17.1. Account Analysis
The most straightforward way to estimate collection percentages is to compute the percentages of collections realized from past months. Once the experience has been analyzed, the results can be adjusted for trends and applied to the credit sales portrayed in the sales forecast. An example illustrates the technique.
Example 1
Assume that an analysis of collection experience for August sales revealed these collection data:
| Description | % of Total Credit Sales |
|---|---|
| Collected in August | 2.3 |
| September | 80.2 |
| October | 9.9 |
| November | 5.1 |
| December | .5 |
| Cash discounts | 1.0 |
| Bad debt losses | 1.0 |
| Total | 100.0 |
If next year's sales in August could be expected to fall into the same pattern, then application of the percentages to estimated August credit sales would determine the probable monthly distribution of collections. The same analysis applied to each month of the year would result in a reasonably reliable basis for collection forecasting. The worksheet (August column) for cash collections might look like this:
| Month of Sale | % Total | Description Sales Net | August Collection |
|---|---|---|---|
| April | 5 | $168,000 | $840 |
| May | 4.2 | 192,000 | 8,064 |
| June | 8.9 | 311,100 | 27,688 |
| July | 82.1 | 325,600 | 267,318 |
| August | 2.3 | 340,000 | 7,820 |
| Total Collections | $311,730 | ||
| Cash Discounts (July) | 1.0 | 325,600 | (3,256) |
| Losses | 1.0 | 340,000 | (3,400) |
| Total | $305,074 |
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