Whether a financial forecast focuses on short- or long-term objectives, teams can always adjust the forecast by adding additional data as it becomes available. AI technology has streamlined the process with automation capabilities, enabling professionals to inform business decisions at a much faster rate.
Financial Forecasting Methods
Financial forecasts hone in on growth and other factors, so teams need to decide which method best serves their purposes.
To determine the most efficient way to allocate resources, finance departments work with several types of financial forecasts. The straight-line method is a convenient option that enables teams to estimate future revenue growth with historical data. Teams can also make predictions based on averages calculated with the moving averages technique.
Still, companies may need to understand how variables interact with each other and influence business revenue. A simple linear regression tracks how a single variable like customer churn affects revenue. Meanwhile, a multiple linear regression looks at two or more variables. Once teams understand what they want to learn from a financial forecast, then they’ll be able to select the method that meets their needs.
Financial Forecasting vs. Financial Planning
Financial planning and forecasting go hand in hand, but the two disciplines occupy unique spaces within the planning process.
In the world of finance, financial planning and financial forecasting are their own entities. A financial plan creates a guide for how a company will leverage its resources to meet its growth and profit goals. While teams can spot strengths and weaknesses with a financial plan, the bulk of the research occurs during a financial forecast.
Financial forecasting relies on past data to estimate how revenues will behave in the future. By studying relationships between variables, financial forecasts give teams the insights they need to develop more accurate financial plans. In addition, teams adjust financial forecasts to ensure their financial plans remain viable. That’s why businesses rely on programs like Python to quickly generate time series and other methods when re-calibrating predictions.
What Are the Advantages of Financial Forecasting?
Financial forecasts help companies follow more secure strategies moving forward and earn the trust of investors.
There’s always the chance a business lacking a plan will waste precious time and resources, but financial forecasting eliminates much of this risk. Leaning on the data of a forecast, finance professionals can prepare for revenue changes and know how to spend or save their funds. Many sales teams have come to appreciate the value of this approach, making financial forecasting essential for those seeking to maximize their growth.
It’s also important to build confidence among investors, and financial forecasts serve as crucial tools in this respect. Investors want to see that businesses have done the research and come up with a plan for growth, leading many SaaS companies to increase their credibility with revenue forecasts. Financial forecasts empower teams to make more thoughtful and purposeful decisions, which are bound to catch the attention of investors.