One of the points in particular seems highly dependant on the product category you are analyzing: ability to put data science models into production. You might

One of the points in particular seems highly dependant on the product category you are analyzing: ability to put data science models into production. You might be working on some product that can't dynamically respond to stimuli as that seems to imply. My team's work influences product decisions frequently, but it would be contrived to actually deploy our models to the product in many cases. Another that may not apply is the stuff about reproducing past experiments. Suppose your experment platform is programmatic and interfaces with some codebase. Old feature flags are a form of tech debt that should be removed. So old experiment code is sitting in a repo history somewhere but not necessarily deployable.