Crowdstrike Holdings Inc (CRWD)

Cash conversion cycle

		Jan 31, 2025	Oct 31, 2024	Jul 31, 2024	Apr 30, 2024	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
Days of inventory on hand (DOH)	days	—	—	—	—	—	105.66	104.88	105.99	113.44	110.03	—	114.76	120.79	117.55	117.25	119.34	128.56	110.48	107.94	122.42
Days of sales outstanding (DSO)	days	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
Number of days of payables	days	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
Cash conversion cycle	days	0.00	0.00	0.00	0.00	0.00	105.66	104.88	105.99	113.44	110.03	0.00	114.76	120.79	117.55	117.25	119.34	128.56	110.48	107.94	122.42

January 31, 2025 calculation

Cash conversion cycle = DOH + DSO – Number of days of payables
= — + — – —
= 0.00

The cash conversion cycle of Crowdstrike Holdings Inc has shown variability over the historical period. The company's cash conversion cycle reflects the time it takes for Crowdstrike to convert its resources and inputs, such as inventory and accounts receivable, into cash flows from sales.

From April 30, 2020, to January 31, 2022, the cash conversion cycle exhibited fluctuations ranging from 107.94 days to 128.56 days. This indicates that Crowdstrike had varying efficiency levels in managing its working capital during this period.

Starting from April 30, 2022, the cash conversion cycle reduced significantly to 114.76 days and further decreased to 104.88 days by July 31, 2023. This improvement suggests Crowdstrike became more effective in managing its cash flows and working capital components during this time frame.

Notably, there were instances where the cash conversion cycle was recorded as 0.00 days, indicating potentially anomalous or unreported data for the periods of July 31, 2022 to January 31, 2024.

Overall, the analysis of Crowdstrike's cash conversion cycle underscores the company's ability to efficiently manage its working capital and convert its resources into cash, albeit with some intermittent anomalies in the data.