It could be said that the main concern of forecasting is the elimination of the phenomenon of time, in that it attempts to negate the effects of time by the logical and probabilistic determination of future events. To appreciate this, you only have to consider the effect time has on the validity of inputs to a forecasting technique.At time t0 all the inputs may be correct, but by time t1, when they are collated, some may well have varied to reflect changing situations, yet this is not shown in the inputs to the forecasting process. Certainly by time t2 (the lead time) the inputs could be totally inaccurate due to changes in the market and this is without considering the changes that may occur in the projection time of a forecast.
Although the analyst may strive to reduce the lead time for a forecast to a minimum in order to ensure that the output is based on the most recently available data, any forthcoming changes in the inputs will ultimately occur in the projection time. As forecasting should be a continuous process, analysts should constantly be updating the inputs to reflect any changes and produce revisedforecasts. It is thus the job of the analyst to reduce lead time to an optimum point where a forecast is based on the latest data without sacrificing accuracy, or involving disproportionate costs for thevalue of the prediction obtained. On the whole, quantitative methods lend themselves to economical revision far more readily than qualitative techniques owing to the nature of the data involved andthe cost of generating and processing them.
A common fallacy is that forecasting is an activity that takes place at periodic intervals, such as once a year, and ceases entirely between these intervals. In fact, in order to reflect changes in the environment and internal structure of the firm, forecasts should be continually evaluated and revised to maintain their credibility. Such factors as price alterations by competitors, government legislation,technological breakthroughs, changes in the organization’s own advertising strategy and alterations of any one of the factors in the marketing mix which has not been previously foreseen can substantially alter sales.
Sometimes a forecast can be rendered totally wrong by completely unforeseen events which would have been impossible to forecast using any method. During the fuel crisis in the UK in the early weeks of September 2000, panic buying caused sales of some products to increase by up to 75 per cent over a three-day period. Few of the companies affected by this could have forecast such a dramatic increase in short-term sales.
The importance of the feedback loop cannot be overemphasized. For the ongoing forecasting process, the feedback loop constitutes a major input to the forecasting process, as can be seen by considering the value attached to error analysis in many quantitative methods. In the case of qualitative techniques, significant weight is attached to any variance between what was forecast and what actually occurred, and the related reasons. Future forecasts thus attach considerable significance to the reasons for past performance and try to incorporate these in any new forecast. The feedback loop is the control on the process.
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