Abstract
The emerging operational concept of multi-domain operations (MDO), which will require a high degree of integration and synchronization of capabilities and activities across all the operational domains (land, maritime, air, space, and cyberspace) and a high operational tempo, needs to be further developed, detailed, tested, and validated through experimentation and analysis. Experimentation and analysis provide the ability to iteratively explore, test, refine, and validate concepts. Furthermore, modelling and simulation (M&S) is essential for being able to experiment with, and analyze the effectiveness of, different concepts.
Effective MDO will rely upon the ability to effectively adapt new technologies and novel thinking into increased combat effectiveness to deal with a rapidly changing operating environment. However, it is often challenging to implement a coherent and holistic end-to-end approach for concept development from ideas to fully functional and fielded concepts. This is especially true when it comes to concept development involving stakeholders and forces from all, or several of, the five operational domains.
At the Norwegian Defence Research Establishment (FFI) we have had success with a methodology based on a structured, data-driven process of wargaming, simulation, and live exercises that follows ideas from conception to fielded concepts, thereby enabling rapid iteration of concept development and driving the lessons learned process (LLP) from observation to implementation and verification. We have used the methodology at the joint level and are now adapting it for concept development for MDO. Furthermore, we envisage moving towards a data-centric approach that facilitates structured data collection and analysis in each step of the process so the data can be more effectively managed, accessed, and utilized.
In this paper we describe our methodology for concept development through iterations of wargames, simulation, and live exercises, along with examples of successful use cases, and discuss challenges encountered and possible future improvements of the methodology.