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You usually normalize a database to avoid data redundancy. It's easy to see in a table full of names that there is plenty of redundancy. If your goal is to create a catalog of the names of every person on the planet (good luck), I can see how normalizing names could be beneficial. But in the context of the average business database is it overkill?
(Of course I know you could take anything to an extreme... say if you normalized down to syllables... or even adjacent character pairs. I can't see a benefit in going that far)
Update:
One possible justification for this is a random name generator. That's all I could come up with off the top of my head.
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Name Normalization analyzes email document headers to identify all aliases (proper names, email addresses, etc.) and the entities (person, distribution group, etc.) those aliases belong to. Name normalization automatically merges entities with those created by Legal Hold, Processing, or Case Dynamics.
Normalizing - Normalizing is a tactic used to desensitize an individual to abusive, coercive or inappropriate behaviors. In essence, normalizing is the manipulation of another human being to get them to agree to, or accept something that is in conflict with the law, social norms or their own basic code of behavior.
Normalizing audio is an effective strategy for making samples, and vocal takes more consistent in volume before/during mixing and even as a method for mastering to bring a group of final music, podcast, or television mixes up to a consistent level.
Normalization is useful when your data has varying scales and the algorithm you are using does not make assumptions about the distribution of your data, such as k-nearest neighbors and artificial neural networks. Standardization assumes that your data has a Gaussian (bell curve) distribution.
Yes, it's an overkill.
People don't change their names from Bill to Joe all at once.
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