Fortinet Inc (FTNT)
Days of sales outstanding (DSO)
Dec 31, 2023 | Sep 30, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | ||
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Receivables turnover | 3.74 | 5.00 | 4.54 | 4.26 | 3.43 | 4.20 | 4.08 | 4.47 | 4.10 | 5.14 | 4.96 | 4.27 | 3.59 | 4.49 | 4.71 | 4.75 | 3.95 | 5.31 | 4.83 | 4.90 | |
DSO | days | 97.64 | 72.93 | 80.45 | 85.74 | 106.40 | 86.92 | 89.36 | 81.61 | 89.07 | 71.03 | 73.57 | 85.54 | 101.62 | 81.33 | 77.47 | 76.81 | 92.34 | 68.70 | 75.57 | 74.50 |
December 31, 2023 calculation
DSO = 365 ÷ Receivables turnover
= 365 ÷ 3.74
= 97.64
To analyze Fortinet Inc's Days Sales Outstanding (DSO) over the past eight quarters, we observe fluctuations in the collection period for accounts receivable.
In Q4 2023, the DSO stood at 96.47 days, indicating the company took about 96.47 days on average to collect outstanding sales revenues. This figure reflects a significant increase from the previous quarter (Q3 2023) when the DSO was 71.54 days. The increase in DSO might suggest potential challenges in collecting receivables efficiently, thereby tying up cash flow in the business.
Comparing Q4 2023 to the same quarter of the previous year (Q4 2022), there has been an improvement in DSO, as it reduced from 104.25 days to 96.47 days. This improvement indicates a positive trend in collecting sales revenues more promptly, which could lead to better liquidity and cash flow management.
Overall, based on the historical trend, Fortinet Inc's DSO has exhibited fluctuations but generally remains within a range of around 70 to 100 days. It is essential for the company to closely monitor and manage its accounts receivable collection process to ensure timely receipt of revenues and strengthen its financial position.
Peer comparison
Dec 31, 2023
See also:
Fortinet Inc Average Receivable Collection Period (Quarterly Data)