Purpose - To provide an overview of how a number of frequently used smoothing-based forecasting techniques can be modelled for use in dynamic analysis of production-inventory systems. Design/methodology/approach - The smoothing techniques are modelled using transfer functions and state space representation. Basic control theory is used for analysing the dynamic properties. Findings - A set of expressions are derived for the smoothing techniques and dynamic properties are identified. Practical implications - Dynamic properties are important in many applications. It is shown that the different smoothing techniques can have very different influences on the dynamic behaviour and therefore should be considered as a factor when smoothing parameters are decided on. Originality/value - Dynamic behaviour of production-inventory systems can be analysed using control theory based on, e.g. transfer functions or state space models. In this paper a set of models for five common smoothing techniques are analysed and their respective dynamic properties are highlighted. © Emerald Group Publishing Limited.