What is a rolling forecast?
The definition of a rolling forecast is a report that uses historical data to predict future numbers continuously over a period of time. Rolling forecasts are often used in financial reporting, supply chain management, planning, and budgeting across every department. The rolling forecast is an essential aid in making sound business decisions.
Rolling forecasts are more agile than static forecasts, which project numbers based on a single time frame, say January through December. Instead, rolling forecasts drop a month as it passes, forecasting the next month automatically. In other words, they allow you to plan continuously over a predetermined time horizon. This way, you’re always looking into the future based on the most recent numbers and time frame.
Rolling forecasts are especially useful in today’s tumultuous, digital business environment, which is fast, fluid, and ever-changing. They enable a company to plan, respond, and refocus their efforts quickly and with less impact as market conditions change.
The Benefits of Rolling Forecasts
Because of their responsive nature, rolling forecasts help businesses respond to changing market conditions faster. When used effectively, rolling forecasts can help you identify performance gaps, shorten planning cycles, and sort out the best decision for your bottom line.
Rolling Forecast Best Practices.
Use a CPM system: How can you create a rolling forecast? Certainly not in Excel alone. Spreadsheets are prone to inefficiency, errors, and miscommunications. Instead, a corporate performance system allows you to draw figures from a single source of data and play out scenarios in a sandbox that doesn’t alter source data. This is a much more effective and accurate way of producing rolling forecasts.
Automation: Traditionally, finance has created forecasts in Excel before loading them into an enterprise resource planning system. But forecasting future periods becomes difficult, labour-intensive, and error-prone in Excel. A corporate performance management system that automates rolling forecasts simplifies this process.
Driver-based forecasting: Drivers are used to help create more accurate forecasts. Drivers are specific factors like “units” and “price per unit,” rather than aggregated, overarching percentages. For example: Let’s say you were in the microwave business. You could forecast the number of microwave units and the revenue per microwave unit. Then, you could use the driver-based forecast to understand your revenue forecast variance. For example, if you exceeded your forecast, was it because of the units sold or the pricing? A driver-based forecast would indicate the difference.
What-if scenarios: Based on your driver-based forecast, you can test our different drivers to see their impact on subsequent months. Going back to our microwave analogy, you could test out the effects of a sale on your units sold and your prospective profits.
Variance analysis: To measure the effectiveness and accuracy of your rolling forecast, you can measure the variance between your forecasted and actual results.