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Analyzing Seasonality Techniques for Forecasting Demand

Learn techniques to identify and analyze seasonal variations in demand, including using Seasonal Index and Centered Moving Average. Understand how to estimate, deseasonalize, and forecast demand to better manage inventory and optimize resources.

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Analyzing Seasonality Techniques for Forecasting Demand

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  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 periods 2-5; • 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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