Project portfolio selection and scheduling optimization based on risk measure: a conditional value at risk approach

Abstract

Project portfolios are considered “powerful strategic weapons” for implementing corporate strategy. Projects are exposed to different types of risks. Studies on project portfolio optimization have addressed risks either by maximizing the expected net present value or including constraints that place an upper bound on portfolio risk score. However, no study has attempted to minimize the risk of severe low returns by adopting a risk-averse measure. The present study contributes by addressing this research gap and utilizes a risk measure conditional value at risk (CVaR) for decision making. The present paper considers a case study of a dairy firm. It captures financial risk in the form of uncertain project cash inflows and evaluates strategic alignment scores and risk scores for technical, schedule, economic and political, organizational, and statutory clearance risks of projects using an analytical hierarchy process. Further, it formulates three project portfolio selection and scheduling models namely, risk-neutral (max_E), risk-averse (max_CVaR) and combined compromise (max_E_CVaR) models. A comparison of results shows that the max_CVaR model ensures that the lowest return in the worst scenario is maximized to the greatest extent possible, thereby yielding high returns even when the confidence levels are low. The model exploits the diversification approach for risk management and its portfolios contain at least one project from each project category (derivative, platform and breakthrough). The results obtained using max_E_CVaR model can be utilized by decision makers to select and schedule project portfolios according to their risk appetite and acceptable trade-off between risk-averse and risk-neutral objectives.