1. The following tabulations are actual sales of units for six months and a starting forecast in January. Calculate forecasts for the remaining five months using simple exponential smoothing with ? = .20. Also, calculate MAD for the forecasts. Month January February March April May June Demand F 100 80 94 106 80 68 94 2. Assume that your stock of sales merchandise is maintained based on the forecast demand. If the distributor’s sales personnel call on the first day of each month, compute your forecast sales by each of the three methods requested here. Month Actual June 140 July 180 August 170 a. Using a simple three-month moving average, what is the forecast for September? b. Using a weighted moving average, forecast for September (Use the following weights: 0.2, 0.3, and 0.5) c. Using a simple exponential smoothing and assuming the forecast for June had been 130, forecast sales for September with alpha = 0.30 3. Assume an initial starting forecast of 300 units, a trend of 8 units, an alpha of 0.30 and a delta of 0.40. If actual demand turned out be 288, calculate the forecast for the next period. 4. Historical demand for a product is as follow: Demand Apr May Jun Jul Aug Sep 60 55 75 60 80 75 Using Least Square Method (Simple regression), forecast for October. 5. The following table shows the past 2 years of quarterly sales information for Rauniar Chips. Assume that there are both trend and seasonal factors and that seasonal cycle is one year. Use trend projection with seasonal variation method for forecast quarterly sales for the next year. Quarter I II III IV Sales 160 195 150 140 Quarter V VI VII VIII Sales 215 240 205 190
