Walmart Inc (WMT)

Receivables turnover

Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019
Revenue (ttm) US$ in thousands 648,125,000 638,785,000 630,794,000 622,021,000 611,289,000 600,112,000 587,824,000 576,013,000 572,754,000 571,962,000 566,145,000 562,839,000 559,151,000 548,743,000 542,026,000 534,661,000 523,964,000 521,086,000 517,989,000 515,640,000
Receivables US$ in thousands 8,796,000 8,625,000 7,891,000 7,647,000 7,933,000 8,218,000 7,522,000 7,674,000 8,280,000 7,349,000 6,103,000 5,797,000 6,516,000 5,770,000 5,111,000 5,029,000 6,284,000 5,612,000 5,382,000 5,342,000
Receivables turnover 73.68 74.06 79.94 81.34 77.06 73.02 78.15 75.06 69.17 77.83 92.77 97.09 85.81 95.10 106.05 106.32 83.38 92.85 96.24 96.53

January 31, 2024 calculation

Receivables turnover = Revenue (ttm) ÷ Receivables
= $648,125,000K ÷ $8,796,000K
= 73.68

The receivables turnover for Walmart Inc has shown fluctuation over the periods provided. The ratio indicates the efficiency of the company in collecting outstanding receivables from its customers during a specific period.

Looking at the trend, we see that the receivables turnover ratio has ranged between 69.17 to 106.32 over the past 20 periods, indicating some variability in collection efficiency. In recent periods, the ratios have been generally high, peaking at 106.32 in January 2020, suggesting a more efficient collection process.

Despite some fluctuations, the trend overall indicates that Walmart has been effectively managing its accounts receivables turnover, with the ratio generally staying at healthy levels. However, it would be beneficial for analysts to further investigate the reasons behind the fluctuations and assess if there are any specific factors driving these changes.


Peer comparison

Jan 31, 2024


See also:

Walmart Inc Receivables Turnover (Quarterly Data)