While traditional robotic systems come with a monolithic system design, reconfigurable multirobot systems can share and shift physical resources in an on-demand fashion. Multirobot operations can benefit from this flexibility by actively managing system redundancies depending on current tasks and having more options to respond to failure events. To support this active exploitation of redundancies in robotic systems, this article details an organization model as basis for planning with reconfigurablemultirobot systems. The model allows us to exploit redundancies when optimizing a multirobot system’s probability of survival with respect to a desired mission. The resulting planning approach trades safety against efficiency in robotic operations and thereby offers a new perspective and tool to design and improve multirobot missions. We use a simulated multirobot planetary exploration mission to evaluate this approach and highlight an exemplary performance landscape. Our implementation of the organization model is open-source available (https://github.com/rock-knowledge-reasoning/knowledge-reasoning-moreorg)