There is no absolute data quality. A customer address that is good enough to send a marketing email is not good enough to ship a pallet, and the same record can be simultaneously acceptable and unusable depending on who picked it up. This is why "improve our data quality" is not actionable and "our address data must be good enough to deliver to, and today 12% of it is not" can.
In practice. Quality work runs in a loop: pick a use that matters, define the rule that use requires, measure the breach rate, fix the process that creates the breach, keep measuring. The fourth step is the one that changes anything — cleansing without fixing the source is a subscription, not a project.
Where it goes wrong. Quality is measured against every dimension for every field and reported as a single score. A composite percentage tells nobody what to do on Monday. Report by rule and by owner, name the process that produced the breach, and the conversation becomes fixable.