I didn't want to put another UX designer on blast, so writing here.

I read an article about using Lean principles for UX research.

As someone who has studied this deeply over the years, I wanted to correct a few errors in thinking.

First, you can only measure overproduction if you know how to calculate the value of a method. When does qualitative interview n + 1 become less valuable than interview n? If you can't answer this question with precision and confidence, you're not really Lean. In addition, it's incumbent on the UX research team to identify their JIT process for doing additional research, so when interview n + 1 is needed, it can be spun up immediately.

Overprocessing is a valid issue, but with the advent of AI, it is now possible to delegate less valuable processing tasks to those assistants.

Second, since UX research artifacts tend to be digital rather than physical, waste as it relates to waiting, transportation, motion and inventory are largely irrelevant. (The exception is if you maintain a UX research repository, and it is difficult/time-consuming to find old inventory.)

Finally, defects are probably the biggest operational waste. But since the Lean philosophy is to build in method quality up front, this is something you can control.

tl;dr: Lean works great for UX research, but if you lack statistical training in measuring overproduction, you're not really Lean.