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IENG 215

IENG 215. Estimating. Sales Budget. Desired Ending Inventory. Production Budget. Direct Material. Direct Labor. Factory Overhead. Cost of Good Sold Budget. Selling Expense. Admin Expense. Budgeted Income. Capital Budget. Budgeted Balance. Cash Budget. Sales Forecast.

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IENG 215

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  1. IENG 215 Estimating

  2. Sales Budget Desired Ending Inventory Production Budget Direct Material Direct Labor Factory Overhead Cost of Good Sold Budget Selling Expense Admin Expense Budgeted Income Capital Budget Budgeted Balance Cash Budget

  3. Sales Forecast

  4. Sales Forecast

  5. Moving Averages • FMA At-3 + At-2 + At-1 Ft = 3 • CMA At-1 + At + At+1 Ft = 3

  6. Moving Averages

  7. Moving Averages

  8. Exponential Models • Forecast Exponential Smoothing • Short Term • Bias, forecast lags demand • Simple Exponential Smoothing • .2 < < .5 • Double Exponential Smoothing • Short Term Trends • Holt Winters • Trends with Seasonal adjustment 

  9. Recursion Ft = At + (1-)Ft-1 Forecast Ft+= at = Ft Simple Exp. Smoothing Model At = a + t

  10. Exponential Smoothing

  11. Exponential Smoothing

  12. Recursion Alternate Ft = At + (1-)Ft-1 Ft+1 = At + (1-)Ft Simple Exp. Smoothing

  13. Forecast vs Centered (a=0.2)

  14. Forecast vs Centered (a=1.0)

  15. Effect of Weights

  16. a = = + 0 . 0 F 0 . 0 A 1 . 0 F - 1 t t t = F - 1 t = F 1 a = = + 1 . 0 F 1 . 0 A 0 . 0 F - 1 t t t = A t Effect of Weights

  17. Optimal a ?

  18. Wrong, Wrong, Wrong • Tendency is to choose lowest RSE • Min {RSE} when a = 1.0 Fit Past History very well

  19. Wrong, Wrong, Wrong • Tendency is to choose lowest RSE • Min {RSE} when a = 1.0 Fit Past History very well • Divide data into two sets {t=1:60}, {t=61:101}

  20. Past Fit vs Prediction

  21. Exponential Smoothing • Class Demo • Forecast Smoothing vs Exponential Smoothing; Excel tutorial

  22. Seasonal Adjustment

  23. = a + - a F A ( 1 ) F where - 1 t t t = s length of seasonal cycle Seasonal Adjustment = a + - a F A ( 1 ) F - - t t s t s or

  24. = a + - a F A ( 1 ) F where - 1 t t t = s length of seasonal cycle Seasonal Adjustment = a + - a F A ( 1 ) F - - t t s t s or

  25. Seasonal Adjustment

  26. Recursion ^ Ft = At + (1-)Ft-1 at = 2Ft - Ft 1. 3.  ^ ^ ^ bt = (Ft - Ft) Ft = Ft + (1-)Ft-1 2. 4. 1- Forecast Ft+= at + bt Double Exp. Smoothing Model At = a + bt + t

  27. Double Exp Smoothing

  28. Double Exp Smoothing

  29. + e At = (a + bt)St t Forecast Ft+= (at + bt)St+ Holt-Winters Model Model where St = Seasonal Factor for time period t Recursion 1. Compute Seasonal factors St 2. Deseasonalize data 3. Double smooth on deasonalized data

  30. Holt-Winters

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