Vector smoothing improves accuracy of item level forecasts

Article Abstract:

Vector smoothing enhances forecast accuracy when disaggregating the aggregate forecasts. Disaggregation is achieved by initially estimating the probability mix of each item within each group. The probability is then used to arrive at the forecast of each item. Simple exponential smoothing method is used to estimate the probability of each item. This method is updated when more data become available. Vector smoothing is actually the process of updating probabilities using exponential smoothing.

Smoothing (Statistics)

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Many plans, one reality; which is the real forecast?

Article Abstract:

There are five essential requisites in the development of successful business forecasting processes. First, the forecast group must maintain their objectivity. Second, a team must be formed to study changing business dynamics. Third, an efficient forecast planning communication process must be formed. Fourth, business plans must be compared against orders. Finally, data needed for decision-support systems should be integrated into one database.

Management science

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How to prepare forecasts using EDA tools: a hospital-based case study

Article Abstract:

Forecasts accuracy can be improved by utilizing the exploratory data analytic (EDA) method. A case study involving a hospital in Southern California shows that aside from the ease of computation, EDA method allows the integration of highly significant predictor data, such as market share. Such ability enables the user to gain a better understanding of the relationship between the forecasted variable and another significant predictor.

Hospitals, Forecasting, Hospital administration

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