The growing relevance of data quality has revealed the need for adequate measurement. As time aspects are extremely important in data quality management, we propose a novel approach to assess data currency. Our metric, which is founded on probability theory, enables an objective and widely automated assessment for data liable to temporal decline. Its values are easy to interpret by business users. Moreover, the metric makes it possible to analyse the economic impacts of data quality measures like data cleansing and can therefore build a basis for an economic management of data quality. The approach can be applied in various fields of application where the currency of data is important. To illustrate the practical benefit and the applicability of the novel metric, we provide an extensive real world example. In cooperation with a major German mobile services provider, the approach was successfully applied in campaign management and led to an improved decision support.