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It's known that despite the time and effort put into forecasting, in a dynamic market with lots of volatility, the forecast will always be inaccurate. [ It is not uncommon to hear of companies within High-Tech struggling to get demand forecast accuracy above 50 percent. The primary reason for this volatility is the Long Tail effect caused by short product life cycle and mass customization on the product side, and globalization and outsourcing on the operations side. The most sensible approach is to look at the actual past demands. Some demands show some kind of trend or cycles, which could be used for our advantage and to forecast more accurately. The common behaviors of the demand is as following: Stationary: here the demand show a smooth pattern where no increase or decrease in the demand. Linear: an steady increase or decrease in the demand Nonlinear: Where the demand takes a weird increasing or decreasing slopes. Trends: Seasonal: Where the demand is repeated after a certain period Cycle: this is easily detected graphically where the demand repeats in each cycle. Random: The most annoying type. it maybe meaningless to forecast such kind of behavior

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Q: How should shoppers stop develop its demand forecast?
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