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Deseasonalizing Forecasts. Prepared by Aaron Hirst Brigham Young University Fall 2005. Agenda:. Seasonality defined & seasonal adjustment methods Brainstorming Exercise Nuts and Bolts How It Works Seasonal adjustment example Exercise Summary Reading List

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Deseasonalizing Forecasts

Prepared by Aaron Hirst

Brigham Young University

Fall 2005


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Agenda:

  • Seasonality defined & seasonal adjustment methods

  • Brainstorming Exercise

  • Nuts and Bolts

  • How It Works

  • Seasonal adjustment example

  • Exercise

  • Summary

  • Reading List

  • Appendix A: Solution to Exercise


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Seasonality

  • A repeated pattern of spikes or drops in the variable of interest associated with a period of time

  • Examples-

    • Consumer buying habits

    • Price of gasoline


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Seasonality

  • Causes of seasonal movement by class:

    1. Weather (temperature, precipitation)

    2. Calendar Events (religious or secular festivals)

    3. Timing decisions (vacations, accounting periods)


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Seasonal Adjustment Methods

  • X-12 ARIMA

  • X-11 ARIMA

  • EEC Method

  • Burman Method

  • TRAMO

  • Seasonal index


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Brainstorming Exercise

  • How can this tool be used in your organization?


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Nuts and Bolts

Why make seasonal adjustments?

  • Reduces errors in time-series forecasting

  • Improves quality of judgmental forecasts

  • Gives good insight into the factors influencing demand

    The purpose of finding seasonal indexes is to remove the seasonal effects from the time series


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How It Works: Deseasonalizing Forecasts

Four-step procedure for seasonal adjustments:

1. Calculate forecast for each demand values in the time series

2. For each demand value, calculate Demand/Forecast

3. Average the Demand/Forecast for months or quarters to get the seasonal index

4. Multiply the unadjusted forecast by the seasonal index to find adjusted forecast value


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Season Adjustment Example

  • Foster Company makes widgets. The quarterly demand for its widget is given in Exhibit 1

  • Using linear regression forecasting, develop a seasonal index for each quarter and reforecast each quarter


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Seasonal Adjustments ExampleStep 1

Calculate forecast for each demand values in the time series

  • Use the unadjusted regression forecast model

    Y= a + bx


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Seasonal Adjustments Example – Step 1

  • Forecasted demand

    Y=95.85+4.03*period

  • Year 1 Quarter 1:

    Y=95.85+4.03(1)

    =99.9


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Seasonal Adjustments Example – Step 2

  • For each demand value, calculate Demand/Forecast

  • Year 1 Quarter 1:

    72/99.9= 0.72


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Seasonal Adjustments Example - Step 3

  • Average the Demand/Forecast for the quarters to get the seasonal index

  • Quarterly Seasonal Index for Quarter 1:

    (0.72+0.66+0.59+0.55)/4 = 0.63


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Seasonal Adjustments Example - Step 4

  • Multiply the unadjusted forecast by the seasonal index to find the adjusted forecast values

  • Year 1 Quarter 1:

    99.9 * 0.63 = 62.7 (adjusted forecast)




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Exercise

  • Smith Company makes widgets. The quarterly demand for its widget is given in Exhibit A

  • You have been asked to develop a seasonal index for each quarter and reforecast each quarter


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Exercise Table

Click here to check your answer


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Summary

  • Deseasonalizing forecasts is effective for

    • Short-term forecasting

    • Comparability

    • Detecting trend changes early

  • The Seasonal Index is the most simple method for making seasonal adjustments


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Reading List

  • Armstrong, J. Scott. Principles of Forecasting: A Handbook for Researchers and Practitioners. Norwell: Kluwer Academic Publishers, 2001.

  • Bozarth, Cecil C. and Robert B. Handfield. Introduction To Operations And Supply Chain Management. New Jersey: Prentice Hall, 2006.

  • DeLurgio, Stephen and Carl Bhame. Forecasting Systems For Operations Management. Homewood: Irwin, 1991.

  • Hylleberg, Svend. Modeling Seasonality. New York: Oxford Press, 1992.

  • Hylleberg, Svend. Seasonality in Regression. Orlando: Academic Press Inc., 1986.




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