In: Operations Management
The following data shows the quarterly profit (in thousands of dollars) made by a particular company in the past 3 years.
| 
 Year  | 
 Quarter  | 
 Profit ($1000s)  | 
| 
 1  | 
 1  | 
 45  | 
| 
 1  | 
 2  | 
 51  | 
| 
 1  | 
 3  | 
 72  | 
| 
 1  | 
 4  | 
 50  | 
| 
 2  | 
 1  | 
 49  | 
| 
 2  | 
 2  | 
 45  | 
| 
 2  | 
 3  | 
 79  | 
| 
 2  | 
 4  | 
 54  | 
| 
 3  | 
 1  | 
 42  | 
| 
 3  | 
 2  | 
 58  | 
| 
 3  | 
 3  | 
 70  | 
| 
 3  | 
 4  | 
 56  | 
a. Use α = 0.3 to compute the exponential smoothing values for the time series. Compute MSE and the forecast of profit (in $1000s) for the next quarter.
a:
Formulae to be used:
Absolute deviation= |Forecast - Actual|
MSE= Mean square error = sum of squares of deviation/ no. of periods
· the formula to be used in Simple Exponential smoothing is
Ft+1= alpha*At + (1-alpha) Ft
At means Actual demand of t'th period, if you want to find out the Forecast through exponential smoothing= forecast of 3rd period = alpha*actual demand of 2nd period +(1-alpha) *forecast demand of 2nd period
· remember forecast of 1st period is 45, alpha= 0.3
| Period, t | Actual , At | Ft, Exponential Forecast | Absolute deviation= |Forecast - Actual| | squared deviation= (absolute deviation)^2 | 
| 1 | 45 | 45.00 | ||
| 2 | 51 | 45.00 | 6.00 | 36.00 | 
| 3 | 72 | 46.80 | 25.20 | 635.04 | 
| 4 | 50 | 54.36 | 4.36 | 19.01 | 
| 5 | 49 | 53.05 | 4.05 | 16.42 | 
| 6 | 45 | 51.84 | 6.84 | 46.74 | 
| 7 | 79 | 49.79 | 29.21 | 853.49 | 
| 8 | 54 | 58.55 | 4.55 | 20.70 | 
| 9 | 42 | 57.18 | 15.18 | 230.58 | 
| 10 | 58 | 52.63 | 5.37 | 28.84 | 
| 11 | 70 | 54.24 | 15.76 | 248.36 | 
| 12 | 56 | 58.97 | 2.97 | 8.81 | 
| 194.91 | ||||
| MSE |