Many business decisions use forecasts of future behavior (e.g., the sales rate for a product) based on past observations. In order to simulate such systems using GoldSim, it is necessary to simulate the forecasting process itself. For example, when modeling a supply chain, it is necessary to simulate how orders are placed. In the real world, these orders are placed not based on the current demand (which may not even be measurable), but on a forecast of future demand.
An Information Delay can be used to represent a very commonly used forecasting method known as exponential smoothing. In exponential smoothing, the forecast is based on an exponentially-weighted average of past observations. Mathematically, this is equivalent to the output of an Information Delay with n =1. An example of such a simulated forecast is presented below: