Shipbuilding Supply Chain Framework and Digital Transformation: A Project Portfolios Risk Evaluation

Abstract

Program portfolio managers in digital transformation programs have a need for knowledge that can guide decisions related to the alignment of program investments with the sustainability and strategic objectives of the organization. The purpose of this research is to illustrate the utility of a framework capable of clarifying the cost-benefit tradeoffs stemming from assessing digitalization program investment risks in the military shipbuilding sector. Our approach uses Artificial Neural Network to quantify benefits and risks per project while employing scenario analysis to quantify the effects of operational constraints. A Monte Carlo model is used to generate data samples that support the execution of the Neural Network. This enables the use of Portfolio Management Theory principles to organize and estimate measures of performance of the digitalization project portfolio. We demonstrate the utility of the framework by means of a theoretical case study presenting several digitalization project investment scenarios. We conclude that the framework makes a contribution and call for additional work to extend this framework to formalize the portfolio assessment activity while including acceptable risk ranges that constrain the final fractions of budget allocations.