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Six Rules of Effective Forecasting

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Six Rules of Effective Forecasting
Six Rules of Effective Forecasting
Q1: Write a summary about the six rules of effective forecasting?
Paul Saffo is the author of the article of six rules for effective forecasting. He points out that effective forecasting is very different from accurate forecasting as it is possible that a forecast is effective but it may or may not be accurate. Accurate forecasting entails being unsure of the situation and one should not race to answers. Effective forecasting on the other hand means looking at the full range of forecast, understanding the un-surety that lies ahead and not rushing to a conclusion. He also adds that a wise consumer is not a bystander but a participant and a critic. The six rules of forecasting given by him are given below:
Rule 1: Define the cone of uncertainty:
He says that one has to rely on intuition but effective forecasting provides essential context that informs one’s intuition. He adds that forecasters should use their common sense of visualizing and predicting the uncertainties. He describes mapping a cone of uncertainty as a tool that is used to delineate possibilities that extend out from a particular moment in time. The forecaster’s should define the cone in a manner that helps the decision maker exercise strategic judgment and it should encompass all the reasonable possibilities that lie ahead. The cone can be narrowed in subsequent refinements but if the cone is drawn too narrow, it leaves you open to avoidable unpleasant surprises.
Rule 2: Look for the S Curve:
Saffo points out that the changes rarely unfold in a linear way. Changes unfold slowly at start and after a critical point is reached, everything starts to change rapidly before it eventually settles down. Very large, broadly defined curves are composed of small, precisely defined and linked S curves. Good forecasting is to identify an S-curve pattern as it begins to emerge. He further states that as forecaster one should never mistake a clear view for a short distance

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