External interruptions are a common phenomenon in today’s working environment. Specifically, attentional shifts in working environments lead to task resumption failures that refer to the improper resuming of a primary task after an interruption and negatively influencing the individual performance of employees. Business Intelligence & Analytics (BI&A) systems are well recognized as an essential concept to support decision making of employees. One important and frequently used BI&A system component are dashboards. BI&A dashboards enable collecting, summarizing, and presenting business information from different resources to decision makers. When working with BI&A dashboards, interruptions and resulting task resumption failures have negative consequences on decision-making processes. This research in progress paper addresses this problem and provides design knowledge for attention-aware BI&A dashboards that support users during task resumption. We follow a Design Science Research (DSR) approach and derive theory-grounded design principles for task resumption support on BI&A dashboards. Moreover, to evaluate the suggested principles, an instantiation is realized. In our instantiation, real-time tracking of eye-movement data is used to capture visual attention of the users and provide visual feedback after task resumption. We introduce testable hypotheses and present preliminary results of a pre-test lab experiment.