This sounds like the "waterfall" model of project management. I could see it working in some areas and not others. In fact, a friend of mind wrote a thesis on a re-analysis of an existing data set from one of the big physics experiments, looking for a new effect that he had proposed based on theoretical work.

But I come from a background in small-lab experimental physics, and my spouse from synthetic chemistry. In both cases, a model of planning, followed by execution, followed by analysis, doesn't work, for a number of reasons. Often, an experiment fails, over and over again, until the design and operating conditions are refined to the point where the data begin to make sense. In my experiment, the equipment didn't even exist until I built it. And in experiments such as mine and my spouse's, the researcher (grad students) are also developing and refining their own abilities as they progress. I was my own electrical, mechanical, and software engineer. Sometimes, preliminary results change the direction of the project.

An additional issue is that experiments are rarely documented well enough to hand the data off to another team to analyze, without significant back-and-forth.

What little I understand about the "agile" model, seems more applicable to this kind of science.