MillerKnoll Inc (MLKN)

Receivables turnover

Feb 28, 2025 Nov 30, 2024 Aug 31, 2024 May 31, 2024 Mar 2, 2024 Feb 29, 2024 Dec 2, 2023 Nov 30, 2023 Sep 2, 2023 Aug 31, 2023 Jun 3, 2023 May 31, 2023 Mar 4, 2023 Feb 28, 2023 Dec 3, 2022 Nov 30, 2022 Sep 3, 2022 Aug 31, 2022 May 31, 2022 May 28, 2022
Revenue (ttm) US$ in thousands 3,597,000 3,574,700 3,476,600 3,544,800 3,605,400 3,650,000 3,695,400 7,789,600 7,796,800 7,863,900 7,930,900 3,955,600 4,065,800 4,162,300 4,256,400 4,308,300 4,341,900 4,309,300 4,249,800 4,175,600
Receivables US$ in thousands 318,700 344,800 323,100 363,500 380,900
Receivables turnover 11.31 10.72 24.13 21.82 10.96

February 28, 2025 calculation

Receivables turnover = Revenue (ttm) ÷ Receivables
= $3,597,000K ÷ $—K
= —

Analyzing the receivables turnover of MillerKnoll Inc based on the provided data, we observe fluctuations in the ratio over different periods.

- As of May 28, 2022, the receivables turnover was reported at 10.96, indicating that on average, the company collected its outstanding receivables approximately 10.96 times during the year.

- There is no data available for several subsequent dates until June 3, 2023, where a significant increase in the receivables turnover to 21.82 was noted. This indicates a notable improvement in the efficiency of collecting receivables during this period.

- Subsequently, on September 2, 2023, the receivables turnover further increased to 24.13, indicating that the company was collecting its outstanding receivables even more frequently.

- However, by December 2, 2023, the receivables turnover ratio decreased to 10.72, compared to the previous period, suggesting a slowdown in the collection of receivables.

- The trend continues with fluctuations in the receivables turnover ratio, showing no data available for several periods thereafter.

Overall, the analysis of the receivables turnover ratio indicates variations in the efficiency of MillerKnoll Inc in collecting its accounts receivable over the reported periods. The company experienced periods of both improved and reduced effectiveness in converting credit sales into cash, which could reflect changes in customer payment behavior, company credit policies, or other operational factors.