When (not how or why) to calculate Big O of an algorithm

"When should you calculate Big O?"

When you care about the Time Complexity of the algorithm.

When do I care?

When you need to make your algorithm to be able to scale, meaning that it's expected to have big datasets as input to your algorithm (e.g. number of points and number of dimensions in a nearest neighbor algorithm).

Most notably, when you want to compare algorithms!

You are asked to do a task, for which several algorithms can be applied to. Which one do you choose? You compare the Space, Time and development/maintenance complexities of them, and choose the one that best fits your needs.