Your Handy Pocket Guide to Forecasting Financial Statements

Your Handy Pocket Guide to Forecasting Financial Statements

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Financial forecasting is imperative to understanding how your company’s finances look in the months and years ahead. In addition to helping executives properly plan and fund future business initiatives, financial forecasts help leadership teams manage company finances along the way.

This article will look at the benefits forecasting provides, two different financial forecasting approaches analysts often use, and a few limitations to keep in mind. Finally, we’ll go over one tool that business leaders and modelers can use to make their forecasts even more reliable.

What is financial forecasting?

Financial forecasting is a process used to predict how a company’s finances will perform in the future. Analysts typically use an organization’s historical data and other factors, like market data and consumer trends, to make these educated predictions. 

Although typically used for income statements, forecasting is very useful for projecting balance sheets, cash flow statements, and many other financials. 

For example, you can use this tool to predict a technology startup’s future sales revenue and profits (especially if they’re not yet profitable). Revenue forecasting is essential for planning growth and anticipating business activities that might require funding.

Forecasting allows leadership teams to estimate how much money they might need to fund sales growth to prepare accordingly far ahead of time. Rather than launching new initiatives by the seat of their pants and getting hit by nasty surprises they didn’t plan for, forecasting gives leadership teams breathing room.

However, it’s important to note that financial forecasting requires thorough knowledge of the business type and industry niche in question. Without reliable data, forecasts are useless. 

A financial forecast is powered by historical data, market research, and the right assumptions. Inaccurate forecasts squander your company’s time, effort, and resources. Even worse—they could cause you to make the wrong decisions when it matters most.

The benefits of financial forecasting

The most immediate benefit of business forecasting is that it helps a company prepare for the future by making conservative projections that account for unknown variables, such as catastrophic events like COVID-19.

Even if nothing terrible happens, financial forecasts help decision-makers predict growth in demand for their products and services, foresee future financing requirements, and estimate minimum required cash flows to stay solvent at all times. It helps a company stay on track to achieve its goals. 

By analyzing past sales and performance data and market trends, business leaders can design effective strategies (and contingencies) no matter what the markets throw at them. They’ll also notice emerging patterns within their company or the larger markets—like seasonal shifts in product demand or impending policy changes that might impact the economy—which helps them pivot safely out of harm’s way. 

Two main approaches to forecasting financial statements

Although there are numerous methods you can use to conduct financial forecasts, many analysts rely on a combination of qualitative and quantitative forecasting.

Most forecast methodologies will include at least a little bit of both. However, the type that you will rely on most may depend on several factors, such as:

  • The purpose of the forecast
  • The type of business you own
  • The current state of the markets
  • The data and resources available to you

Ideally, you want to adopt an approach that gets you the accurate results you’re looking for without draining too much of your resources. Let’s take a look at each of these financial forecasting approaches.

Qualitative forecasting methods

As the name implies, this method relies on information that can’t be measured through traditional means. Qualitative forecasting relies on input from industry experts, more extensive market and consumer trends, competitor research, and even survey feedback from your target audience. 

A qualitative approach shows you how your business fits into your industry’s greater context as a whole, allowing you to assess your performance relative to your competitors. This makes qualitative forecasting an excellent tool for attracting investors and lenders to your company. 

Qualitative forecasting also shines in situations that require long-term forecasting or assessments of new business opportunities. It’s beneficial for startups and newly established companies that don’t have a lot of historical data.

But even though a qualitative approach can be useful for anticipating a company’s finances a few months or years into the future, it still has its limits. 

For example, relying too much on human experience and decision making rather than hard data can cause you to overlook critical risks and opportunities. Too often, decision-makers think analysts can consult crystal balls when they’re mostly relying on “gut” feel and instinct (i.e., educated decision making).

Qualitative forecasting can also take a considerable toll on your finances, especially if you’re looking for the kind of detailed information that only expert consultants and researchers can provide. 

Quantitative forecasting methods

Unlike qualitative forecasting, a quantitative approach largely removes human misassumptions and human error from the equation. Quantitative analysts focus on mathematical models that crunch measurable data, like recent financing obligations and historical sales figures. 

Compared to qualitative methods, quantitative forecasting doesn’t require as much time—provided you already have the data you need and a way to process it, such as an analytics platform and a dependable team of quants. If you don’t, it can still be very costly.

Quantitative forecasting can be used to assess a company’s long-term performance, including projected sales, company growth, and much more. At the same time, it’s also beneficial for short-term projections. Since businesses and the markets they operate within are always changing, a data-driven approach that accounts for historical market states will be less risky than one that relies on human intuition and judgment.

But because you’re relying solely on your company’s historical data, quantitative forecasting doesn’t allow you to compare your organization’s performance against your competitors or larger industry trends nearly as well as a qualitative approach.

The limitations of financial forecasting

Business forecasting provides you with a snapshot of your company’s financial future and lays the foundation for your growth strategy. But of course, this tool is not without its drawbacks. 

For one, business forecasts rely too heavily on past performance to arrive at future assumptions. Financial projections don’t take into account sudden changes within your business. This retrospective focus also makes it impossible to account for and prepare for unexpected externalities.

Take the coronavirus pandemic, for example. In the past, the largest quantitative hedge funds in the world—such as Renaissance Technologies—could use historical data to outperform discretionary investors (in this example, they’re the qualitative analysts).

But due to the unprecedented speed of the March 2020 crash and V-shaped recovery, historical data was unreliable. As the markets fell, historical data told quant funds to sell. When it started recovering, the same data told them to hedge their bets if there’s a second downturn. As a result, some of the biggest quant funds suffered significant losses and ended the year in the red, while regular Americans who didn’t touch their 401ks are up nearly 15% YTD.

Put another way, one business executive confessed to a writer at McKinsey & Company in May 2020, “The five-year plan that we would be sending to the board right now is completely out the window. How do we plan in this environment when we don’t know what is going to happen?”

In other words, relying too much on historical data can prevent leadership from considering extreme and unlikely scenarios. As a result, decision-makers can fall into the trap of believing—and hoping—that the present will play out more or less like the past. But when the unthinkable happens, they aren’t prepared to pivot.

Financial forecasting software that evolves with you

Although financial forecasting does have its limitations, new advances in technology like artificial intelligence and big data can help close the gap. 

In these volatile times, business leaders need impervious financial forecasting solutions that are highly accurate and flexible enough to accommodate qualitative decision-makers. Financial modelers built Synario’s intelligent financial forecasting software for business leaders who want to make faster, better decisions with more confidence.

Synario’s forecasting engine allows you to update your models in real-time, even during presentations. This gives you the freedom to test your model across countless different scenarios in a fraction of the time it would take using traditional spreadsheets, which force you to go back to the drawing board.

Best of all, you don’t need to be an Excel expert or mathematics professor like Jim Simons (who founded Renaissance Technologies) to use Synario’s powerful and intuitive platform. CFOs, financial modelers, and stakeholders can finally speak the same language, helping decision-makers reach consensus faster than ever before.

Interested? Sign up for a demo of our software today, and you’ll also receive the “Modeling Intelligence for the Modern CFO” e-book for free.