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6 min read

Bottom-up or Top-down: Which Financial Modeling Approach Is Better?

A look inside the topsy turvy world of financial modeling (it's not all smoke & mirrors)

Any business plan or investor pitch would be incomplete without a financial model. It is used to convey a company's projected performance over time, usually in terms of annual, quarterly, or monthly statements. It will delineate the different revenue streams, operating expenses, and capital expenditures, and provide guidance on the cash fluctuations a business may incur.

One of the best ways to understand the financial model is to compare it to a different kind of forecasting: predicting the weather.

When you look at the weather forecast, you realize that it will not perfectly predict the upcoming climate conditions. There are far too many variables for that to be the case. The high and low temperatures are often off by a degree or two. Sure, you can see whether there’s a chance of precipitation, and when it is most likely, but you know there will be fluctuations. You also recognize that the forecast for tomorrow will be more accurate than the forecast for five or 10 days from now, but you also know that those projections will be revised for better accuracy as that date approaches. In short, the purpose of a weather forecast isn’t to predict exactly what all the weather conditions will be, it’s to tell you whether you should bring a jacket or pack your swimsuit. And it’s always subject to change.

The financial forecast of a company is very similar. It will never be perfect, because just like meteorology, it is dependent on many complex factors. The goal is to provide an estimation for how a company will perform in the short- and long-term, adjusting to market factors as the company grows and evolves.

Even if we all know that a financial forecast will not be perfect, there is a reason why banks and investors request it, and why it is critical that the financial forecast be as measured as possible. If you take a financial forecast to a bank for an SBA loan, they will immediately judge it based on how similar businesses have performed. Similarly, if you show that your startup's revenue will outpace the competition too quickly when pitching investors, you will lose all credibility.

Like a good weather forecast, a good financial model necessitates experience, research, and attention to detail. It of course requires an understanding of accounting concepts, but just as importantly, the financial model requires the financial modeler to creatively compile many reasonable assumptions to predict the attractiveness of a business opportunity.

And that is the purpose of this post today, to give an idea of where to start when thinking about a financial model, and in particular, the top line of a financial statement: predicting revenue.

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Putting concrete numbers behind a concept can be intimidating. But knowledge is power, and you'll feel better once you have some ballpark figures for your financial model. The first step toward making your fantasy a reality is RESEARCH!

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Top-Down vs. Bottom-Up: The Definitions

A financial modeler's approach to a revenue projection can be divided into two categories: top-down and bottom-up. Top-down financial modeling looks at the company's revenue in the context of the market as a whole. Bottom-up forecasting, on the other hand, looks at the business's foundation level, such as production capacity, hours available for services, seat turnover in a restaurant, or other drivers, and uses that to predict revenue.

A top-down model starts with the market and works its way down, whereas a bottom-up model starts with the business and works its way up.

So which is better, you ask? Well … it depends.

The Pros and Cons of Top-Down Financial Modeling

At first glance, top-down financial modeling appears to be a simple and clean approach. In fact, the "equation" is:

Total Market x Market Share = Revenue of the Company

However, creating an accurate top-down model is dependent on having accurate data for both the total market size and a reasonable share of that market. Let's say you're launching a cereal company. According to IBISWorld, the total cereal market in the United States is worth $12 billion per year. But, in a market dominated by established national brands, how do you calculate a reasonable market share?

If you're new to the market, you're probably not even thinking about competing with Post and Kellogg on a national level; instead, you're looking at a localized and likely niche market (organic artisan granola, for example) within that total U.S. market.

One method for approximating the local market is to use population. If you were to launch in my hometown of Portland, Oregon (population 2.5 million), you could make an educated guess that its cereal market is about 0.75% of the national market, or about $90 million. This obviously does not take into account regional trends within the national market, but it is a good starting point for a rough calculation.

But, even with a rough local market, how much of this can be expected to go towards artisanal granola? According to IBISWorld, oat cereals account for approximately 20% of the overall market, so it would be prudent for us to limit the total available market of oat-cereal Portlanders to approximately $18 million per year.

However, the major players will continue to dominate this market, making it difficult to estimate a reasonable market share. 1%? 2%? Where are you getting that figure? Is that a large enough number to pique an investor's interest?

So as you can see, top-down financial modeling is far from simple.

On the other hand, one of the reasons top-down models are so popular is because it creates a realistic constraint for the forecast, it shows you’ve researched the market, and gives you information that can be useful in future operations.

Top-down financial models, however, cannot account for the creation of new markets, or even market effects that are harder to identify. If your artisanal granola becomes the next TikTok craze and everyone in Portland starts eating it, your market share will likely be higher than you anticipated, and you'll need a bigger machine and more personnel to meet this surge of demand. (As a side note, if your company’s success is dependent on going viral, I would recommend a different business model.)

Uber is an excellent example of this effect. If Uber had been restricted to a top-down model by a share of the taxi market (about $21 billion in 2014), it would not have been nearly as appealing an investment opportunity. Instead, Uber (and its competitors) blew the lid off the taxi marketplace, propelling it to grow at a compound annual growth rate (CAGR) of 22.5% over the next five years until the industry reached $58 billion in 2019. (The market experienced a significant revenue drop in 2020 as a result of the pandemic, but it is gradually returning to its 2019 peak.)

Industries Well-Suited for Top-Down Financial Models
  • Consumer Goods: End-user sales fluctuate with consumer confidence, making it an easier market to forecast
  • Ecommerce: Ecommerce retail can be a good approach for large businesses because location (both size and placement) isn't a factor.
  • Commodities: When a product is less customized, location and price are more likely to be your primary differentiators

The Pros & Cons of Bottom-Up Financial Modeling

As previously stated, a bottom-up model begins by examining a company's internal drivers in order to forecast future revenue. Bottom-up financial models work well for businesses where there is a clear maximum capacity, such as a hotel (number of rooms) or restaurant (number of tables). Returning to our local artisanal granola, determining how much cereal can be produced is a key driver in determining how much cereal can be sold.

If you can produce 5,000 units per month and sell your granola at a wholesale price of $5 per unit, you can expect to earn $300,000 in total revenue.

Bottom-up models are also effective for existing businesses with well-defined performance metrics such as customer acquisition costs (CAC) and attrition rates. Even if your company is new to the market, you can use competitor data to develop your own bottom-up model.

Demand determination is a challenge for a bottom-up model. Just because you can produce a unit of granola does not guarantee that it will sell, and it is unrealistic to expect every available hotel room to be filled every night. Even though Facebook grew at a rate of 74% per year, that doesn't mean that the next social media company will do the same.

Industries Well-Suited For Bottom-Up Financial Models
  • Restaurants & Food Service: Revenue is typically limited by size and staffing (but don’t forget about delivery!)
  • Manufacturing: Production capacity is usually determined by equipment and/or labor
  • Services: The majority of service revenue is generated by hourly labor billing or customer contracts

Which Approach is Better?

Well, Masterplans financial modelers prefer a combination of top-down and bottom-up approaches. Understanding your business and the funding you require is critical, as this frequently dictates the revenue you must generate in order to be fundable. It is also essential to recognize some of the most common revenue-generation constraints in order to make realistic projections.

There's nothing stopping you from using both a top-down and bottom-up approach. You can use one to drive revenue while using the other as a metric to assess the output.

Using the granola brand again, we can demonstrate that the forecast is reasonable from both perspectives by using both production capacity to drive unit sales and our $18 million local market to gauge demand. Does it predict that it will happen? Just like the weather, it is always subject to change.

However, by using both internal company and external market data points, we can develop more accurate forecasts, increasing your credibility as an entrepreneur.

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