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Scenario Analysis (What Ifs) Tips & Techniques For Power BI

Today, I wanted to cover in detail some fantastic scenario analysis techniques you can use inside of Power BI.

 

Power BI is an amazing tool if you want to predict what may happen in the future or alternatively see what could have happened in the past based on certain variables changing in your data.

 

To run scenario analysis, first, you have to get to know more about the 'What If' feature. This is what this first tutorial is all about; how you can find and utilize the 'What If' feature inside of your Power BI reports.

 

Once you understand how to utilize this feature, then you can leverage it to create some advanced and interesting insights around scenarios which could occur based on changes in your data.

 

 

The next approach is what I call Multi-Layered scenario analysis. This is where we can incorporate numerous different variables, or factors, into our analysis so we can see how our results change based on how the variables could also change.

 

A perfect example of this is when you have a business which sells goods.

 

There are many different variables that could determine your ultimate results or performance. These may include changes in demand, price, import costs, and exchange rates. These are all variables that could change and that's where this Multi-Layered approach comes in. It enables you to solve for all of these adjustments and scenarios that could play out in the future.

 

 

In this last example, I want to showcase a prediction example that really highlights how far you can take this subset of analysis inside of Power BI.

 

This is a really detailed example that was part of a wider workshop that I've run before. This breakout session shows you the power of the 'What If' feature and Scenario Analysis techniques inside of Power BI.

 

Certainly well-worth reviewing, especially if you're working in some sales environment or running analysis on financial results.

 

 

These are possibly my most favorite analytical techniques in Power BI. Mainly due to the fact that they were so difficult to complete historically.

 

The value that you can generate from running multiple scenarios and understanding what might happen in the future is just really powerful stuff and will definitely add value to the consumers of your reports.

 

 

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