Example: Method 1: Percent Over Last Year
The Percent Over Last Year formula multiplies sales data from the previous year by a factor you specify and then projects that result over the next year. This method might be useful in budgeting to simulate the affect of a specified growth rate or when sales history has a significant seasonal component.
Forecast specifications: Multiplication factor. For example, specify 110 in the processing option to increase the previous year's sales history data by 10 percent.
Required sales history: One year for calculating the forecast, plus the number of time periods that are required for evaluating the forecast performance (periods of best fit) that you specify.
This table is history used in the forecast calculation:
Past Year |
Jan |
Feb |
Mar |
Apr |
May |
Jun |
Jul |
Aug |
Sep |
Oct |
Nov |
Dec |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 |
128 |
117 |
115 |
125 |
122 |
137 |
140 |
129 |
131 |
114 |
119 |
137 |
This table shows the forecast for next year, 110 Percent Over Last Year:
Jan |
Feb |
Mar |
Apr |
May |
Jun |
Jul |
Aug |
Sep |
Oct |
Nov |
Dec |
|---|---|---|---|---|---|---|---|---|---|---|---|
141 |
129 |
127 |
138 |
134 |
151 |
154 |
142 |
144 |
125 |
131 |
151 |
January forecast equals 128 × 1.1 = 140.8 rounded to 141.
February forecast equals 117 × 1.1 = 128.7 rounded to 129.
March forecast equals 115 × 1.1 = 126.5 rounded to 127.