1. Forecasting

2. Why Forecast ? To Plan For Demand Its not a goal

3. Vocabulary of Time Series Trend – gradual upward or downward movement of the data over time Seasonality – demand fluctuation pattern above and below the trend line repeating at certain points of time ( not limited to years) example – business at the bank with seasonal effects around mid and end of month paydays Cycles – patterns that occur in the data every several years (reflect business cycles) Random Variations ( Special Causes )– chance variation in the data – no pattern – like error in statistical model

4. Graph of a Time Series

5. Analyse data Univariate A No Yes Plot Data into I-MR Chart Huge Variations No Correct For Special Causes Decompose Stationary ? Trend & Seasonality Single Exponential Smoothening Double Exponential Smoothening Holt -Winters Yes No No Stable after Checking for n/2 vaues/ errors? Forecast Value Regression MAPE ,MAD, MSE Should be very good pointers Yes Yes Yes Yes No

6. Illustration Of Errors

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