Aging Buckets

Cash Collected per Aging Bucket = Total Cash Collected / Total Bucketed Receivables

Where:

• The total cash collected is the amount of cash collected from credit sales in a given aging bucket. For example, the company may track 30, 60, 90 and 120 day aging buckets.

• Total bucketed receivables is the total amount of unpaid credit sales that fall into a specific aging timeframe or bucket. The aging days are calculated from the day the credit sale occurred.

Accounting and finance metrics allow a company's internal analysts to understand how well its accounting and finance departments are operating. This is usually assessed by examining metrics such as error rates, transactions processed, discounts taken, and turnaround times. Accounting and finance metrics allow the company's management team to identify areas where changes can be made that will improve their key operating metrics. One of the ways to learn about the effectiveness of the company's credit policy and collections process is to calculate its cash collected per aging bucket.

A company's accounting, finance and collections departments are usually responsible for determining the policy that allows customers to make purchases on credit. Once a sale on credit occurs, it is the responsibility of the company's accounts receivable and collections teams to manage the dunning processes which will attempt to collect the dollars owed the corporation. One of the ways to measure the effectiveness of these policies and processes is to measure the company's cash collected per aging bucket. This information can also be used to project the amount bad debt the company will have to write off as never being collected from a credit sale.

Typically, the analysts tasked with measuring these values will work with the collections department to determine the timeframes of interest. For example, receivables may be placed in buckets of 30, 60, 90, 120, 150 and 180 days. The company will then measure how much of the money owed in each bucket is collected from customers. This information can then be used not only to assess performance, but also in forecasts of bad debt expense. For example, a company might expect to collect 95% of receivables over 30 days old, while only expecting to collect 5% of receivables over 180 days old.

The CFO of Company ABC wanted to understand if a recent downturn in the economy was causing receivables to grow as well as an estimate of the bad debt expense to be reported in the next quarter. In order to perform this calculation, her team looked at historical information such as the amount of cash collected per aging bucket. Her analytical team analyzed this information and eventually passed it to the collections team to develop the bad debt estimate. The CFO's team found the following:

Based on the above information, the collections team was able to provide the CFO with an estimate of the quarterly write off for bad debt.