Workshop Report on Methods for R&D Portfolio Analysis and Evaluation

Brian Bush, Rebecca Hanes, Chad Hunter, Caroline Hughes, Margaret Mann, Emily Newes, Sam Baldwin, Erin Baker, Leon Clarke, Steve Gabriel, Max Henrion, Magdalena Klemun, Giacomo Marangoni, Gregory Nemet, Alexandra Newman, Mark Paich, Steven Popper, Rupert Way

Research output: NRELTechnical Report


The Workshop on Methods for R&D Portfolio Analysis and Evaluation convened on 17–18 July 2019 at the National Renewable Energy Laboratory in Golden, Colorado, and examined strengths and weaknesses of the various methodologies applicable to R&D portfolio modeling, analysis, and decision support, given pragmatic constraints such as data availability, uncertainties in estimating the impact of R&D spending, and practical operational overheads. Participants employed their deep expertise in approaches such as stochastic optimization, real options, Monte-Carlo analysis, Bayesian networks, decision theory, complex systems analysis, deep uncertainty, and technology-evolution modeling to critique the initial example models developed by the project’s core team and to conduct thought experiments grounded in real-life technology models, progress data, expert elicitation, and portfolio information. This engagement of participants’ methodological expertise with the practical requirements of real-life portfolio decision support yielded ideas for improved approaches, alternative methodological hypotheses, and hybridization of methodologies that are well-grounded theoretically, computationally sound, and realistically executable given data availability and other practical constraints.
Original languageAmerican English
Number of pages129
StatePublished - 2020

NREL Publication Number

  • NREL/TP-6A20-75314


  • expert elicitation
  • portfolio analysis
  • stochastic optimization
  • technology modeling


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