October 3rd, 2022 | By: Wil Schroter

All financial projections for startups are based on a handful of financial assumptions. The problem is we tend to make **very bad assumptions!**

There are no "genius MBAs" out there building financial projections in a business plan that magically come true because they took a class on it. Financial assumptions, particularly for startups, are about making and refining a million tiny guesses until our financial performance gets somewhere close to our financial projections.

Startup financial projections are built around making a series of educated guesses about how things *might* go. Public companies make sales projections, issue projected income statements, and create revenue forecasts all the time. The difference is they are going off of lots of history.

As startup founders, we make assumptions about how much customers will **pay **for our product, how much it will cost us to **acquire **a paying customer, and how **many times** they will keep paying us over time.

But we have no history at all.

We make all of that revenue and assumptions of our startup expenses to get us started. Then we test our business model in the real world and find out we’re totally wrong. Then we make more adjustments. Then those are wrong too. Then we keep adjusting until eventually, our financial forecasts start to make sense.

In order to better understand the assumptions that make up our financial statements, let's first understand how little we actually know!

If we assume that our average customer will pay **$40** for our product, do we really know they will? Of course not! We probably haven’t even started our business venture, so perhaps we pulled some industry benchmarks to get us started, or maybe we straight-up guessed.

Think of assumptions as a **placeholder value **that we will use to begin building the financial projections for our business. In most cases, our startup probably hasn’t been around long enough to know whether any of these values are accurate — and that’s OK.

For the time being, just know that all we need to build our first financial model is to know what the **types of assumptions** are and then make a reasonable guess as to what the values might be.

In the initial investment period of a small business, we spend more time **forecasting** our new business than tracking our monthly expenses or our nonexistent operating income. Whether we have potential investors on board or not, we still need to build some projected income statements to create a theoretical forecast of our future performance.

A financial forecast is just what we’d think it is — a **guess **about how the business ** might go**.

We don't know exactly how fast we'll see revenue growth in our business plans, so we use assumptions based on guesses (really, guesses!) to build things like sales forecasts or plans for marketing expenses. Then we go test them.

Now, of course, we’re freaked out that we’ll make bad assumptions and the forecast will be based on numbers we can never hit. We think potential investors are going to look at our financial assumptions and laugh us out of the room (well, they might...).

The reason startups don’t understand forecasting is that they tend to think it’s based on information we have on hand right now. Forecasting isn’t intended to predict the future **specifically**.

Our specific assumptions are intended to provide a working model to show us what happens when different assumptions we’ve made will **change**.

So, let’s just think of our future forecasting as a simple “if/then statement.” “If” our costs per product are too high “then” we’ll need to increase our retail price to maintain the same margin. Our forecasts are just us moving all these levers until we find the right balance of revenue and costs for our business.

Assumptions and Forecasts go together like peanut butter and chocolate. Like Run and DMC. Like Ninjas and Pirates. Like… well, point being – they work well together!

Our **assumptions** allow us to make really specific guesses about things like what a customer will pay or how much it will cost to produce the product. Our **forecasts** simply take those assumptions and calculate what will happen if those assumptions are true.

Here’s an example of where just 2 assumptions can tell us exactly how much revenue we can forecast per month:

**Assumption #1**: Our average customer will pay**$40**for our product.**Assumption #2**: We think each month we’ll acquire**10**new customers.

Let's take a look at how those two assumptions would affect our income statement.

Those two assumptions tell us that "If this happens... then this is the outcome"

If our Average Customer pays $40 (

Assumption #1)then for every 10 Customers (Assumption #2) we'll generate$400.

What's important to focus on here is that while we don't necessarily know how many units we might sell, or what the customer will ultimately pay, we do know that those two assumptions will drive our financial statements.

Here's where we get all worked up - we think that the way to build an income statement is to *know all of the answers to our assumptions - *it's not!

We build a a financial statement by isolating all of the key assumptions first, and then testing different inputs to see how the projected financial statement reacts.

By focusing our efforts on the assumptions (like how much the product will sell for how many customers we acquire) we can let our forecasts simply be a calculation.

Once we learn how distilling our business into assumptions gets us closer and closer to numbers that we can actually understand and predict with more accuracy, this whole business of guessing starts to become a heck of a lot easier!

With that said, let’s first dig into how assumptions work, and then once we have a handle on that, let’s see how those assumptions can build a forecast for us.

Every startup financial model is based on a handful of “assumptions” which are the values and values we *think* are going to be true about our business.

Some of our assumptions will likely be:

How much will the customer pay for the

**product**?How much will it cost to acquire a paying

**customer**?What will it

**cost**us per unit sold?How many

**times**will the customer purchase the product again?

Those are just a few of the most popular assumptions, but there are many. We’re probably thinking “How the heck could I possibly know what any of those values would even be?” and that’s the right question to ask!

We don’t know exactly what any of thesevaluesare, but we know exactly whichassumptionswe need to have answers to in order to build theforecast.

That’s like saying “We don’t know if this recipe requires a pinch of salt or vat of salt – but we know it needs salt.” In this case, we don’t know whether our product will sell for $20 or $40, but we know there will be a **price **for our product.

When we distill the formula down to specific values that we know we need to prove out (like the amount of salt in this recipe) it changes our concern from “what the hell is this recipe?” to “I know the recipe, now let’s just monkey with the amount of salt.”

So right now, let’s just focus on how assumptions work wonders for making our lives easier. Later on, we’ll focus on what actual values to use and how to make some sweet-ass guesses!

We would think that if we’re going to build a financial model, it would have to be pretty damn accurate. I mean, we’re talking about finances, right? We can’t turn this thing into Enron meets WeWork!

We're not building a forecast for a public company to hold up to the scrutiny of financial institutions — we just need a model with a few financial assumptions to monkey with. As it happens, we only have to be totally right about *a few major assumptions*. The rest, well – they sorta don’t matter by comparison.

Allow me to illustrate this point in the form of a rant.

/ begin rant

Startups get super distracted by trying to forecast every part of their business. Most of it is a wasted effort. If a startup can’t sell a product for more than they paid for the product (including marketing) — there’s no business there!

We’d be hard-pressed to find a business that sells dollar bills for 99 cents (re: not sustainable!) and is going to be around for very long (

ignore Uber et al). The assumptions of a startup need to be set up so that if they hold true, the startup can operate profitably at some point in the (hopefully) near future.This doesn’t mean that operating expenses and fixed costs don’t matter – they do. But it’s rare that a company can find a way to sell at a loss and still come out ahead because they “nailed the forecast on office space costs in Year 3.”

/end rant

It’s this simple – there are a handful of assumptions that will make or break our business. The rest of the assumptions can be right or wrong, but it won’t matter if the core assumptions that drive our business model don’t hold up. Instead of listing every assumption that doesn’t matter let’s focus on the major assumptions that matter.

Although it can be said that every business is a little different, the truth is most businesses still have to sell something to a customer at a price *higher* than what they paid. Within this universal truth lies a common set of major assumptions that nearly every startup uses to develop a successful financial model (or an unsuccessful one – the model is still the same).

We call these the major “Assumptions that Matter.”

While there are TONS of other assumptions that will also matter in different capacities, we’re going to focus on the 3 most typical and important that can make or break the business.

We'll do a quick "fly by" right now of assumptions and then dig into the details in the next section.

*"How much will it cost to acquire new customers?"*

The first question we’ll need to answer is how many customers will pay us, and what that associated cost will be. This is frequently known as our **"Customer Acquisition Cost" (CAC) **and we'll certainly be asked about it by potential investors.

To calculate the cost to acquire customers we need to make specific assumptions based on how many customers we could generate and what our total cost would be to acquire them. Don't worry — we're just inserting numbers right now to understand the relationship, it doesn't matter if we're right.

If we spent $1,000 and acquired 10 paying customers, our Customer Acquisition Cost – “CAC” – is $100 ($1,000 divided by 10).

CAC is an incredibly important number for businesses that rely on marketing (not direct sales) to drive growth. We'll explain how to go about working with these common assumptions and some common mistakes people make later.

*"How much revenue will a single customer pay us over time?"*

Next, we’ll determine how much those customers will pay us by estimating the “Lifetime Value” (LTV) of a customer. This is an indication of the total amount they will pay to us in a given time frame, such as a single year.

If I buy one pizza for $10 and never buy it again, my

LTVis $10.If I buy 100 pizzas over the course of a year (yum!) and we set “lifetime” to mean 1 year, my LTV is $1,000 ($10 x 100).

LTV is really important when we want to understand how much long-term value a customer has beyond an initial sale. This can be particularly valuable for businesses with a recurring revenue driver (think NetFlix, a cell phone bill, or similar companies) where the early acquisition costs may be high, but the customer becomes profitable over a period of time.

*"What is the cost of each sale?"*

Finally, we’ll determine the Cost of Goods Sold (COGS) — the hard cost of a single unit of the product. While this is a popular assumption, it may not necessarily apply in every case. If we're a software business and our incremental product costs are essentially zero, this may not apply.

If we sell a bottle of soda for $3 and we paid $1 to manufacture it — we have a $1 cost of the goods sold (COGS). We also way overcharged for a soda.

Early investments like capital purchases are typically not included though raw materials may be part of that equation. Those are small business decisions we make along the way.

Sometimes we may wonder if people are considered COGs as they are required to deliver each individual unit of the product. The easy way to think about this is that if the product is the people (like a law firm) then most likely yes.

If there are just people working in the business, and each additional unit we sell does not directly create more people costs (again, we're not selling humans for time) then we tend to just call those Operating Expenses and they sit as more a fixed cost that grows over time.

There are tons of different assumptions based on what business activities are specific to your startup or small business. We're focusing on the most common assumptions that most small business owners deal with.

A startup company may also put a different weight on certain assumptions in the income statement. For example, depending on the industry, the revenue driver may be the most important assumption since the Cost of Goods Sold (COGs) could be well known or constant.

These key assumptions usually form the foundation of our financial projections in our business plans. We have many more key assumptions to consider to get accurate sales projections or to build out our financial statements in a way investors will want to see.

It will take time to figure out what our solid assumptions might be — no one typically knows from the outset and that's OK. What we want to focus on right now is what assumptions will make the most impact on our business (for better or worse) and how they will transform our income statement.

Next up we're going to dig deep into more key assumptions as well as how we can build a projected income statement for our business plan. We'll use a few examples along the way to give you a better sense of how to modify your own income statement as well.

Wil Schroter is the Founder + CEO @ Startups.com, a startup platform that includes Bizplan, Clarity, Fundable, Launchrock, and Zirtual. He started his first company at age 19 which grew to over $700 million in billings within 5 years (despite his involvement). After that he launched 8 more companies, the last 3 venture backed, to refine his learning of what not to do. He's a seasoned expert at starting companies and a total amateur at everything else.

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