Forecasting After an Organizational Realignment

ForecaStinG aFter an orGanizational realiGnMent By Michael Gilliland Organizational realignments result from changes in product groupings, customer / sales geography, or distribution networks … realignments alter the hierarchical structure of the historical data used for statistical forecasting … hierarchical changes can be problematic for forecasting software packages … storing historical demand at the lowest level makes it possible to derive the organizational groupings appropriate for forecasting. T T he statistical approach to forecasting can be very efficient: Historical demand data are fed into the statistical forecasting software, demand patterns are modeled, and forecasts are generated. With good software, this entire process can be automated. If the demand happens to be reasonably “well behaved” (without too much erratic behavior and randomness), then you can even get good forecasts. A key assumption in statistical forecasting is that the demand being modeled is appropriate to the future you are trying to forecast. In other words, when you need to forecast demand for bananas, it is best to model the actual historical demand for bananas, rather than ...