Aging groups records by an aging period and counts the rows in each period. The aging period relies on a date column in the data table, and you can subtotal numeric columns for each aging period.
You do not need to sort data before aging.
When you age data, Add-In for Excel:
You are working with an accounts receivable table and you need to find the total number of transactions for each aging period. To find this, you age the data using the due date field and subtotal the transaction amount column.
In your results, you see the total number of transactions per aging period and the total transaction amount per period.
If you output the results of aging to a PivotTable or PivotChart, you can further group the aging periods by the values in additional columns.
You are working with an accounts receivable table and you need to find the total number of transactions per customer for each aging period. To find this, you age the data using the due date column and group the periods by customer ID. You then subtotal the transaction amount column.
In your results, you see the total number of transactions per aging period, grouped by customer, and the total transaction amount per period and per customer each period.
Aged data is grouped using two elements:
Tip
Instead of using the default aging periods, you can specify your own set of periods. User-specified aging periods remain defined until you exit MS Excel or change them.
Use a cutoff date that aligns with a date such as a fiscal period end date. If you leave the default date, the first aging period (if specified as ‘0’) begins on the most recent date in the column, which may or may not be appropriate for your investigation.
The aging period begins on the date that is equal to the cutoff date minus the number of days and ends at the preceding aging period.
If data included in the aged report falls after the cutoff date, a negative aging period is automatically calculated based on the furthest date past the cutoff.
Period dates for cutoff at 30 Nov 2016 | ||||
---|---|---|---|---|
0 (0 to < 30) | 30 (30 to < 60) | 60 (60 to < 90) | 90 (90 to < 120) | 120 (120 to < 365) |
1 Nov 2016 to 30 Nov 2016 | 31 Oct 2016 to 2 Oct 2016 | 1 Oct 2016 to 2 Sep 2016 | 1 Sep 2016 to 3 Aug 2016 | 2 Aug 2016 to 29 Nov 2015 |
You specify the cutoff date as 30 Nov 2016 and the number of days as 30. As a result, this aging period starts on 31 Oct 2016. In your data, you have two rows with dates of 05 Nov 2016 and 10 Nov 2016. These rows are grouped in the 0 to < 30 period.
If you clear Include count, Include percentage is also automatically cleared.
By default, the most recent date in the column you have selected for aging is selected. You are not prevented from specifying an earlier or more recent cutoff date, however the date must fall after the oldest date in the column.
To define the output format, select one of the following output options and then click Finish:
The output results appear in a new ACL Add-In worksheet. If you output the results to a PivotTable or PivotChart, you can further group aged periods by additional columns, or add additional subtotal columns: