A Simulation-based Tool for Increasing the Impact of DoD R&D Contracts

The objective of this research is to create an explainable and structured approach to determining profit or fee negotiations, which accommodates factors that the present weighted guidelines do not. The innovation that this proposal offers is to build an interactive, computational model that simulates these factors—existing and newly identified—and enables negotiators to explore in real-time the effects the factors have on contract performance.  Software Factory Labs (SFL) and Purdue University will collaborate on this research. The Principal Investigator (PI) at SFL brings experience in a variety of computational modeling regimes for process simulations, years of research and review of the DoD and its contractors in technical and contractual performance, and personal knowledge of operation as a small defense subcontractor. The Co-PI at Purdue is a world expert in collaborative innovation research who brings knowledge of the effects of both economic and non-economic business incentive factors, and is well experienced in computational modeling to identify emergent behaviors in complex adaptive systems.  The proposed work entails using a structured literature review and other methods to identify the factors affecting the incentives that drive firms to participate in and perform efficiently on DoD research and development (R&D) contracts. The research will specifically identify overlooked or underutilized factors that could encourage broader participation in DoD R&D initiatives. As factors are identified, the team will incorporate them into computational models that have strengths in identifying unrecognized emergent behaviors, and in simulating the effects of complex process interrelationships. We plan to have working prototype computational models before the end of the performance period, exceeding the solicitation goal to have only a notional system design.  We anticipate that the resulting computational models will be field-testable at the end of Phase I. This field testing may comprise applications deployed on government-owned personal computing equipment, and we also have a plan for and experience in creating a cloud-based Software as a Service (SaaS) solution in Phase II. Either approach will allow use of the real-time models in actual or simulated negotiations, and will provide the means to evolve the models based on findings and user feedback. The cloud-based solutions have the additional advantage of centralizing and simplifying deployment, operation, cybersecurity, and upgrades of the computational models, and allowing them to be accessed through already-approved web browser interfaces from government-owned equipment.