Get rid of the eye test and names. Develope a mathematical system to find the best team’s objectively.
Several years ago I got really interested in hockey analytics when the LA Kings won the Stanley Cup as the 8th seed in the Western Conference. There was a guy with a hockey analytics website who was predicting before the playoffs started that the Kings were going to win - his analytics showed they had a crazy number of "bad losses" that year and they were possibly the best team in the league.
What was interesting was an interview with him the following year before the season started, when he was asked how he "knew" the Kings were going to win. He said he didn't "know", but thought they had a really good chance when he compared his system to what he observed on the ice. He would never just rely on analytics alone, it required a sanity check as well. The analytics results basically fell into four categories:
1) Results that were obvious without any analytics, like teams who spend more time in the offensive zone score more).
2) Results that were so marginally relevant as to be inside the margin of error.
3) Results that appeared significant but weren't - an example of where that might have happened in college basketball is when Syracuse was good but JB played stall ball at the end which allowed teams to close the margin of the loss. That may have led to Syracuse being undervalued in computer metrics which would have only been observable by comparing analytics results to actual game play and seeing there was a possible issue.
4) Results which were not immediately obvious but were relevant. There are very, very, very few of these. (He thought the Kings being massively better than the game results would indicate was possibly one of them, decided to go big and predict them to win it all and got lucky when they did. That led to him getting hired to lead the analytics department for an NHL team...sometimes success is just shooting your shot. Its better to be lucky than good, but success is usually a combination of both).
If you don't do a sanity check, you are going to make errors of classifying conclusions which belong in the third category with ones that belong in the fourth. It'll be objectively accurate via the analytics that one team is "better" than another - it'll just be wrong. What he also tried not to do is what I'll call the "Millhouse approach" (shots fired) of coming to the conclusion first and then mining for data to support that conclusion, since that just leads to conclusions from categories 1 & 3 getting allocated to category 4.
In reality all the pro sports leagues have "objective" systems for selecting and seeding playoff teams, and we can find in most years a team that other objective systems and/or our personal eye tests would indicate a better team was left out. The big difference is that the pro league model is clearly laid out with no room for politics, while college is going with a selection committee which guarantees it will be a political process many feel is unfair.
TL; DR summary - I agree that doing away with the selection committee and going to some apolitical selection process is needed. I don't have any delusions that will lead to us selecting the 12 best teams...I don't even think it'll be free from charges of politics. It'll just be a system that can be defended from those charges with some credibility, where the current approach can't be (and the efforts to do so are laughably bad and destroy the credibility of the person making that argument).