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Bottom-up approach to forecasting yields better forecasts than the topdown when forecasts are statistically generated ... top-down approach works well when SKUs within a family are of equal size ... carefully specified statistical models give better forecasts than those judgmentally developed.
Frms often market families of items that are closely related in function, styling, and design. For example, a manufacturer of irrigation equipment may offer several families of irrigation equipment including impact sprinklers, rotator sprinklers, and gun sprinklers. The impact sprinkler family might then consist of two individual stock keeping units (SKUs) such as low angle and high angle impact sprinklers. Two general approaches have been suggested for developing forecasts for individual items in a family. One approach might be referred to as "topdown" (TD). In this approach, the family data are used to develop a family forecast which is then disaggregated into individual items based on their historical fraction of sales. The alternative employs a "bottomup" (BU) approach where a separate forecasting model is developed for each item in the family.
The forecasting methods used by planners can be either objective or subjective in nature. Objective methods are statistical or other well-specified processes through which data of any type (subjective or objective) can be translated into forecasts. With these formal methods, the forecast could be replicated by anyone using the same data and methodology.
Subjective methods are based on informal, experiential and intuitive processes and are often referred to as judgmental forecasting. Like formal methods, judgmental forecasting can also be based on either objective or subjective data. In some situations, formal analysis may also be involved. The important distinction is that the forecast is derived intuitively and is unlikely to be identical to another person's forecast developed from the same information. In most cases, the decision maker would be better off using an objective forecasting technique. However, despite the existence of formal forecasting methodologies and the ready availability of computer resources, most forecasts are still made the old fashion way-- intuitively. This study examines how accurately professional planners can forecast items in a family when they are presented with either aggregate (family) time series or item time series and asked to make judgmental forecasts. In addition, the planners ' forecasts are compared...