Fixed asset turnover is a financial metric that measures the efficiency of a company's fixed assets. Fixed assets are assets that are not easily converted into cash and are used in the production of a company's goods or services.
Fixed assets include things like factories, machinery, equipment, and vehicles.
Fixed asset turnover is calculated by dividing the company's net sales by the total value of its fixed assets.
Fixed asset turnover is a good metric to use when comparing companies in the same industry.
It can be difficult to calculate Fixed Asset Turnover 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 Fixed Asset Turnover.
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 Fixed Asset Turnover. 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 Fixed Asset Turnover.