The ability to monitor data quality on an ongoing basis is critical to ensure it is fit for purpose and provide an early warning of defects that may impact on the organisation’s corporate performance. Relying on a manual process in order to connect the data quality owners with the key results of a project or ongoing analysis is dangerous; it often leads to projects where progress is invisible and the quality of data and its impact is unknown.