The aim of statistical disclosure control (SDC) is to provide protection to the individual respondents by minimizing the risk of disclosing confidential information but to do so in a manner that preserves as much as possible of the features of the original unprotected data and not distorting the usefulness of the data. However, SDC-methods typically alter the original data in some way and introduce some kind of “error”. Measuring both risk and data utility can be done in various ways and will depend on how one defines risk and utility. Recent research (Schouten, Cobben and Bethlehem, 2009; Särndal, 2010; Lundquist and Särndal, 2014) has introduced so called R-indicators and Lack-of-Balance-indicators as means to measure the usefulness of a sample when dealing with non-response. Part of the focus has been on how to asses if the responses are in some sense representative and, if not, at what stages during data collection measures should be taken. The idea that will be discussed at the seminar is if these indicators could be used in an SDC-context, i.e. how protection of a data set affects the usefulness of the data with respect to these new indicators. We will illustrate the basic idea using real data from Statistics Sweden and the behavior of a (very) crude protection method in a data collecting process. The study was done in collaboration with I. Jansson and P. Lundquist at Statistics Sweden and was originally presented at NTTS 2013.