Question II: Forecasting 2. Monthly sales for consumer electronic goods at Best
ID: 3306013 • Letter: Q
Question
Question II: Forecasting 2. Monthly sales for consumer electronic goods at Best Buy for a 4-month period were as follows: Month Feb Marpr Month Sales (in hundreds) 120 194 275 360 Forecast June Sales volume using each of the following techniques (Note: round off all values to two decimal places): a) Naive approach (the most appropriate one) b) A three-month moving average c) A weighted moving average using 0.4 for the most recent month, 0.3, 0.2 and 0.1 for the next most recent months. d) Exponential smoothing with a smoothing constant equal to 0.5 e) Linear Trend Equation ft) Compare the forecast accuracy for a MAD metric using Exponential smoothing, and Linear Trend. Which among the two is a better technique for this data? (30 points)Explanation / Answer
a. Naive approcah is the most primitive approcah of forecasting which believs that tomorro wwill be same as today. Thus, June sales volume will be same as that of May sales volume, that is 360 (in hundreds).
b. The moving average method uses the formula mt=yt-L+1+yt-L+2+yt-L+3+...+yt-1+yt]/L, that is moving average over the last L periods ending in period t is calculated as follows:
m3=(120+194+275)/3=589/3=196.33
m4=(194+275+360)/3=829/3=276.33
Use m4=276.33 as sales for June.
c. A weighted 3-month moving average requires to multiply weights (more weights to recent data) and to forecast the value.
wm4=0.4*360+ 0.3*275+0.2*194+0.1*120=277.3
use wm4=277.3 as sales for June.
d. Exponential smoothing gives greater weights to recent observation and takes into account all previou sobservations. The formula is as follows:
Mt=muYt+(1-mu)Mt-1 where, mu is the smoothing constant, Yt is current value, and Mt-1 is smoothed moving average.
M1=120
M2=0.5*194+0.5*120=157
M3=0.5*275+0.5*157=216
M4=0.5*360+0.5*216=288
Use M4=288 as sales for June.
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