Operating Profit Margin (OPM) is the percentage of revenue that remains after subtracting the cost of goods sold from the revenue generated by your product or service.
For example, if your company generates $100,000 in revenue and $50,000 in cost of goods sold, your OPM is 50%.
Operating profit margin is a great metric to use when determining whether or not your company is profitable. If your company is not profitable, you should look closely at your operating expenses and determine if they are necessary. If they are, you should look for ways to reduce them.
For example, if your company has a high OPM, you may be able to reduce your operating expenses by outsourcing certain functions or by hiring less expensive employees.
It can be difficult to calculate Operating Profit Margin directly inside of Google BigQuery; that's where Causal comes in.
Causal is a modelling tool which lets you build models on top of your Google BigQuery data. You simply connect Causal to your Google BigQuery account, and then you can build formulae in Causal to calculate your Operating Profit Margin.
Causal lets you build models effortlessly and share them with interactive, visual dashboards that everyone will understand.
In Causal, you build your models out of variables, which you can then link together in simple plain-English formulae to calculate metrics like Operating Profit Margin. This makes your models easy to understand and quick to build, so you can spend minutes, not days, on your models.
When you're done, you can share the link to your model with stakeholders. They'll be able to view your model's outputs in a visual dashboard, rather than a jumble of tabs and complex formulae. The dashboards are interactive, letting viewers tweak your assumptions to see how they affect the model's outputs.
Causal lets you add visuals in a single click, letting you plot out graphs and distributions for metrics like Operating Profit Margin.