Financial forecasting models are used to help businesses predict the future.
Different types of financial forecasting models perform best depending on the events you are trying to predict, the types of data you have on hand, and the level of precision you need.
Knowing how to use multiple different forecasting models, as well as when each is going to work best, is an important part of upping your analytics game. In this article, we'll have a closer look at five different financial forecasting models and present examples of use cases.
First, it is important to distinguish between the terms “financial forecasting” and “financial marketing” to understand exactly how they work together.
Financial Forecasting vs. Financial Modeling
Forecasting and modeling are different but related functions. They are often used interchangeably because they are done by the same people, with the same information, and the same goal in mind.
What is financial forecasting?
Financial forecasting is usually done by the CFO or controller. First, they take all the current internal trends, such as revenue growth, and external ones, such as market conditions and changes in consumer behavior. Then, they use this information to make predictions about the future.
That’s really it. Just like “weather forecasting” is predicting whether it will be sunny or rainy tomorrow, “financial forecasting” is predicting whether sales will go up or down.
What is financial modeling?
If financial forecasting is the “why,” then financial modeling is the “how.” Companies want to have an idea about the future so they can make strategic decisions that benefit their bottom line. The best way to get accurate, actionable information about the future is to use a financial model.
Why is financial forecasting important?
A company must have an idea of how things are going to be able to react to changes in the marketplace. Anticipating new opportunities is the best way to benefit from them. Seeing problems on the horizon is the only way to navigate around them.
For example, if you are seeing a market downturn coming, then you might want to improve your cash position so that you can survive the next few months. If you are seeing huge growth happening, then you’ll want to update your hiring plan.
Why is financial modeling important?
The simple answer to this question is uncertainty. If you are unsure about how the market is going to change in the coming months or years, then you need create models to see how your company would fare under different scenarios.
Financial models allow you to work with your uncertainty about the future to improve your financial forecasting.
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5 financial forecasting models for SaaS
The best financial model changes based on what information you have, how you want to use the model, and what you are trying to predict. Here are five financial forecasting models to help you drive business growth.
1. Top-down financial forecasting models
This model can come in handy when you want to evaluate a new opportunity and you have no historical data to base your predictions on.
A top-down forecasting model can use the size of a new market as a point of departure and then make a forecast by estimating how much market share your business will be able to grab.
Top-down model use case
You are thinking about building a new SaaS product but are unsure of how big the market could be. Start by looking at the total addressable market (TAM). That’s how much the market is worth in total.
Then, you look at market share. If there is a major player in the market, then it can be a lot harder to grow your market share. If the market is dominated by many smaller players, then it is easier to build your share of the market.
Finally, you take the market share you think you can attain and multiply it by the TAM to predict your future revenue. If it is greater than your expected costs building and launching the product, as well as acquiring customers, then you have a good opportunity.
2. Bottom-up financial forecasting models
If you have access to historical sales data or financial statements, it makes sense to go about your forecasting from the bottom-up. Then, you use your existing sales numbers and cash flow statements as the input for calculating future scenarios.
This method will usually be more accurate and more detailed since you are working with actual numbers, so you reduce the assumptions.
Bottom-up model use case
You have 200 customers currently. You are currently charging $25/month for your product. You are seeing 5 customers churn and 10 customers sign up monthly. You can use this to see that your current revenue is 200 × $25 = $5,000 and will increase by 5 × $25 = $125 per month.
3. Delphi forecasting models
The Delphi method is a model where you get your forecast from a group of experts, leveraging a facilitator and continuously collaboratively iterating on hypotheses and analyses to reach a consensus opinion.
Questionnaires, surveys, and focus groups form the basis of this process, where every round builds on the previous iteration. This is an efficient way to make sure the entire group gets access to all information.
Delphi model use case
Your product is stagnating at an MRR of $10,000. You’ve updated your platform with new features a few times, but your current customers do not seem willing to pay more and it is getting harder to find new customers.
You decide to hire a consulting firm with experts in the field to conduct a series of focus groups with your current customers, prospects, and influential people in the field.
After each round of focus groups, the experts present their findings. You take these findings as the basis for making changes and report them back to the consultants. They then conduct another round of focus groups, bring you their recommendations and you try them out. This continues until the problem is solved.
4. Correlation-based forecasting models
Another way to look at financial forecasting is to identify correlating variables and track how they follow each other. The rise of big data makes this a possibility for even smaller firms.
This way of predicting financial outcomes can help decision-makers make forecasts based on the relationships between prices and costs, supply and demand, and other factors that affect each other.
Correlation-based use case
While correlation-based forecasting is traditionally done in an academic setting, there are many ways to use this system in your company.
You want to start a new paid marketing campaign. While you understand who your buyers are when they are acting as a customer, you want to see if there are other behaviors that might help improve your sales campaign.
Going deeper into your buyer personas, you see that members of your customer demographics tend to share funny memes. You reorient your social media advertising to be “funny” and “viral” in hopes that they will be shared more in private messages, which can help build social proof for your product.
5. Statistical forecasting models
Statistical models (also called quantitative forecasting models) create relationships between the findings of other disciplines. This can help you figure out how your operation compares to other similar businesses, i.e. benchmarking.
Statistical forecasting model use case
Your growth rate is going exponential. You know this can’t last, but you want to have a better idea of when the exponential growth period will end so you don’t over hire.
You gather data from two main sources. First, you find the trends in the market growth over the last 20 years as well as expert opinions on how it will grow over the next 10 years.
Second, you use public data to track how your more established competitors grew over that same period to see when their growth curves started to level off.
Then, you use some statistical models to “fit” the growth rates of your competitors to the growth rate of the model to make inferences about how long your company will enjoy exponential growth.
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Companies want to have a better idea about how the future of their market and business will change. That’s the “why” of financial planning.
Companies do not have good information on what will happen in the future so need to use financial models to help predict the future. That’s the “how” of financial planning.
Gathering as much data as possible is the first step in creating a sound financial forecasting model. This information can be found internally on your balance sheet and income statement or externally from the news.
Then, you need to track down all of the uncertainties in your future and find ways to eliminate them. This is usually done through running multiple scenarios.
Finally, you need to select the right type of model. The right model is the one that can be used with the data you have on hand.