Calling Excel easily inspectable is laughably wrong imho. Just the opposite.
Sounds more like an issue with the skill of average excel users than a feature gap.
To me, R seems more easily inspectable, as all the logic of a program is visible just by looking at text files, where in Excel it's hidden "under the surface", you have to click on cells, look at what's there, go click on other cells that relate to it, remember what you were looking at in the first one that's now invisible, etc.
For anything very complicated though, I'd prefer R, as Excel eventually gets unwieldy. Although, I'm saying that from the perspective of being a reasonably experienced coder. The majority of the population should just use Excel, especially in a work context in non-technical teams. No matter how much you push for R, other people in the team aren't going to see the value and aren't going to go along with it, and your R code will be useless after you've left.
R has a beautiful functional ability based on S-expressions, allowing some clever stuff to be done (i.e. tidyverse), incredibly fast (data.table is faster than Python, Julia, Matlab etc).
And as a side note, I believe it's moving down the rankings in the h2o benchmarks [1].
People shouldn't do important work in Excel. If it is important, people should be involved who have invested the time in learning something more powerful. Indeed, we could ask they aspire all the way to good practice and store their data in a database and their code in git. But there needs to be a process to verify model correctness no matter what tool is being used and bugs will exist in R as well as in Excel.