---
title: "Cells and Limits"
source_url: https://support.lucanet.cloud/en/documentation/xp-a---extended-planning-and-analysis/working-with-models/cells-and-limits
language: en
last_updated: 2023-08-16
---
# Cells and Limits

## Overview

A **cell** in xP&A represents a single number in the spreadsheet.

The **model cell count** is the total number of cells when all variables and dimensions are expanded across all scenarios in a model.

Your **organization's cell count** is calculated by adding together the cell counts of each of your models.

When using xP&A, there are **limits** on the number of cells that can be used across your organization.

The default limit is 150 million cells. (If you need more than 150 million cells, then please get in touch with us to increase the limit.)

The more cells you use, the more it affects the **performance of your model**.

In this article, you can find examples on how your cells are counted and information on how proper dimension linking can influence your cell count.

## Example 1: P&L

Suppose that you have a P&L model in xP&A:

- Your P&L has 50 line items, represented by **50** variables.
- Your P&L is broken down into **10** departments, represented by a **Department** dimension.
- Your P&L is **monthly**, with 4 years of historical data and 1 year of forecasts ( **5** years total).

The cell count of your P&L would be calculated as follows:

- Variables: **50**
- Dimension items per variable: **10**
- Time steps: 12 x 5 = **60**

**Total = 50 x 10 x 60 = 30,000 cells**

## Example 2: Cohort Model

Suppose that you have a SaaS revenue model with monthly cohorts:

- You have **3** different products, represented by a **Product** dimension.
- You have customers in **5** countries, represented by a **Country** dimension.
- You are modelling the customer build (new, churn, expansion, contraction, total) and ARR build, represented by **10** variables in total.
- Your model has 5 years of historicals and 5 years of forecasts ( **10** years total), with **monthly** cohorts.
- You have **3** scenarios with different assumptions: base case, upside, downside.

The cell count of your cohorted revenue model would be calculated as follows:

- Variables: **10**
- Dimension items per variable: 5 x 3 = **15**
- Time steps: 12 x 10 = **120**
- Cohort items per variable: **120**
- Scenarios: **3**

**Total = 10 x 15 x 120 x 120 x 3 = 6,480,000 cells**

## The Importance of Proper Dimension Linking

When modeling employee data, it's essential to understand that each employee exists within a specific organizational structure. Every employee is assigned to:

- **One team**
- **One job title**
- **One department**
- **One region**

Because of these one-to-one relationships, dimensions must be properly linked to reflect these real-world constraints.

## Impact of Linked Dimensions on Cell Count and Model Performance

**With Proper Dimension Linking**

When dimensions are correctly linked, the model efficiently allocates resources based on the actual organizational structure. For our scenario (1 month, 1 scenario, no additional dimensions), this results in:

- 1,000 cells for 1,000 employees

**Without Proper Dimension Linking**

When dimensions are not linked, xP&A treats each dimension as independent and calculates all possible combinations, resulting in:

- 1,000 employees × 150 job titles × 40 departments × 20 regions × 30 teams\
\
= 3,600,000,000 cells

This dramatic difference—from 1,000 cells to 3.6 billion cells—demonstrates why proper dimension linking is not just a best practice, but a critical requirement for model performance and system stability.

{% idea-box %}
Always verify your dimension relationships before implementing your model to avoid exponential cell growth and potential system performance issues.
{% /idea-box %}