I want to go over how to calculate dynamic profit margins in Power BI. This is something I consider to be quite straightforward if you’ve been using Power BI for some time. But if you’re just starting out, this could be challenging to piece together. This kind of information is something that most organizations need.
I want to dive deeper and show you the ways of implementing some sensitivity analysis examples in your Power BI model. Sensitivity analysis is a very important financial model. It helps businesses in predicting the outcome of a certain scenario, like customer and cost changes, to the overall gains of company. In a previous tutorial
In this post, we’re going to look at an analytical insight where we find out if our profit margins grew together with our revenue. We can do this through the use of Power BI measure branching. This is important because we want to see if revenue expansion or getting the market share is actually good
Here we’re going to look at customer margin contraction. We’re going to try and work out what customer margins are contracting and why are they contracting. Is it because of their purchasing frequency? Is it because of the products they’re buying? Or because of some other reason? We’re going to solve this analytical problem with
We’re getting specific today and really showcasing the analytical power of Power BI. Sensitivity analysis, or even running some ‘what ifs’ around this, allows you to almost predict what may happen in the future with your results. In this example, I want to see what will happen to my profitability if I am able to
