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Using the Sensitivity Analysis

A key tool to getting to the nuts & bolts of your business
Written by Max Valentine
Updated 1 year ago

Investing and most financial decisions are based on many assumptions, but nothing is certain. Sensitivity analysis is one way to explore how changes in conditions might affect your results. Sensitivity analysis is a financial modelling tool that helps you analyse how different values of a given variable (a factor that can vary) affect the outcome, assuming other conditions stay the same.

This tool is often known as a “what-if” analysis or a simulation analysis because it helps you predict how an outcome might change “if” a variable in that situation changes. For example, it can help you estimate how changes in inflation might affect interest rates or how variations in material costs will affect profit.

Sensitivity analysis is vital to getting to the nuts and bolts of your business. It enables you to figure out which are the crunch inputs, in other words, the ones where a small change can make a big difference to the model outputs.

This analysis can also help you in determining the right level of pricing, margins and most importantly the minimum levels that you can charge / earn just to keep your head above the water. Such insight is vital when negotiating supply or a sale.


Let’s say you run an online Keyboard website, and you know it is busiest in December. If you’d like to know how the increased online traffic might impact your revenue, you can conduct a sensitivity analysis.

In this case, you will keep all other elements of your business the same so you charge the same prices and also expertise the same conversion rates. You can toggle the Order Volume up. Let's say the Christmas rusk will be a 20% uplift in the number of orders.

This shows that if this was the case


On Numberslides, you can toggle your assumptions up or down by up to 20% to see the impact on the outputs - namely the investor return, the business valuation and the multiple on the invested capital. It is as simple as that.

The bigger the change from the toggling of the assumption shows you which assumptions are elastic or most sensitive. This means small changes in the assumptions result in magnified changes to the outputs. For these assumptions, you need to make sure you have validated them and that they are as realistic as possible.
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