Simulating Product Costs Under Stochastic Conditions Using the ABC Matrix Model

Costing models tend to follow a top-down or, alternatively, a bottom-up approach, following, respectively, a financial/accounting or an engineering/production perspective. Regardless of the approach used, cost models tend to be based on past information and be deterministic, contributing little to decision making at the organization’s operational and strategic levels. Moreover, the current business environment is characterised by conditions of high variability, uncertainty, complexity, and ambiguity. As such, predictive models for decision making which consider the stochastic nature of certain variables are beneficial. In this paper, we present a matrix activity-based costing model which allows a combined bottom-up and top-down approach to predict the resource requirements of a production system and to compute the cost of products and other relevant cost objects, considering the processes as deterministic or stochastic. The developed costing model includes the main elements which characterise a production system. Therefore, it can be easily generalized to different processes and industries. This proposed costing model was replicated using the SIMIO simulation software, including parameters to both make the test process efficient and allow to take full advantage of experimentation. Moreover, tallies were modelled to exhibit custom results, suited to this matrix costing model. We have concluded that discrete event simulation is a well suited tool to cost modelling, especially given its stochastic capabilities and the ease of scenario creation. In future work, different system aspects can be assessed, different resource combination, and the cost per resource call; can be estimated and the simulation model can be improved to facilitate scenario creation.