Evaluating real options for mitigating technical risk in public sector R&D acquisitions

Government acquisitions requiring R&D efforts are fraught with uncertainty. The risks are often mitigated by employing a multi-stage competition, with multiple vendors funded initially, until a single successful vendor is selected. While decision-makers recognize they are using a real options approach, analytical tools are often unavailable to evaluate optimal decisions. We present an efficient stochastic dynamic programming approach that public sector acquisition managers can use to determine optimal vendor selection strategies in those competitions where Technology Readiness Levels (TRLs) are the measure of progress. We then use examples to demonstrate the proposed approach and provide illustrative numerical results.