How it works
Use this tool to work with your Anaplan model. All processing runs locally in your browser — nothing is sent to any server.
Estimate your Anaplan module memory usage before you build
One of the most common causes of Anaplan model performance problems is oversized modules. Every line item in every module occupies memory proportional to its dimensions and data type. Understanding how module size is calculated helps you design models that stay fast and within workspace limits.
The size of an Anaplan module is determined by multiplying the number of cells by the bytes per cell for each data type. A cell exists for every combination of list members across all dimensions, for each time period, and for each line item.
Number format: 8 bytes per cell
Boolean format: 1 byte per cell — the most efficient format
Text format: Variable — approximately 4–40 bytes depending on content length
Date format: 8 bytes per cell
List format: 8 bytes per cell. Anaplan stores a reference ID, not the text of the list member name.
Reducing module size is one of the highest-impact optimizations you can make to an Anaplan model. Even modest reductions translate directly to faster calculation and lower memory usage.
Remove unnecessary dimensions: The most powerful lever. If a line item doesn't actually vary by Products, remove the Products dimension from that specific line item (or move it to a smaller module without Products).
Use Boolean instead of Number for flags: A flag line item that is always 0 or 1 should be Boolean format, saving 7 bytes per cell — this adds up fast across large dimensions.
Archive historical time: Unused historical time periods still occupy memory. Archive time periods you no longer need in your planning horizon.
Split large modules: Break modules with mixed line item types into smaller, purpose-specific modules. A module with all Booleans will benefit from sparsity optimization; mixing types prevents this.
Anaplan's calculation engine applies sparsity optimization — it doesn't store cells that are empty (zero or blank) if it can determine they'll always be empty. This means your actual module footprint may be significantly smaller than the theoretical maximum calculated by multiplying all dimensions.
Sparsity is most effective when: list hierarchies are well-defined with clear parent-child relationships, formulas are structured so empty inputs produce empty outputs, and Boolean line items are used for sparse flags.
Sparsity is defeated by: constant values applied across all cells, complex formulas that force evaluation of every cell, and modules where every cell genuinely needs a value. Our Module Size Calculator shows the theoretical maximum — your actual size in Anaplan will typically be 10–50% of that number for well-designed models.
Workspace size limits depend on your Anaplan subscription tier. Most enterprise workspaces range from 40 GB to several hundred GB. However, best practice is to design your model to use as little memory as possible — smaller models calculate faster regardless of the available limit.
Go to your module's Blueprint view, then look at the model settings or use the Model Optimization Workbench (MOW) if your workspace has it enabled. The MOW provides actual memory usage per module and per line item, which is the most accurate way to identify large modules.
Yes, every line item adds to the module's footprint. However, strategically adding helper line items that simplify other formulas can actually reduce total model size by improving sparsity and allowing the engine to avoid re-calculating complex intermediate results. The key is to audit line items periodically and remove those that are no longer needed.