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Create monthly re-forecasts

Rob Markwell

Last Update 5 เดือนที่แล้ว

Understanding monthly re-forecasts

Monthly re-forecasting is a financial planning methodology that involves the regular updating and recalibration of financial projections on a month-to-month basis. Unlike static annual budgets, this approach acknowledges the dynamic nature of business and enables finance teams to align their strategies with the ever-evolving economic landscape.


This provides the finance team with a number of strategic benefits:

  • Responsive decision making - respond to an ever changing market and update assumptions and forecasts to match your latest view
  • Real time insight and accuracy - regular updates with the latest data enhances the accuracy of the financial projections
  • Proactive strategic planning - waiting for annual budgets to make decisions is impractical. Keeping updated re-forecasts enables finance teams to stay ahead

Using scenarios to create re-forecasts

In Blox, each scenario has a Forecast Start date. Data before the start date is considered Actuals, and after the start date is considered Forecast.


You can set the Forecast start date when creating new scenarios

This allows us to create multiple scenarios in a single Blox model which correspond to different forecasting periods. In this example, we:


  • Created a baseline scenario in January 2024 which forecasts the next 18 months
  • Re-forecasted in April 2024 following Actuals data for Jan-Mar 2024


The re-forecasted scenario shows us the expected position of the business, taking the Actual values for January to March plus the updated forecast values (based on any updated assumptions) from April 2024 to the end of the model period.


The actual period is displayed as a shaded area in charts and tables

Comparing re-forecasts

When you have multiple scenarios with different start dates, you can easily compare them using the Blox comparison features.


This helps create a quick Forecast vs Actuals comparison between what was initially forecasted and the actuals for that period - along with the expected overall impact on the full model timescale

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