway and take a crack at hitting it.

Over the following two years, they methodically executed their “UIE” framework (an acronym for Understand, Identify, Execute) where they would set a goal for increasing active users, research opportunities for growth, identify the most attractive lever, and then roll out controlled experiments. If the experiments worked, they would shift the goalpost and begin again; if the experiments failed they would research why and identify a new lever.

Companies don’t have to be large to be methodical. Be scrappy, certainly — think hard about every investment you make and what it’s meant to yield. Try things that don’t seem scalable — you can figure out a more scalable approach once you know it works. The key point is that every day in the seed stage is precious. If you choose the right direction and execute effectively, you’ll escape the desert before you starve.

With this roadmap in place it’s time to get to work! More on that next.

Written by

GP at Wave Capital, formerly head of data science at Airbnb

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