Drawing conclusions from deterministic logistic simulation models

Computer simulation is one of several technologies available to improve competitiveness, and simulation is thus often used as a design and/or decision tool in various industries including supply chain systems. The presumed difficult and time-consuming statistical analysis of simulation data is often avoided while doing simulation studies by supplying deterministic input data to simulation models. This article addressed this issue in order to make managers aware of the risks involved with this practice. Embracing any technology that is new to the organisation requires responsibility. A theoretical comparison of deterministic simulation versus stochastic simulation is conducted and the theoretical results are substantiated with empirical results obtained from a simple logistic simulation model using deterministic input as one alternative and stochastic input as a second alternative.