Cost at Risk (CaR): a Methodology for Costing under Uncertainty

Abstract

Paper aims: This paper proposes Cost at Risk (CaR), a concept and a methodology that allows the computation of the risk of cost estimations within a costing system by means of the Monte Carlo Simulation, considering a predefined level of confidence and considering the worst expected result in terms of cost in a certain period. Originality: Traditionally, researchers and practitioners have been focused on deterministic costing models without recognizing and managing cost uncertainty. The proposed methodology is based on five steps that go from the determination of the parameters that generate uncertainty to the estimation of the risk. Research method: A Design Science Research (DSR) approach was followed based on mathematical modeling and computer simulation. Main findings: The model was applied to the imaging area of a hospital allowing to identify and quantify the risk of the most relevant costs and therefore, supporting the design and implementation of both operational and strategic decisions. Implications for theory and practice: The main contribution is the inclusion in costing systems of the uncertainty inherent in the estimation of costs, particularly in complex environments.