Without a financial forecast, as a business leader you’ll have a hard time gaining funding and essentially be navigating without a compass. Still, a forecast is by definition an educated prediction, subject to the usual disruptive external forces and human predilection for either irrational exuberance or excess pessimism.

Calibrating a forecast to account for these variables is possible. Still, developing accurate financial scenarios, along with managing cash flow, is one of most pressing challenges for CFOs.

What Is a Financial Forecast?

A financial forecast is a projection of a company’s likely future outcomes; forecasts are developed by finance leaders and consumed by business managers, investors and other key stakeholders.

Financial forecasts may leverage historical actuals, external market and economic factors and strategic internal plans to develop one or more scenarios of how a company may perform in the presence of future variables. Forecasts can alert business leaders to possible future changes in revenue and expenses so that they may act proactively—such as by staffing up or acquiring more inventory—and set financial expectations appropriately.

Financial forecasts are developed from pro forma financial statements. Pro forma financial statements present both historical actual and future estimates of a company’s performance.

Pro Forma

The effects of a future transaction on past financial statements. Answers the question “If we had made this transaction earlier—say, bought a competitor or key supplier—the effect on our financial statement(s) back then would have been.”

Pro formas typically include:

The Income Statement

This report portrays a company’s profit or loss over a specified period. Financial forecasts indicate the implication of potential variables on revenue, cost of goods sold, expenses and other factors that could affect a company’s bottom line.

The Balance Sheet

The balance sheet represents a company’s position at a point in time. Forecasts may look at how factors such as cash collections, amounts owed to suppliers or financing through debt or equity may affect the company’s overall position at various points in the future.

The Statement of Cash Flows

The cash flow statement is plain and simple: How much cash do you plan to have coming in and going out at a given point in the future? Both the income statement and balance sheet forecasts will help determine future cash projections that are critical to running a business—or to help companies determine when they may run out of cash.

Forecast vs. Actuals

A critical part of the month, quarter, and annual close processes is to assess how actual financial performance compares with forecasts. Many businesses have multiple forecasts based on pre-determined variances to prepare for what the future will hold if progress continues on the same trajectory, as well as best-case (growth factors) and worst-case scenarios.

While most business would love for their projections to match their “best-case” scenarios, it’s rare that all variables perfectly align with estimated projections. During the evaluation process of comparing forecasts and actuals, management will review significant variances on a line-by-line basis and assess what occurred that was not accounted for in the forecast.

Economic upswings or downturns and other external factors often affect actual performance; in case of a significant disruption, management may choose to revise the forecast. This process, called reforecasting, is common and uses actuals to reassess forecasts on a rolling basis to ensure that future financial projections factor in what is actually happening at a company, on as much of a real-time basis as possible.

By analyzing forecasts vs. actual performance and reforecasting, management is able to highlight where it needs to allocate resources or adjust targets.

Traditional vs. Rolling Forecasts

Traditional Forecasting Rolling Forecasting
Fixed financial plan calculated for a set period of time, typically one year, that uses historical observations to estimate future business metrics. A “live” financial plan that is regularly updated throughout the year to reflect changes.
Calendar-based (annual, quarterly) Event-based with real-time adjustments to calendar forecasts
Fixed targets (sales/profit, other KPIs) Dynamic adjustments to targets based on external/internal events
Resource allocations are rigid May trigger reallocation of resources based on dynamic targets
Manual, account-based and often linked to accounting cycles Business-driver-based and connected to operations

Budgeting vs. Financial Forecasting

Budgeting and forecasting are two distinct tools used by management to evaluate performance.

A budget is a plan that quantifies expectations that a business wants to achieve for a specified period. A financial forecast is different in that it leverages variables to estimate future outcomes, whether those are desirable or not. In other words, a budget is management’s plan, while a financial forecast is a prediction.

The two tools also differ in how they are used. The budgeting process is typically performed before the end of the fiscal year. It’s a collaborative process between a number of stakeholders where management sets achievable goals based on past performance and known business changes for the coming year—and to determine where to allocate your company’s resources. Throughout the year, actual performance is evaluated against the baseline budget, and variances are analyzed.

Forecasting, on the other hand, does not measure performance based on variances. Forecasts are estimations of future performance based on variables and scenarios. They’re frequently updated when new information is brought to management’s attention and used to strategize, plan and even create budgets. A complete financial forecast includes projected revenue, assets, liabilities, cash flow, and operational KPIs.

For example, if a competitor opens up down the street, the management team may run various forecasts to predict how this event could affect future revenue. They may choose to budget for additional marketing costs in future months to keep new customers coming in the door and revenue consistent. The tools work hand in hand.

Financial Forecasting vs. Financial Modeling

There is no way to definitively predict the future. The best financial forecasts come from using a complete representation of relevant historical data and all future information that is reasonably certain. To cover the variable factors that can impact performance, financial forecasters should use financial models, which effectively parse through various outcomes, weighted by the likelihood of specific what-if scenarios playing out.

There are two basic forms of financial modeling:

  • Quantitative models: Statistical data that uses industry and economic values from various sources as well as research that includes core financial benchmarks, such as GDP growth and price-to-earnings ratios.
  • Qualitative models: Information that is not bound by statistical data but instead is subject to other considerations, such as collective decision-making by all stakeholders capable of directly or indirectly affecting financial performance.

Benefits of Financial Forecasting

Financial forecasting allows management to predict how a business will perform in the future. By brainstorming variables, leadership teams can create scenarios that prepare them to act proactively and plan accordingly.

For example, by forecasting revenue over the next 18 months, a business could plan for how it will respond if projected economic indicators do or do not manifest.

By using both assumptions and drivers, companies can plan for a multitude of scenarios and how they might affect various areas of the business, including:

  • Future expansion, including necessary cash flow and staffing to support initiatives.
  • New products or services to gain additional revenue streams.
  • Demand planning for inventory.
  • Launching a customer acquisition or retention project.
  • Cash flow.
  • Workforce planning.

Challenges of Financial Forecasting

Financial forecasts can guide better decision-making—presuming the models and data used to create them are reliable. However, a survey of participants during a webcast by Ernst & Young (EY) (opens in a new tab) showed that only 9% were “very confident” in their ability to forecast demand for their products and services. More than one-third, or 35%, said they were “not at all confident” or “not very confident” in their forecasting abilities.

Why is that?

Plenty of variables can affect the accuracy of a forecast, and not just economic factors. Often, the most difficult variable to account for is a company’s data that is used to create the forecasts in the first place. Many companies leverage a multitude of systems to run their businesses; perhaps a CRM, HCM, a general ledger, an inventory management tool and an ecommerce platform.

The only way to create a forecast is to download data from these sources and aggregate it in Excel. Once data is aggregated, it can be manipulated and formulas applied; only then can forecasts be analyzed.

Several challenges can arise during this process.

  • Static data. The moment data is downloaded into Excel, it becomes static. But businesses aren’t static. Data changes, transactions are reversed and altered. Material changes to, for example, inventory levels made after that data is downloaded means that forecasts may not be based on the most complete and accurate information.
  • Unified sources of data. Oftentimes, data sources used to forecast don’t “talk” to one other. Rather, data is manually entered, and changes made in one system may not be reflected in others. This can create several problems, among them the possibility of duplicate records and the inability to reconcile transactions. A lack of “truth” makes it hard to feel confident that forecasts are built on accurate information.
  • Errors. Any process with many manual steps has an increased propensity for error and version control. The standard forecasting process in Excel has a number of manual steps and typically caps the process off with complex formulas. However, one small error in a formula—or in any of the aggregation and manipulation steps—could have significant effects on forecasting.
  • Issues with understanding the business impact. A manual forecasting process is difficult to manage, so the finance team can waste too much time just ensuring accuracy or fixing errors. That leaves little time left to understand the specific issues impacting business units.
  • Transparency issues. With crucial information stuck on separate files across the organization, there’s no central repository of information for everyone to work from. This lack of transparency often translates into a lack of trust between business units and finance leaders.

These challenges just add to the reasons so many executives don’t feel confident in their companies’ forecasting processes.

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6 Steps to Creating Your Financial Forecast

So how do you create a forecast that stakeholders can trust? The six steps below will get you started:

  1. Align the process of financial forecasting with modeling and budgeting, ideally with a unified solution or tools that are well-integrated.
  2. Establish a methodical approach to maintaining historical data that analysts can tap when building models and creating forecasts.
  3. Create a pro forma income statement that projects expenses and revenues. If you’re seeking funding, you may include a P&L statement that provides important details that can be used to calculate key metrics like EBITDA and that gives investors insight into operational performance.
  4. Build a pro forma cash flow statement that outlines your opening balance, sources of revenue and outlining operating expenditures to project net cash flow. The cash flow statement should include cash flows from operating, investing and financing activities.
  5. Create a balance sheet that shows all assets—current and non-current—as well as total liabilities including accounts payable, lines of credit, amounts borrowed and total equity
  6. Consistently re-evaluate the financial forecast, especially as business or economic conditions show signs of changing or in the immediate aftermath of an event that can have any form of impact in your business.

Finally, companies with very large data sets may want to investigate machine-learning tools. By adding more inputs and greater data volumes to the forecasting equation, companies can render more accurate predictions. What sort of big data? Think buying patterns, fraud detection, real-time stock market information, customer segmentation and more.