In this Hot New Research Column in Foresight, Paul reports on three new approaches to the difficult challenge of supermarket forecasting. James Taylor has investigated a robust approach to this challenge; he calls it exponentially weighted quantile regression (EWQR). Aburto and Weber propose another method more complex than the exponential smoothing suggested by Taylor. They developed a hybrid model that combines an autoregressive integrated moving average (ARIMA) with a neural network (NN). Matteo Kalchschmidt and two co-researchers came up with yet a third perspective on the problem, a store-clustering approach. Paul explains the workings of each method. Copyright International Institute of Forecasters, 2007
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