3 Essential Types of Variances Every FP&A Analyst Should Know

How FP&A Analysts Leverage Different Types of Variances

In FP&A, your ability to explain what’s behind financial shortfalls and overruns is just as important as the numbers themselves. Understanding different types of variances helps you identify planning assumptions that didn’t materialize, adapt forecasts based on emerging trends, and track how business expectations evolve over time. 

However, not all variances are created equal. Depending on what you’re comparing, you’ll uncover insights for measuring budget accuracy, tracking forecast adjustments, or evaluating changing business assumptions. This guide explores the three types of variances that every professional should know.

1. Budget-to-Actual Variances

In FP&A, budget-to-actual variances measure the differences between your planned budget figures and the actual results achieved.

You can calculate variances at different levels of detail. At the highest level, you might analyze the overall variance in EBITDA (earnings before interest, taxes, depreciation, and amortization). This total variance comes from the combined variances in revenue, costs, and operating expenses. Each of these components might have further variances within individual line items.

You can also apply variance analysis to specific items. For instance, you might compare actual sales to a particular customer against what you budgeted or analyze how your actual cash balance differs from your cash budget projection.

Example of Budget-to-Actual Variance

Consider a company that budgeted $2 million in fixed costs but actually spent $2.2 million. This creates an unfavorable variance of $200,000 — 10% over budget.

This variance serves as a starting point for investigating why the overspend occurred. When you created your budget, you made specific assumptions about staffing levels, resource requirements, facility costs, and operational efficiency. The variance signals that one or more of these assumptions didn’t match reality.

Further analysis into fixed costs could reveal other factors, such as:

• Additional personnel hiring (a headcount issue), 
• Unexpected maintenance costs (a facility issue), or 
• Inefficiencies that increased operating expenses (a productivity issue). 

Understanding which assumptions were incorrect helps you improve future financial planning and take appropriate corrective action.

2. Forecast-to-Actual Variances

While similar to budget-to-actual variances, forecast-to-actual variances have important distinctions. Budgets typically represent annual plans that remain relatively fixed, while forecasts are more dynamic and flexible in their timeframes and inputs.

Forecasts can span various time horizons including:

• Short-term (like a 13-week cash flow forecast).
• Long-term (such as a three-year strategic forecast). 

FP&A professionals update forecasts frequently to incorporate changing information and new data that emerge after the annual budget is set. While budgets often start with strategic targets, forecasts draw from multiple inputs: 

• Historical data. 
• Emerging trends. 
• Business drivers and assumptions.
• Real-time business intelligence. 

This makes forecast-to-actual variances particularly valuable for understanding how well your most current predictions align with reality.

Example of Forecast-to-Actual Variance

Forecast-to-actual variances can also examine differences between specific inputs and drivers. For an oil and gas company, this might involve comparing the actual spot price of ethanol versus the futures price that was expected. Consider this example:

The table reveals that if price were the only factor, revenue would have declined by $400,000 ($0.50 × 800,000). 

However, the actual revenue variance was only $200,000. This is because volume increased by 100,000 ounces, generating an additional $200,000 ($2.00 × 100,000) that partially offset the price decline. 

Therefore, the price variance explains only 50% of the net revenue variance, with volume changes accounting for the other 50%.

Analyzing forecast-to-actual variances improves your decision-making process in three key ways: 

1. By establishing a structured approach to evaluate your predictions.
2. By creating a system to regularly update forecasts with new information.
3. By helping you identify patterns in what you consistently overestimate or underestimate, allowing you to refine future forecasting accuracy.

3. Forecast-over-Forecast Variances

The third essential type of variance involves comparing different versions of your forecasts over time. This approach reveals how your expectations and assumptions have evolved.

Example of Forecast-over-Forecast Variance

Suppose you create a January revenue forecast predicting your organization will bring in $1.5 million in revenue (Forecast 1). A month later, you roll this forecast forward, so it now covers February through the following January. You also update the prior January with the actual revenue generated — $750,000 — and incorporate new data and assumptions based on current business conditions (Forecast 2).

When comparing these forecasts, two distinct variances emerge:

1. Forecast-to-Actual Variance: January’s actual revenue was $750,000 against a forecast of $1.5 million, creating a $750,000 unfavorable variance. This measures the accuracy of your original prediction.
2. Forecast-over-Forecast Variance: For the overlapping months (February through December), you can compare what you originally predicted in Forecast #1 versus your updated predictions in Forecast #2. These differences show how your expectations for future months have changed after seeing January’s results.

The following table illustrates how forecast-over-forecast variances appear when comparing two consecutive forecast versions:

As shown in the table, January represents a forecast-to-actual variance, while February through December shows forecast-over-forecast variances. Notice how some months show no change between forecasts, while others show significant revisions to expectations. 

These patterns reveal how your business outlook evolved after receiving January’s actual results. For instance, if there’s zero variance in all future months between forecast versions, this implies you’re revising the annual forecast downward by the amount of the January miss. You’re essentially saying, “We missed January by $750,000, and we don’t expect to make it up elsewhere.”

Conversely, if Forecast 2 shows a positive variance of $750,000 in February compared to Forecast 1, this suggests you expect the January miss to be realized one month later. If the positive variance is only $500,000, this may indicate that market conditions have changed, and you now expect lower overall performance for the year.

How to Apply Different Types of Variances in Financial Analysis

Understanding these three types of variances gives you a comprehensive toolkit for analyzing financial performance. Each type serves a different purpose:

• Budget-to-actual variances help you evaluate performance against your annual plan.
• Forecast-to-actual variances provide insights into more recent predictions and current business conditions.
• Forecast-over-forecast variances reveal how your outlook is changing over time.

By knowing all three, you’ll develop a more nuanced understanding of business performance and be better equipped to provide valuable financial insights to leadership.

Remember that effective variance analysis isn’t just about identifying variances — it’s about understanding why those differences occurred and what they mean for the business going forward. This analytical approach transforms variance analysis from a simple reporting exercise into a powerful decision support tool.

From Analysis to Insight: Maximizing Value from Types of Variances

Proficiency with the three types of variances allows you to spot emerging trends, identify potential issues, and uncover opportunities that might otherwise remain hidden in financial data. When applied effectively, these analytical tools enable you to provide the actionable insights that drive strategic business decisions.

The most successful FP&A professionals can seamlessly move between different types of variances, choosing the right analytical approach for each situation. They understand how to interpret the results within the broader business context and communicate findings in ways that resonate with stakeholders across the organization.

Ready to enhance your variance analysis skills and develop a complete FP&A toolkit? CFI’s FP&A Specialization provides hands-on training in essential financial modeling and analytical techniques. Through practical case studies and expert instruction, you’ll learn how to apply these concepts to real-world financial challenges and elevate your impact as an FP&A professional.

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Additional Resources

How to Analyze Budget Variances with 10 Essential Questions

KPIs in FP&A: Measuring What Matters Most

Managing Uncertainty with Sensitivity Analysis

See all FP&A resources