Purpose: The aim of this paper is to suggest a new approach to the problem of sales forecasting for improving forecast accuracy. The proposed method is capable of combining, by means of appropriate weights, both the responses supplied by the best-performing conventional algorithms, which base their output on historical data, and the insights of company’s forecasters which should take account future events that are impossible to predict with traditional mathematical methods. Design/methodology/approach: The authors propose a six-step methodology using multiple forecasting sources. Each of these forecasts, to consider the uncertainty of the variables involved, is expressed in the form of suitable probability density function. A proper use of the Monte Carlo Simulation allows obtaining the best fit among these different sources and to obtain a value of forecast accompanied by a probability of error known a priori. Findings: The proposed approach allows the company’s demand forecasters to provide timely response to market dynamics and make a choice of weights, gradually ever more accurate, triggering a continuous process of forecast improvement. The application on a real business case proves the validity and the practical utilization of the methodology. Originality/value: Forecast definition is normally entrusted to the company’s demand forecasters who often may radically modify the information suggested by the conventional prediction algorithms or, contrarily, can be too influenced by their output. This issue is the origin of the methodological approach proposed that aims to improve the forecast accuracy merging, with appropriate weights and taking into account the stochasticity involved, the outputs of sales forecast algorithms with the contributions of the company’s forecasters.

The study presented in the paper is the result of a mandate to the Authors from the management of a freight-terminl located in a region in the North-East of Italy. The objective of the study, therefore, is to identify the most efficient configuration in term of costs and performance of internal container handling systems in among a set of possible solutions set by the designers. Given that in the freight-terminal there’s a high level of stochasticity elements (hours of arrival and restarts of container vehicles, breakdowns of handling equipment, availability of operators, etc.) an effective and efficient modelling could not have disregarded this fundamental characteristic of the real system. For this reason the Authors decided to study the problem by the use of Discrete Event Simulation. The tools selected by the Authors for the construction of the model was Flexsim CT, whose graphics allow managers to exploit the prerogatives of management methodologies known as “visual management” in addition, of course, to the usual quantitative analysis that characterize the output of a correctly constructed DES model. Thanks to the study carried out, the managers were able to establish, among the solutions proposed, the scenario that involved 1 crane and 3 top loader was the one that allowed both the minimization of purchase and management costs of the yard than the reduction of expectations for handling equipment.