We see this in data science and machine learning where people complain about spending their time cleaning data, etc... when their time should be spent "generating insights/etc." We also see that those insights are interesting but not very useful if they aren't actionable, too costly or too impractical to implement.
Ultimate value is related to being able to contribute to and achieve the holistic outcome, but the lens of success is often focused on models or insights instead. This is a cultural and organizational problem, rather than a technological one. It also takes a dose of humility to appreciate the true value of the so-called dirty work.