Data utility is a measure of how useful a data set is (e.g. for business insight, analytics, machine learning, etc). The removal of personal data and/or noise addition can make data suffer a loss of utility.
There are a number of use cases in which sensitive data isn’t actually needed to achieve valuable results – and de-identified data is just as useful (we talk about it in this blog post). Businesses sometimes need to assess the privacy/utility trade-off when making decisions on privacy policies.