Stock-based compensation expense forecasting refers to calculating your company’s anticipated future expense from issuing stock-based compensation awards.

This calculation is often complex and time consuming, with many moving pieces that need to be considered.

Typical Stock-Based Compensation Forecasts

There are generally three areas where forecasts apply to stock-based compensation.

1. Core expense forecast. This forecast provides predictive insight into upcoming stock-based compensation expense, which can be leveraged by companies for strategic planning purposes.
2. Tax benefit forecast. A tax benefit forecast estimates the likely corporate income tax deduction a company will receive from issuance of awards. This is measured as the excess value to the employee upon vest relative to the grant date fair value.
3. Earnings per share dilution forecast. Companies use this forecast to predict how outstanding awards will dilute the earnings per share over time. Typically, this calculation is a subset of unamortized expense, proceeds from exercise of options, and the stock price over the forecast period.

While all three forecasts are critical for planning purposes, the expense forecast is the basis for other processes. For this reason, it should be the priority in forecasting for companies that offer stock-based compensation.

Many companies approach stock-based compensation expense forecasting with a complex system of manual spreadsheets. While this might seem like a cost-effective approach, it can overextend finance teams and lead to errors that ultimately affect your company’s bottom line.

Adopting a fully automated data solution can help your company streamline computations and come up with an accurate forecast. It can also greatly reduce errors and the complexity of the forecasting process through:

• Rapidly refreshing source files
• Using push-button reporting to generate outputs
• Providing what-if analyses
• Testing multiple forecast scenarios with different inputs and assumptions

One important rationale for leveraging automation is that it can free up time that your financial accounting team members spend performing manual spreadsheet wrangling, allowing them to focus on the reasonableness of the forecasts review.

This can help validate that forecasting assumptions are accurate and identify areas where additional precision could be applied to improve results.

Public and private companies should apply stock-based compensation expense forecasting if they:

• Have complex granting practices that can result in material expense amounts to the company
• Offer broad-based equity plans to employees
• Want to refine the accuracy of the overall company forecasts

It’s important to note that expense forecasting can become necessary before your company goes public. An experienced financial professional can help your company determine if it should forecast stock-based expenses and how to get started.

To produce an informative forecast, your company must establish effective assumptions, processing rules, and data sources.

Business Assumptions

Assumptions are the rules your company follows to align its stock-based compensation models with the anticipated future reality of award behavior. Key assumptions your company may need to consider in its expense forecast include the following:

• Anticipated stock price—if your company grants cash-settled awards, the fair value must be pegged to the current market price of traded equity.
• Planned activity, like annual grants—including future grants allows the user to tweak assumptions and see what the expense impact will be. Examples may include changes to total value granted per employee, or changes to total employees receiving awards.
• Forfeiture rates, which are baked into expense accruals—modifying forfeiture rate application to project future cancellation activity is often best practice. The method for doing this can be nuanced and often changes based on if using static or dynamic forfeiture rates.

Reliable Processing Rules

Processing rules are the procedures your company has in place to accurately forecast expenses each quarter. Key processing rules an expense forecast should include are:

• A formula-based approach that can mathematically predict how your data will or won’t meet future expectations
• Systems that can show how changes in stock behavior, grants, and other factors will impact current numbers
• Safeguards that will help your company navigate financial hardship or structural changes, such as a reduction in force

Multiple Data Sources

Additional challenges can stem from the collection of forecast assumptions. Many different teams handle moving pieces of forecast inputs, and information silos within your organization can cause headaches.

It’s necessary to include the following teams in assumption building in order to have accurate projections:

• Human resources data that includes assumptions for future grants, employee headcount growth or attrition, and performance award payout targets.
• The internal accounting team can provide insight into SBC accounting features—forfeiture rates, amortization methods, anticipated award modifications.
• Financial planning and analysis often models expected future stock price.

An equity platform can track award activity which is used as the primary data input.

Internal controls can make the difference between accurate forecasting and expensive mistakes. Here are a few your company should apply.

• Established processes. Your company should have a fully realized forecasting approach that includes systems automation. Knowing your processes will allow more time spent on review to catch any errors that may occur and create less errors to begin with.
• Review procedures. It’s important to establish procedures that help your company evaluate forecasts. It’s critical to ensure that all assumptions are considered correctly in the output is critical.
• Controls over source data. Often, companies don’t house their own data. Your company should implement controls that allow it to cross-reference source data for accuracy from outside vendors. All input data should be considered in the report output.