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This resource provides a detailed overview of sales budgeting and production forecasting, emphasizing key concepts such as desired ending inventory, production budgeting, direct material costs, and labor overheads. Learn the methodologies behind moving averages, exponential smoothing, and seasonal adjustments to enhance demand forecasting. The guide covers simple to double exponential smoothing techniques and how to apply them in practical scenarios for effective decision-making. Ideal for finance professionals looking to refine their budgeting strategies.
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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
Moving Averages • FMA At-3 + At-2 + At-1 Ft = 3 • CMA At-1 + At + At+1 Ft = 3
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
Recursion Ft = At + (1-)Ft-1 Forecast Ft+= at = Ft Simple Exp. Smoothing Model At = a + t
Recursion Alternate Ft = At + (1-)Ft-1 Ft+1 = At + (1-)Ft Simple Exp. Smoothing
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
Wrong, Wrong, Wrong • Tendency is to choose lowest RSE • Min {RSE} when a = 1.0 Fit Past History very well
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}
Exponential Smoothing • Class Demo • Forecast Smoothing vs Exponential Smoothing; Excel tutorial
= 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
= 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
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
+ 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
