Development of advanced technology (e.g. High Level Information Fusion (HLIF), Data Mining, Artificial Intelligence (AI), human factors, etc.) enabled decision support for prediction and recognition of piracy activity is an extremely challenging problem. It requires the consideration of multiple interrelated factors and constraints for numerous aspects of the system, including legal, jurisdictional, information sharing and exchange, information availability and quality, user roles and hierarchy, application of hardware and software technologies, etc. which do not lend themselves to simple analyses. There are numerous stakeholders, and no one has either an understanding of or access to, the entire knowledge to be able to resolve any of these challenges by themselves. There are too many unknowns in a traditional top-down design methodology to be feasible to use. Because scenarios are task-based and descriptive, it was judged that the Scenario Based Design (SBD) approach needs to be explored for advanced technology-enabled systems, in which human is a part of the system. This chapter presents an initial discussion on how SBD methodology could be applied to incrementally develop advanced decision support capabilities for prediction and recognition of piracy activity in collaboration with the stakeholders.