The International Probabilistic Planning Competition is a leading showcase for fast stochastic planners. The current domains used in the competition have raised challenges that the leading deterministic-planner-based MDP solvers have been able to meet. We argue that in order to continue to raise challenges and match real world applications, domains must be generated that exhibit true stochasticity, multi-valued domain variables, and concurrent actions. In this paper we propose the academic advising domain as a planning competition domain that exhibits these characteristics. We believe that this domain can build upon the success of previous contests in pushing the limits of MDP planning research.