Use exponential smoothing, with α =.2, to develop a forecast for March and April. (Hint: Use the forecast for March 2020 as the actual sales in March 2020 in developing the forecast for April 2020.) b. Comment on the use of exponential smoothing for forecasts more than one period into the future. c. Use trend projection to forecast sales for March and April 2020.
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1. The information provided below relates to sales in a dine-in restaurant in Salisbury Maryland:
| Months | Sales (in $1000) |
| Mar-19 | 46.5 |
| Apr-19 | 49.6 |
| May-19 | 49.8 |
| Jun-19 | 61.9 |
| Jul-19 | 65.5 |
| Aug-19 | 64 |
| Sep-19 | 70.3 |
| Oct-19 | 59.8 |
| Nov-19 | 60 |
| Dec-19 | 70.8 |
| Jan-20 | 51.9 |
| Feb-20 | 59.6 |
Due to Coronavirus outbreak, Restaurants were ordered to shut down during March and April of 2020. The restaurant manager is trying to determine the amount of sales lost while it was shut down during March and April because of the outbreak.
a. Use exponential smoothing, with α =.2, to develop a
b. Comment on the use of exponential smoothing for forecasts more than one period into the future.
c. Use trend projection to forecast sales for March and April 2020.
d. The restaurant had purchased as insurance policy to be be fully compensated in case of forced shut down. The insurance company proposed a settlement based on lost sales of $96,100 in March and April. This is based on the total sales for March and April of 2019 combined. Is this amount fair? If not, what amount would you recommend as a counteroffer?
2. The following table shows information regarding sales in a restaurant in Ocean City (in $1000)
| Winter | Spring | Summer | Fall | |
| 2015 | 75 | 110 | 190 | 120 |
| 2016 | 79 | 114 | 203 | 127 |
| 2017 | 84 | 121 | 220 | 132 |
| 2018 | 90 | 128 | 231 | 140 |
| 2019 | 93 | 135 | 245 | 145 |
a. Code Winter 2015 to Fall 2019 by assigning 1 to Winter 2015 and ... 20 to Fall 2019.
b. Conduct a simple regression to find the trend line by using sales as dependent variable and codes (time) as independent variable.
c. Compute 4 quarter moving averages and ratio to moving averages to compute seasonal indexes.
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