Ph.D. Defense
Alicia Hong
(Advisor: Dr. Dimitri Mavris)
"A Methodology for R&D Decision Making Under Uncertainty – Applied Towards the Elimination of Stalling Projects"
Thursday, June 13
3:00 p.m.
Virtual
Meeting ID: 243 080 780 357
Passcode: oiHS6q
Abstract
Portfolio management is a well-established strategic practice applied in many R&D organizations. The objective to optimize returns or explore new strategies through balanced investments typically involves a project selection method. Defining value and uncertainty of projects enable portfolio selection through tools that depict risk balance and portfolio optimization. However, these insights do not provide clear indication of when projects have been continued beyond a reasonable effort, consuming valuable resources that could be utilized on other opportunities. Challenges with understanding uncertainty reduction, often associated with R&D projects, make it difficult for portfolio managers to know when a project is stalling. This dissertation provides a method that supplements existing portfolio decision tools to address the issue of terminating stalled projects within an R&D portfolio for better resource utilization.
Given the complex nature of existing portfolio management processes, the objective was to utilize existing metrics to formulate a different perspective of project productivity. Many portfolio management processes already utilize risk mitigation to measure project maturation. Evaluating risk mitigation relative to investment sunk provides further insights into the productivity in utilizing R&D budgets. The health of projects can then be measured by comparing their risk and sunk cost status to a historical benchmark called the productivity threshold. Participants from various industries and R&D organizations were invited to participated in an R&D computer simulation to demonstrate the effectiveness of the productivity threshold tool with different types of portfolios. Main effects and interactions were analyzed to identify the types of projects for which the threshold tool demonstrated the greatest impact in motivating portfolio managers to pivot from stalling projects. By introducing the productivity threshold tool, this dissertation offers a valuable contribution to the field of portfolio management, enabling better decision-making and optimization of investments in R&D organizations.
Committee
- Dr. Dimitri Mavris – School of Aerospace Engineering (advisor)
- Dr. Daniel Schrage– School of Aerospace Engineering
- Dr. Elena Garcia – School of Aerospace Engineering
- Dr. Shreyes Melkote – School of Mechanical Engineering
- Larry Schneider – Retired VP Chief Program Engineer, Boeing
- Joe Shaw – Retired Senior Executive, NASA