Automatic Data Processing Inc (ADP)

Days of sales outstanding (DSO)

Jun 30, 2025 Jun 30, 2024 Jun 30, 2023 Jun 30, 2022 Jun 30, 2021
Receivables turnover 5.74 5.60 5.98 5.20 5.50
DSO days 63.54 65.16 60.99 70.14 66.34

June 30, 2025 calculation

DSO = 365 ÷ Receivables turnover
= 365 ÷ 5.74
= 63.54

The Days of Sales Outstanding (DSO) for Automatic Data Processing Inc. over the period from June 30, 2021, to June 30, 2025, reflects fluctuations that provide insights into the company's accounts receivable management and collection efficiency.

In June 2021, the DSO stood at 66.34 days, indicating the average duration taken to collect receivables. This figure increased to 70.14 days by June 2022, suggesting a slowdown in the collection process or potential challenges in receivables management during that period. The rising trend in 2022 could have been influenced by various factors such as changes in customer credit terms, economic conditions, or internal collection practices.

However, in the subsequent year, the DSO decreased to 60.99 days as of June 2023, signaling an improvement in receivables collection efficiency. This reduction indicates that the company was able to shorten the time it takes to convert receivables into cash, which generally contributes positively to cash flow and liquidity management.

The DSO then experienced a slight increase to 65.16 days by June 2024, and subsequently to 63.54 days in June 2025. Despite these increases, the DSO remained relatively close to the 2021 and 2022 levels, demonstrating some stability but also highlighting ongoing variability in collections.

Overall, the DSO trend over the observed period illustrates periods of both elongation and contraction in receivables collection time, with the shortest average collection period observed in June 2023. This pattern suggests that the company has been actively managing its credit and collection policies, aiming to optimize cash flow and reduce receivables aging. The fluctuations are within a moderate range, indicating a relatively stable credit management environment, although continuous monitoring and potential process improvements could further enhance receivables efficiency.


See also:

Automatic Data Processing Inc Average Receivable Collection Period