Example of Exponential Smoothing
By using the previous example and smoothing constant 0.3 generate monthly forecasts
|
Months
|
Sales
|
Forecasts: a = 0.3
|
|
January
|
1200
|
|
|
February
|
1280
|
1200
|
|
March
|
1310
|
1224
|
|
April
|
1270
|
1250
|
|
May
|
1190
|
1256
|
|
June
|
1290
|
1233
|
|
July
|
1410
|
1250
|
|
August
|
1360
|
1283
|
|
September
|
1430
|
1327
|
|
October
|
1280
|
1358
|
|
November
|
1410
|
1335
|
|
December
|
1390
|
1357
|
Solution
Since there were no forecasts before January we take Jan to be the forecast for February.
∴ Feb - 1200
For March;
March forecast = Feb forecast + 0.3 ( Feb sales - Feb forecast)
= 1200 + 0.3 (1280 - 1200) =1224
Note:
- The value a lies between 1 and 0.
- The higher a value, the extra forecast is sensitive to the current status.