Mostly it's about best practices I think, and getting a feel for them. Try starting with something simple, like making a peanut butter and jelly sandwich. Describe how it's done, each step. Think about where it's efficient, where there's extra wasted action, or time. By the time you're done you'll be considering if your butter knives are stored in the best spot, if you should get everything out at once, or one at a time. Do you have enough inventory? Is having extra inventory a waste? Is it worth washing knives afterwards or get extra so you can wash a batch at a time instead?

Then, go back through from the perspective of a child that has never seen your kitchen. Do the steps still make sense? How can you make it more simple, less effort? Finally, when I mentioned hand off... How do you ensure that your child laborer is going to deliver a pb&j of sufficient quality? Who determines quality? Production time?

Once you start thinking that way, everything is a process that could be considered, with inputs and outputs, quality control issues, potential waste, efficiency improvements, etc. It applies to data just as much as a sandwich for example, and office jobs are all about taking information, changing it a little and sending it on. Each step should transform in some way (capturing who does what, to what, at each step can help). Understanding the complexity instead of assuming simplicity so you can analyze it, but then distill it back down to something that is actually simple and understandable.

Anyway, hopefully that helps some in thinking about it a little differently.

For googling key words: quality management, process mapping, process analysis, lean, ?

Unfortunately there's a lot of corporate shit, buzzwords, and SEO that have accumulated so it can by hard to find good info (like everything else now?)

Even better, just some handy keywords to plug into google and we can open up that box of knowledge ourselves!