I may have misunderstood something, but I don't think your system excludes pivotal voters. For example, with the aforementioned ten people, it is possible that everyone gave every alternative except B score 0, and alternative B got score 1 from every member of the group. If one of the members then changes her score for A to 10 and for B to 0, we have A(10) > B(9).

This does appear fixable with a scale tailored to the number of people and alternatives.

Propositional knowledge does not make anything happen by itself, but it can help when actually doing something. For example, the venture won't happen by itself, but once it is started, it might be that certain things happen, and you go "hmm, this looks like something I read about". This allows you to make predictions and act upon them, potentially avoiding a pitfall others have already trod in.

To take programming, once you start programming something, you might go "wait, this looks exactly like that theory, and there was a solution", or "wait, here I also need to guard against this problem" --- both things you have not experienced yet. Learning by doing can be quite expensive.

You are arguing a strawman. Many-worlds is contended only conceptually correct, in the same way classical illusions of our billiard ball world are conceptually correct. Obviously, quantum mechanics is technically imprecise, and there is likely another conceptual picture that gives the more accurate layer of description of reality, in the same way as classical physics is technically imprecise, and quantum mechanics serves as a shift in perspective allowing to fix some of its imprecision (theories of relativity working on the same problem on the other end, and quantum relativity on both).

Reductionist analysis is not about getting to the bottom of things (it's pretty bad at that), but about moving between levels, finding simple patterns at the lower levels and using knowledge about them to reach conclusions at the higher levels.

Computer programming. Aside from the market value, it helps me analyze and plan day-to-day tasks. If there are several things I need to do, and they are tangled (one necessitates another, say), I start thinking like I would when programming, breaking the whole mess down into manageable pieces and then stringing them back together into a plan of action.

I expect that other people may have this as a separate skill not related to programming at all.