>IOW, the experimenter wanted to be able to arrive at the conclusion that difference in performance was unrelated to workers and designed the experiment so it would give this result.
That's the whole point. The experiment is not that we're supposed to be surprised that the workers did not affect performance - in fact, that's the subtext of the whole thing! We know it from the start cause he explains exactly how the process works and we can all see that individuals cannot affect their output.
The point is, if we are unaware that we're in such a situation, we can still find metrics to allow us to rank workers, fire low performers, give out raises, etc. When we myopically focus on such metrics, and disregard the system that makes them worthless, we're making all our decisions on random chance, even though we have a clear process, data collection, the whole thing.
That's also my whole point: this is not an experiment but an elaborate artificial argument designed to prove a point of view decided in advance. That is why I find it unsavory.
The point of the experiment is to be extreme, but after reading (a very large portion of) Deming's work, I don't think he'd disagree with your initial assertion that there are differences between workers.
The broader points he makes, related to this experiment at least: There are individual and systemic issues that influence the outcome of a process. The actual ratio will vary depending on what kinds of processes are involved.
If the job is to be a literal screw turner on an assembly line, then there is relatively little difference between the majority of people (assuming they are generally able bodied, sighted, and have decent coordination), the system (tempo, length of shift, accessibility of the thing being screwed together, tools being used) will have a much larger impact than the individual's skill. The system of the assembly line will influence the outcome more than the individual's skill (at least above a basic threshold, a supremely uncoordinated individual could flounder even with the slowest pace of work). Switch to more skilled work and you will find, increasingly, more differences in outcome based on individual performance versus the system of the work, but even there the system matters.
Look at software development offices that still favor things like manual build processes, code versioning control, testing, and deployment over automation. They provide many opportunities for human error (even just simple miskeying of data) that can reduce everyone's effectiveness no matter how skilled. (Fortunately these kinds of places are increasingly rare, at least outside of US defense contractors.)
The experiment, then, is an artificial construct (like most classroom experiments) meant to illustrate a point by showing one extreme. This acts as a counterpoint to the more conventional wisdom that the individual, and not the system, is what actually matters for the outcome. The conventional wisdom, of course, being wrong in many circumstances since it tends to place too strong a weight on the individual performance and too weak a weight on the system.
It would be unsavory if he had said, "See, stop evaluating individuals their contribution doesn't matter." But he never did say that (in anything I read, at least), and anyone who looks at this experiment and draws that conclusion would be an idiot.
That's the whole point. The experiment is not that we're supposed to be surprised that the workers did not affect performance - in fact, that's the subtext of the whole thing! We know it from the start cause he explains exactly how the process works and we can all see that individuals cannot affect their output.
The point is, if we are unaware that we're in such a situation, we can still find metrics to allow us to rank workers, fire low performers, give out raises, etc. When we myopically focus on such metrics, and disregard the system that makes them worthless, we're making all our decisions on random chance, even though we have a clear process, data collection, the whole thing.