Identity and access management (IAM) has become one main challenge for companies over the last decade. Most of the medium-sized and large organizations operate standardized IAM infrastructures in order to comply with regulations and improve the level of IAM automation. A recent trend is the application of attribute-based access control (ABAC) for automatically assigning permissions to employees. The success of ABAC, however, heavily relies on the availability of high-quality attribute definitions and values. Up to now, no structured attribute quality management approach for IAM environments exists. Within this paper, we propose TAQM, a comprehensive approach building on a tool-supported structured process for measuring and improvement of IAM data quality. During the evaluation of three real-life use cases within large industrial companies we underline the applicability of TAQM for the identification and cleansing of attribute errors by IT and non-IT experts as well as the general introduction of quality management processes for IAM.