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Techniques for Seasonality

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Presentation on theme: "Techniques for Seasonality"— Presentation transcript:

1 Techniques for Seasonality
Seasonal variations Regularly repeating movements in series values that can be tied to recurring events. Seasonal relative Percentage of average or trend Centered moving average A moving average positioned at the center of the data that were used to compute it.

2 Seasonality Short-term cyclical, not random, change in demand
Measurement: Relative to overall amount Seasonal Index Estimated using Centered Moving Average (CMA) Question: What does SI tell us about the season if SI = 1.2? 0.8?

3 Seasonality Average of months 2 & 5

4 Seasonality Even number of periods per cycle: Average periods 1-4;
Average the 2 averages. Avg of 2 averages centered at 3 Avg of 1-4 centered between 2-3 Avg of 2-5 centered between 3-4

5 Seasonality

6 Seasonality: Estimate SI’s

7 Seasonality: Deseasonalize demand

8 Seasonality: Deseasonalize demand

9 Seasonality: Estimate trend

10 Seasonality: Forecast

11 Seasonality: Forecast

12 Seasonality: Forecast

13 Seasonality: Forecast

14 Dealing with Trend & Seasonality
Estimate seasonal indexes using CMA Deseasonalize demand data by dividing demand with seasonal indexes Estimate trend based on deseasonalized data using either TAF or Linear Trend Equation Project the trend to the future Forecast by multiplying trend values with seasonal indexes

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