Forecasting HW The following is the recent historical sales of Sony HDTV at a lo
ID: 388179 • Letter: F
Question
Forecasting HW The following is the recent historical sales of Sony HDTV at a local BestBury store Month 1. (a) Use a 4-month moving average to forocast sales for June (b) If June actually experienced a demand of 75, what is the forecast for July? 2. (a) Using weighted moving average method, with weights of 0.5 one period ago, 0.3 two periods ago, and 0.2 three periods ago, to forecast sales for June. (b) If June actually experienced a demand of 75, what is the forecast for July? 3. (a) Use exponential smoothing, first with a smoothing constant of 0.2 and then with onc of 0.9, to develop forecasts for monts Feb. through June. Assuming the forecast for January had been 70. (b) Compute the two sets of MAD (-0.2 and a -0.9) using data from Jan through May. Which smoothing constant is a better choice by evaluating MAD? (c) Compute TS using data from Jan. through May, for the forecasting with a- 0.2. Does the store manager need to re-evaluate or adjust the forecasting model used? 4. Use simple lincar regression to forecast sales for June Selected Answers: 1 . (a) F6 = 60.75 2. () F6-59.9 3. (a)a-02: F6-63.85 a- 0.9: F6- 61.71 (b) a=0.2: MAD is about 7.11:a:09; MAD s about loos, smoothing constant 0.2 is better because the error measurement values are smaller C) The TS value is out of acceptable range, indicating bias in the forecasting and an adjustment is needed 4. F6-56.2Explanation / Answer
Answer 1.a
The four month moving average for June is Total of sales of previous 4 months divided by 4
4 month moving average = (62+70+48+63)/4 = 60.75
Answer 1.b
The forecast for july as per four month moving average = (75+63+48+70)/4 = 64
Answer 2.a
Formula for weighted moving average is sum of weightage multiplied by sales of previous month
Forecast of June = (0.5 × 63) + (0.3 × 48) + (0.2 × 70)
= 31.5 + 14.4 + 14 = 59.9
Answer 2b.
Forecast for July = (0.5 × 75) + (0.3 × 63) + (0.2×48)
= 37.5 + 18.9 + 9.6
= 66
Answer 3a.
Forecast for current month = Forecast for previous month + smoothing constant(Actual sales for previous month - Forecast for previous month)
Case 1: When smoothing constant is 0.2
FFeb = FJan + 0.2(ActualJan - FJan) = 70 + 0.2( 65 - 70) = 70 - 1 = 69
FMarch = FFeb + 0.2(ActualFeb - FFeb) = 69 + 0.2(62 - 69) = 67.6
FApril = FMarch + 0.2(ActualMarch - FMarch) = 67.6 + 0.2( 70 - 67.6) = 68.08
FMay = FApril + 0.2(ActualApril - FApril) = 68.08 + 0.2(48 - 68.08) = 64.064
FJune = FMay + 0.2(ActualMay - FMay) = 64.064 + 0.2(63 - 64.064) = 63.85
When smoothing constant = 0.9
FFeb = FJan + 0.2(ActualJan - FJan) = 70 + 0.9( 65 - 70) = 65.5
FMarch = FFeb + 0.2(ActualFeb - FFeb) = 65.5 + 0.9(62 - 65.5) = 62.35
FApril = FMarch + 0.2(ActualMarch - FMarch) = 62.35 + 0.9( 70 - 62.35) = 69.325
FMay = FApril + 0.2(ActualApril - FApril) = 69.235 + 0.9(48 - 69.235) = 50.12
FJune = FMay + 0.2(ActualMay - FMay) = 50.12 + 0.9(63 - 50.12) = 61.71