How to Incorporate Rolling Forecasts into Budget vs. Actual Reports in Power BI

Budget vs. actual reporting is a critical process in financial management, providing insights into how closely a company’s financial outcomes align with its financial plans. However, in a dynamic business environment, static budgets alone can be limiting. This is where rolling forecasts come into play. Rolling forecasts allow organizations to continuously update their financial predictions based on the latest data, helping them stay agile and responsive to changes.

In this blog post, we’ll explore how to incorporate rolling forecasts into your budget vs. actual reports using Power BI, with a practical example to illustrate the process.

Understanding Rolling Forecasts

Rolling forecasts extend beyond the traditional annual budget by continuously projecting future financial performance over a set period (e.g., 12 months). As one month ends, another is added to maintain a consistent forecasting window, enabling businesses to adapt to changing market conditions.

Step-by-Step Guide to Incorporating Rolling Forecasts in Power BI

1. Prepare Your Data

• Budget Data: Ensure you have your budget data for the relevant periods (e.g., annual budget broken down by month).

• Actual Data: Collect the actual financial data up to the current period.

• Forecast Data: Gather your rolling forecast data, which should include updated projections for future periods.

Example:

• Budget Table: [Date], [Category], [Budget Amount]

• Actual Table: [Date], [Category], [Actual Amount]

• Forecast Table: [Date], [Category], [Forecast Amount]

2. Load Data into Power BI

• Import the Budget, Actual, and Forecast tables into Power BI using Power Query.

• Ensure that all tables are properly formatted and that date fields are consistent across the tables.

3. Create Relationships

• In the Power BI model view, establish relationships between the Budget, Actual, and Forecast tables based on the [Date] and [Category] fields. This ensures that data from different tables can be analyzed together.

4. Create Measures for Analysis

• Define the measures needed for analysis. These may include:

  • Total Budget: Total Budget = SUM(Budget[Budget Amount])

  • Total Actuals: Total Actuals = SUM(Actual[Actual Amount])

  • Total Forecast: Total Forecast = SUM(Forecast[Forecast Amount])

  • Variance (Actual vs. Budget): Variance = [Total Actuals] - [Total Budget]

  • Forecast Variance (Forecast vs. Budget): Forecast Variance = [Total Forecast] - [Total Budget]

5. Create a Rolling Forecast Measure

• Implement a rolling forecast measure to dynamically calculate the forecast values for the next periods:

DAX

Rolling Forecast = CALCULATE( [Total Forecast], FILTER( ALL(Dates), Dates[Date] >= MIN(Actual[Date]) && Dates[Date] <= MAX(Dates[Date]) ) )

• This measure adjusts based on the current date, ensuring that the forecast remains up-to-date as new actuals are added.

6. Visualize the Data

• Use Power BI’s visualization tools to create a comprehensive report:

  • Line Chart: Show the trends of Budget, Actual, and Forecast amounts over time.

  • Bar Chart: Compare Budget vs. Actuals for each period.

  • Variance Analysis: Highlight areas where Actuals significantly deviate from the Budget and Forecast.

Example:

• A line chart displaying the budget, actuals, and rolling forecast across a 12-month period, with the rolling forecast dynamically adjusting as new actual data is input.

7. Implement Dynamic Filtering

• Add slicers for time periods (e.g., Year, Month) and categories (e.g., Departments, Expense Types) to enable users to drill down into specific areas of interest.

8. Automate Data Refresh

• Schedule automatic data refreshes in Power BI to keep your rolling forecast and budget vs. actual report up-to-date without manual intervention.

Practical Example

Let’s say your company has budgeted $1,000,000 in revenue for the year, with $83,333 planned for each month. By the end of June, actual revenue is at $470,000, falling short by $30,000. Your rolling forecast for the remaining six months adjusts based on market trends, predicting $540,000 in revenue, which totals $1,010,000 for the year.

In Power BI, you would visualize this as:

• Budget: Steady line at $83,333 per month.

• Actual: Line tracking actual revenue month by month.

• Rolling Forecast: Line adjusting from July onwards, reflecting the updated $540,000 prediction.

Conclusion

Incorporating rolling forecasts into your budget vs. actual reports in Power BI enhances financial planning by providing a more flexible and responsive approach. This ensures that your organization can make informed decisions based on the latest financial data. By following the steps outlined in this blog post, you can create powerful, dynamic financial reports that keep pace with your business’s evolving needs.

Power BI’s ability to handle complex calculations and present data visually makes it an invaluable tool for modern financial reporting. Start incorporating rolling forecasts into your reports today and experience the benefits of more adaptive financial management.