To effectively design a data-fusion system (DFS), users goals and situation and impact needs must be addressed for efficient action. Using the User-Fusion model, we explore the human’s capability to investigate the situation, determine the impact or threat, and refine DFS operations. By mapping user actions with DFS processes through “management by interaction”, the user-DFS design (1) actively engages the user in proactive control, (2) improves situation awareness, (3) reduces DFS dimensionality, (4) increases user confidence, and (5) decreases user-DFS reaction time. For example, by designing user refinement operations, we streamline DFS development for efficient target recognition and tracking scenarios by cueing an operator as well as allowing the user to prime the DFS. Notional results, using a novel 3D receiver operator curve (ROC) mapped over false alarm rate, detection rate, and time; captures the user-DFS interaction to increase target accuracy, reduce time of target identification, and increase system confidence.