SAP Analytics Cloud Excel Add-in: Optimized Forecast Blocks

When working with planning and forecasting using the SAP Analytics Cloud Excel Add-in, a frequent challenge is managing Actuals and Forecast data together without breaking formulas or requiring constant manual updates.

Previously, in our blog SAC Excel Add-in Rolling Forecast, we described how to build rolling forecasts using the SAC Excel Add-in, focusing on dynamic date selection and version filtering.

Based on further practical experience, this article presents a more optimized report structure that reduces manual adjustments and improves Excel formula stability.

Why Asymmetrical Filters Matter in SAP Analytics Cloud Excel Add-in Forecasting

In real planning scenarios, Actual and Forecast data rarely cover the same time range:

  • Actuals stop at the last closed period.
  • Forecasts begin in the next open period.

Trying to manage this with a single symmetrical filter often leads to:

  • Overwritten formulas
  • Manual reassignments every month
  • Hard-to-read logic
  • Higher maintenance effort

By contrast, asymmetrical filters in the SAP Analytics Cloud Excel Add-in allow each version block to have its own tailored date set, making forecasting tables clean, predictable, and formula-friendly.

The Block-Based Design Explained

The optimized approach structures the table into two dedicated blocks:

  • Actual Block – contains only historical months up to the Assigned Date.
  • Forecast Block – contains only future periods beyond the Assigned Date.

This ensures:

  • No overlap between Actuals and Forecast
  • Fixed column positions
  • Excel formulas remain intact and never require rewriting

Implementation Steps

Split the Date into Year and Month rows – makes filtering and logic easier.

InsightCubes_SAC_Excel_Add_in_Get_Date

Define a Version column – distinguish between Actual and Forecast.

Apply dynamic formulas for date logic – assign each month to the correct data category:

The first formula handles months before or equal to the cutoff.

InsightCubes_SAC_Excel_Add_In_MonthCutOff

The second formula handles months after the cutoff through December.

InsightCubes_SAC_Excel_Add_In_MonthCutOff_till_December
InsightCubes_SAC_Excel_Add_in_DateSelection

Create separate blocks based on the Actual and Forecast selection.

InsightCubes_SAC_Excel_Add_in_Block_Formula

Assign blocks to the report table – ensures stable layout and formula integrity.

InsightCubes_SAC_Excel_Add_In_Assymetric_Filter

Why Leaving Space on the Left Side Is Critical

A common pain point is losing formula stability when columns shift due to filters. In the previous blog, we showed how dynamic date selection enhances rolling forecasts – but without reserved space, formulas often broke as time periods changed.

In this optimized design, we intentionally reserve space on the left side so that:

  • Users can insert Excel formulas
  • Calculations reference fixed cell ranges
  • Notes, variance logic, and helper columns remain intact
  • The table stays formula-friendly even after data refresh

This simple design consideration is highly effective -especially for finance professionals relying on Excel logic alongside SAC data

Benefits of the Optimized Approach

  • Fixed structure – report layout doesn’t shift monthly
  • Formula stability – no rewriting required
  • Clear Actual vs Forecast separation
  • Simplified maintenance
  • Improved readability and usability
  • Scalable – easily extends to future years or rolling periods

Most importantly, this method aligns with how planners and analysts think: past data stays static, future projections change, and the layout supports both without confusion.

Final Thoughts

While our previous blog introduced the concept of a rolling forecast, this optimized approach takes it further by providing:

  • Excel-friendly layouts
  • Stable time filters
  • Independent blocks for version control

The result is a robust, flexible, and user-friendly report in the SAP Analytics Cloud Excell Add-in, making it easier for end users to write formulas, compare Actuals vs Forecast, and maintain the model over time.

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