It sounds like number of downloads and times a library is called could be easily padded to simulate more usage. Without knowing the true intent of the exec team, I would think that if you have Shiny apps in production, knowing how many times those are used and by how many unique users would be a better metric to track when it comes of the impact R in production. If the intent is to figure how much development is happening in R, in contrast with other products, then I would say that an analysis of the content in your code repositories may be a better KPI. If the analysis is for R packages (which is kind of weird to me that an exec is worried about that) then a text analysis of the code in your repos will tell you know many times a particular library is called, not perfect, but it may get you closer to the truth.