Recently, representativeness indicators, or R-indicators, have been proposed as indirect measures of nonresponse error in surveys. The indicators employ available auxiliary variables in order to detect nonrepresentative response. They may be used as quality objective functions in the design of survey data collection. Such designs are called adaptive survey designs as different subgroups receive different treatments. The obvious question is whether the decrease in nonresponse bias caused by adaptive survey designs could also be achieved by nonresponse adjustment methods that employ the same auxiliary variables.In this paper, we discuss this important question. We provide theoretical and empirical considerations on the role of both the survey design and nonresponse adjustment methods to make response representative. The empirical considerations are supported by a wide range of household and business surveys from Statistics Netherlands.