Companies do not end up with good cash flows simply by luck.

Financial forecasting is essentially the crystal ball that allows financial advisors to predict the future of a company. Of course, there are always unpredictable and uncontrollable variables that could make outcomes differ from predictions.

When unexpected changes happen, financial forecasts help executives understand how the changes have altered the company’s trajectory and adjust accordingly. Financial forecasts are an important decision-making tool that eliminates the need for making uneducated guesses about the business.

Financial health results from thorough data analysis, in-depth knowledge of the firm, and up-to-date consumer and market information. In good times, financial advisers who forecast correctly share in the company's prosperity, and in difficult times, they may make the predictions that keep the company trending upward.

What is financial forecasting?

Financial forecasting examines previous data to forecast a company's future financial outcomes. It helps predict future possibilities for the company based on historical financial data.

Financial forecasts are updated fairly regularly, as often as monthly and usually at least quarterly. A company often has multiple financial estimates for short and long-term analysis. These projections help with determining the next steps for a company and enable executives to pivot if needed.

Financial forecasting vs. budget forecasting

Financial forecasting and budget forecasting get mixed up because both are part of a company’s financial planning process.

The most straightforward way to differentiate them is to think of budgeting as a company’s goals and financial forecasting as the tool that tells the company if they are likely to reach those goals as things change throughout the year. Executives may use a forecast to create a budget that is aspirational but still achievable.

Unlike a budget, a financial forecast can be used to help shape decisions about the company by informing executives about how variables could affect outcomes. A budget, on the other hand, is more of a baseline for comparison.

Financial forecasts are generally conducted more frequently than budget, making them more flexible and reflective of recent events or variables. Financial forecasting helps management look objectively at a budget goal to determine what’s achievable based on external market factors. In this way, financial forecasting helps keep employee morale high by preventing the pursuit of unachievable budget goals.

Financial forecasting models

There are many different financial forecasting models, but they all fall into two categories: quantitative and qualitative.

Quantitative forecasts are based on data that can be measured, controlled, and rendered statistically.

Qualitative forecasts are based on data that cannot be measured objectively. Qualitative forecasting models are less reliable since they aren’t based on objective facts. They include forecasts based on expert opinions, consumer reports, and reference forecasts. However, they’re still helpful for companies in many ways.

Let’s examine the most common types of forecasting models:

1. Straight-line method
   ‍This model uses historical data and presumes it will continue on the same trend to predict a future outcome. For example, if a store has seen a 2% increase in sales each year for two years in a row, they may assume that will continue and create a model that will predict sales in five years. They may then use that information to decide whether an investment in the business, such as a renovation, makes sense.
2. Moving average
   ‍The calculation of average performance around a particular statistic in shorter timeframes than a straight line is known as a moving average. It is not used for longer periods, such as years, because there is a lag. This calculation is good for metrics that frequently move, like the price of certain raw materials or inventory.

For example, if an executive wanted to predict how much to produce of a certain product for the holiday season, looking at daily inventory fluctuations may not be helpful. Instead, they may use a moving average to predict how the item will trend throughout the season and ensure the correct amount of inventory.

1. Simple linear regression
   ‍A linear regression is what you are likely familiar with seeing on most line graphs. It demonstrates how one variable (X) relates to a second variable (Y). For example, it could be used to show a relationship between marketing spend and sales. When charted, a line indicates a trend – such as sales increasing as marketing spend increases. However, a lack of a clear trend line between points usually indicates that there is no direct relationship between the variables. This information is valuable for executives to understand which investments are driving results.
2. Multiple linear regression
   ‍As the name implies, multiple linear regression shows the relationship between more than two variables. It models the connection between independent explanatory factors (parameters) and the dependent response variable (outcome).This financial model is helpful for predicting how multiple factors (sales, costs, the economy) will affect revenue to give an overall projection for a given time period.

Whatever your preferred financial forecasting model, having the right tools can make all the difference.

A data platform such as Causal automates data imports, streamlines formulas, so you’re not spending days punching in calculations, and gives you visualization tools that help decision-makers see what the numbers actually mean. Also, Causal has a library of financial templates you can lean on to provide you with a head start on financial modeling.

Financial forecasting helps you get it right

Overall, financial forecasts are an important tool for businesses and decision-makers. They can predict profitability, cash flow, and even inventory needs. Financial forecasting best practices are more likely to be adopted and maintained by business executives who want to expand — and weather unforeseen setbacks. While it's impossible to forecast the future, adequately ensuring against worst-case scenarios provides a company a fighting chance to adapt.

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