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It's hard to say. Most customers want to do the right thing (though some just don't feel that provable tradeoffs in design are their problem because they outsourced).

I did some deep diving in large customer performance near the end of my tenure at parse to help some case studies. Frankly it took the full power of Facebook's observability tools (Scuba) to catch some big issues. My top two lessons were

1. Fix a bug in our indexer for queries like {a:X, B:{$in: Y}}. The naive assumption says you can index a or b first in a compound index and there's no problem. The truth is that a before b had a 40x boost in read performance due to locality

2. The mongo query engine uses probers to pick the best index per query. If the same query is used in different populations then the selected index would bounce and each population would get preferred treatment for the next several thousand queries. If data analysis shows you have multiple populations you can add fake terms to your query to split the index strategy.