1. A computer program product encoding a computer program stored on a non-transitory computer readable storage medium for executing a process on a digital computer processor, the process comprising a set of instructions for forecasting commodity consumption by a target individual of a large population of a size of at least on the order of magnitude of one million individuals, the large population including individuals exhibiting irregular historical consumption patterns of a commodity, the target individual not necessarily having a commodity consumption pattern representative of the large population, wherein the set of instructions comprises instructions for: a) selecting, from the large population of individuals having a size on the order of magnitude of one million, a representative sub-set of the population, the representative sub-set of the population, when combined with the target individual, not required to coincide with the large population; b) providing historical consumption data describing actual historical consumptions of the commodity by the representative sub-set of the large population during one or more less-recent historical time period(s) and during one or more more-recent historical time periods(s); c) for a plurality of commodity consumption forecast models, evaluating, for the specific case of the representative sub-set selected in step (b), performance of each forecast model of the plurality of forecast models by determining the ability of each forecast model of the plurality of commodity consumption forecast models to predict: i) consumption of the commodity by the representative population sub-set during the more-recent historical time period(s) from ii) data describing consumption of the commodity by the representative population sub-set during the less-recent historical time period(s) d) according to the results of the forecast performance evaluating of step (c), selecting a sub-plurality of commodity consumption forecast models from the plurality of consumption forecast models; e) for the target individual of the large population, providing historical consumption data describing actual historical consumptions of the commodity by the target individual during one or more less-recent historical time period(s) and during one or more more-recent historical time periods(s), the historical consumption data of the target individual not necessarily representative of the large population or of the representative sub-set of the large population; f) for the selected sub-plurality of commodity consumption forecast models, evaluating, for the specific case of the target individual, performance of each forecast model of the sub-plurality of forecast models by determining the ability of each forecast model of the sub-plurality to predict: i) consumption of the commodity by the target individual during the more-recent historical time period(s) from ii) data describing consumption of the commodity by the target individual during the less recent historical time period(s); g) formulating a combined forecasting model adapted for the target individual that includes at least some forecast models of the sub-plurality weighted for the target individual, in accordance with the results of the model performance-evaluating for the specific case of the target individual; and h) forecasting, future consumption of the commodity by the target individual using the combined forecast model.