2D calculation blocks offer a structured and efficient approach for performing repetitive calculations on rows and columns of data, reducing the need to replicate similar calculation blocks multiple times. By leveraging 2D blocks, modelers can streamline their processes and ensure accuracy across large datasets.

Understanding the Concept with an Example

Consider a company that sells four different products: A, B, C, and D. The following information is provided:

• Units sold in each period
• Base price of each product
• Escalation factor affecting price increases

The task is to calculate the revenue for each product across all periods.

There are two approaches to achieve this:

Approach 1: Multiple Calculation Blocks

In this method, you create a separate calculation block for each product. For example, to calculate the revenue for product A, you would place the base price, units sold, and price escalation factor in a vertical sequence, then apply the formula:

Revenue = Base Price × Units Sold × Escalation Factor

This process would need to be repeated for each product, leading to four separate calculation blocks.

Approach 2: 2D Calculation Block (Preferred Method)
As we know, the calculation for all products is identical:

Revenue = Base Price × Units Sold × Escalation Factor

A 2D calculation block can be designed to handle all products simultaneously. Here’s how:

   Block Structure:

     1. First, capture the base prices of all products in a vertical sequence.

     2. Next, create a block capturing the units sold across all periods.

     3. Finally, place the escalation factor which is a same ingredient for all the products.

   Block Separation: To clearly distinguish between these blocks, insert a small blank row of reduced height (e.g., 5 points) between them.

   Formula Application: Write a formula with appropriate anchoring, ensuring it references the correct cells for base price, units sold, and escalation factor. This formula can then be copied across the entire dataset, automatically calculating revenue for all products across all periods.

Why Choose a 2D Calculation Block?

While both approaches yield the same result, the 2D calculation block offers several advantages:

1. Efficiency:
   2D calculation blocks streamline repetitive tasks by allowing you to define a calculation once and apply it across the entire dataset. This approach saves time and effort, reducing the need to manually replicate calculations.
2. Ease of Review:
   Because 2D calculation blocks are concise and not spread over multiple lines, they are easier to review. A viewer can quickly assess multiple calculations in one glance, enhancing the model’s transparency and reducing the likelihood of errors.

Important Consideration: Anchoring
When creating a 2D block, it is crucial to pay close attention to anchoring rows and columns. Improper anchoring can lead to incorrect results when the formula is copied across the dataset. Ensuring correct anchoring is essential for the accuracy and reliability of your calculations.

Conclusion

Using 2D calculation blocks provides a structured, efficient, and easily reviewable framework for handling repetitive calculations across large datasets. This method is particularly beneficial when the calculations are uniform across different data sets, making it a preferred approach in financial modeling.