Costco Wholesale Corp (COST)

Days of sales outstanding (DSO)

Sep 1, 2024 May 12, 2024 Feb 18, 2024 Nov 26, 2023 Sep 3, 2023 May 7, 2023 Feb 12, 2023 Nov 20, 2022 Aug 28, 2022 May 8, 2022 Feb 13, 2022 Nov 21, 2021 Aug 29, 2021 May 9, 2021 Feb 14, 2021 Nov 22, 2020 Aug 30, 2020 May 10, 2020 Feb 16, 2020 Nov 24, 2019
Receivables turnover 93.51 98.22 89.54 96.64 106.04 94.10 86.36 99.93 101.27 109.26 94.18 105.12 108.67 117.01 92.36 105.06 107.59 106.75 79.65 90.40
DSO days 3.90 3.72 4.08 3.78 3.44 3.88 4.23 3.65 3.60 3.34 3.88 3.47 3.36 3.12 3.95 3.47 3.39 3.42 4.58 4.04

September 1, 2024 calculation

DSO = 365 ÷ Receivables turnover
= 365 ÷ 93.51
= 3.90

Days of Sales Outstanding (DSO) is a key financial ratio that measures the average number of days it takes for a company to collect revenue after a sale has been made. Analyzing Costco Wholesale Corp's DSO over multiple periods provides insights into its efficiency in collecting payments from customers.

The trend in Costco's DSO over the past several quarters shows relatively stable performance, fluctuating between 3.12 days and 4.23 days. Lower DSO values indicate faster collection of receivables, which is generally favorable as it signifies effective credit management and liquidity.

The lowest DSO of 3.12 days in May 9, 2021, suggests that Costco was exceptionally efficient in collecting revenue during that period. On the other hand, the highest DSO of 4.58 days in Nov 24, 2019, may indicate a slight delay in collecting payments, which could be due to various factors such as changes in customer payment behavior or seasonal variations.

Overall, Costco's DSO levels demonstrate a consistent and efficient approach to managing accounts receivable, reflecting positively on its cash flow management and operational efficiency. Further monitoring of DSO trends will be crucial to assess any changes in the company's collection practices and financial health.


Peer comparison

Sep 1, 2024


See also:

Costco Wholesale Corp Average Receivable Collection Period (Quarterly Data)