9 Financial Forecasting Methods & When To Use Them

We’re not gonna sugarcoat it — financial forecasting is a tough nut to crack. But if you’re serious about your startup’s success, you’ve gotta get it right. 

Financial forecasting is a powerful tool. By crunching numbers and analyzing external factors, it can give you a sneak peek into your startup’s future. There are a lot of methods do this. But if your financial forecasts are way off, it can lead to vast misalignment about the reality of where a company is heading.

That’s why you need to take a more holistic approach and use corporate forecasting exercises to get a better handle on things.

Each of these financial forecasting methods can help you develop a concrete plan to achieve your goals and understand the potential future of your business. So if you’re serious about taking your startup to the next level. It’s time to roll up your sleeves and get forecasting!

Financial Uncertainty Is the Enemy

When it comes to emerging and growing businesses (such as startups), nothing can be more deadly than financial uncertainty. The most common reason startups fail is that they run out of cash, and plenty of other startups struggle with a lack of financing or investors. Ultimately, cash management and capital are crucial for keeping the lights on and paying employees. But they also play a central role in a startup’s ability to grow. 

While financial uncertainty is the enemy, financial forecasting can be the secret weapon. 

Financial forecasting involves data collection, calculations, and a bit of educated guesswork in the form of modeling, and it can take some trial and error to really get right. Forecasts consider historical data, such as cash flow, financial statements, expenses, and sales, to make projections. Forecasts also apply external variables to their models, considering things such as market conditions, industry trends, customer behavior, and even regulatory changes.

As you can imagine, financial forecasting can take a lot to get right. But by tapping into different corporate forecasting exercises, leaders, decision-makers, and those tasked with the mission-critical financials of their organization can create the most accurate, data-informed projections possible. These can then be used to make strategic decisions, support long-term planning, and best determine how to allocate future resources.

Financial Forecasting Methods to Try

By now, you likely understand just how important financial forecasting is. With that in mind, here are 9 corporate forecasting exercises to try (and some financial forecasting tips) to help you obtain valuable insights into your organization’s financial future. 

1. Straight-Line Forecasting

Considered one of the simpler forecasting models, straight-line forecasting uses past data to predict future performance and assumes the future growth rate will stay consistent. In order to arrive at this figure, some basic math is involved: you use the previous growth rate and apply it to predict what the upcoming years look like.

Straight-line forecasting is beneficial because of its ease and simplicity. It could give startups a great ballpark for their future based on their previous performance. But one of the downsides is that it doesn’t consider any unexpected events, such as market fluctuations or changing customer habits. 

2. Time Series Forecasting

You might find time series forecasting methods helpful if you need to make time-sensitive predictions. These methods gather data at regular intervals over a period of time and can identify patterns like seasonality, trends, and cycles. The accuracy of time series forecasting depends on the amount of data collected and its quality, and these models can sometimes be complex or time-consuming to produce.

3. Moving Average Forecasting

A form of time series modeling, moving average modeling uses past forecasting data to identify noise, errors, or outliers in forecasts to best spot trends. One of the biggest challenges of forecasting can often be dealing with outliers: how do you know if something is a trend or just a blip?

Moving average forecasting helps address this question. It smoothes out previously identified outliers and fluctuations to help clarify what’s a legitimate trend and what’s just a random occurrence. 

4. Top-Down Forecasting

This forecasting approach estimates future sales by starting with big-picture market data. Top-down forecasting starts by looking at the overall market and estimating how much market share your company can likely acquire in the future. Then, this model calculates how much revenue a company can expect to earn. 

Top-down forecasting has a few benefits: it’s usually fairly quick to collect data and can provide a startup with information about expected demand. But this high-level overview can often miss smaller details and sometimes leave out key information from forecasts. 

5. Bottom-Up Forecasting

Bottom-up forecasting is essentially the opposite of top-down forecasting. It starts from the “bottom,” or the smallest level of data detail available, to anticipate future performance. Someone executing a bottom-up forecast might start with data about amounts of products, orders, or customers, for example, but the data can be even more granular.

Bottom-up forecasting allows for an impressive amount of detail and can really hone in on specifics (such as a product or offering). It can also take many factors into account. But bottom-up forecasting also can come with some risks. It can be comparably more time-consuming than other methods, and if there is too much data in the model, it can become ineffective and difficult to distill what is influencing certain outcomes. 

6. Percent of Sales Forecasting

This forecasting method makes future predictions based on sales data. It uses current and historical data related to sales, including revenue and expenses. This model assumes there is a relationship between certain financial metrics and the amount of sales generated and that this relationship will stay consistent in the future.

7. Simple Linear Regression

The simple linear regression forecast model operates similarly to straight-line forecasting. It considers two variables, such as the price of the product and the number of units sold, and determines their relationship. In this example, simple linear regression might determine how changes in the price impact the sales volume. 

While simple linear regression can help startup leaders understand how one part of their business impacts another, it’s also important to note that it provides a simplified view of the relationship between the variables. Adding to our example, when it comes to startups, other factors such as marketing efforts, customer preferences, and market volatility can also influence sales. 

8. Multiple Linear Regression

Similarly to simple linear regression, multiple linear regression allows for the analysis and forecasting of the relationship between multiple variables and one dependent variable. For startups, it can help leaders understand how various factors influence a startup’s performance.

Let’s say you want to predict the future revenue of your business based on marketing expenses, the number of employees, and customer satisfaction. Revenue would be the dependent variable, while the other three would be the independent variables (or the influencing factors). As with simple linear regression, it’s also important to remember that other factors can influence the variable being analyzed. 

9. Delphi Method

This structured approach collects relevant experts’ opinions, distilling their insights and judgments into takeaways on certain topics. For startups, the Delphi method can be used when it comes to market trends, product development, strategic planning, or risk assessment. 

To execute the Delphi method, you first need to identify a group of knowledgeable or experienced individuals with relevant domain expertise. Then, you present them with the defined problem through specific, open-ended questions. These experts fill out questionnaires, and you collect their feedback.

After this, analyze the feedback to see whether there is consensus or trends. Share the feedback with the experts in subsequent rounds, and prepare a final report. 

Financial Forecasting Minimizes the Unknown

The future of your startup doesn’t have to be foggy. Instead of fumbling around in the dark and operating in a state where you’re unsure of your company’s financial future, you can turn to tried-and-true financial forecasting methods. With a clear vision of your company’s future, you’ll be unstoppable on your path to success.

But don’t go it alone. There is finance software, like Basis, that can help you map out various scenarios and demonstrate how adjusting certain variables can impact your results. This tool is like having your own personal crystal ball. Plus, when you work with Hiline, we manage it all for you. 

Contact us today to get started.