Season Your Data with Theory and Common Sense in Nate Silver's Book, Signal and The Noise

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I attended my second APICS Central Indiana Professional Development Meeting at Carmel on the 13th of March 2014. The keynote speaker was Bill Whiteside, who is a founder of Demand Solution Northeast, which markets and supports the Demand Solution suite of forecasting and supply chain management software in the Northeast US. He is a graduate of the University of Notre Dame and a professional member of APICS. At that dinner event, he presented twelve supply chain forecasting lesson from “The Signal and The Noise.”
The Signal and The Noise book is about the overwhelming proliferation of data and how so much of that data can produce more noise (garbage) than the signal (truth). The book told us how to find the truth amidst all the noise and …show more content…

Lesson number three is “it is better to be a fox than a hedgehog”. On the book, Silver expands this idea and notes that a fox know many things because it’s likely to intensely question itself and gather information from a variety of sources. A hedgehog, on the other hand, will be more likely to rely on a single source of conventional wisdom. This idea encourage us to be resourceful like a fox, so we can be a more valuable contributor during the collaborative process. Collaboration is typically understood as a process in which multiple people provide input .However, collaboration can also be performed on an individual basis by collecting the information we need to shape to temper our projections and plans.
Lesson number four is “polls become more accurate the closer you get to the Election Day”. This idea encourage us to continually update our forecast especially when we are approaching a decision point. The farther into the future you forecast, the less accurate your forecasts are likely to be. The closer you can update your forecasts to the point of decision, the more you improve your chances for accuracy. But, we need to notice if we wait too long to share our forecasts in order to ensure maximum accuracy, then we are defeating the purpose of the forecasting process. The optimal time to commit to a forecast is when a decision has to be made based on that forecast. For example, a commitment to production or to a purchase. We need

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