Forget what we've already invested in this methodology; data relevance is the real issue, not just the tool.
Simply executing Kolmogorov-Smirnov tests does not guarantee the validity of conclusions if the underlying assumptions are fragile or the thresholds poorly chosen.
An apparent statistical similarity can mask significant financial risks, especially if the venture portfolio multiples used are biased.
For example, a French bank ignoring the specifics of its credit portfolio by relying on generic benchmarks could face failures.
We need to evaluate whether we would re-analyze with fresh eyes facing such limitations.