Churchill Downs Incorporated (CHDN)

Inventory turnover

Dec 31, 2024 Sep 30, 2024 Jun 30, 2024 Mar 31, 2024 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
Cost of revenue (ttm) US$ in thousands 1,795,800 1,751,500 1,717,100 1,684,200 1,666,000 1,614,600 1,486,600 1,360,000 1,243,400 1,176,000 1,182,800 1,174,700 1,151,100 1,095,700 1,057,400 885,200 860,500 878,700 872,900 1,000,300
Inventory US$ in thousands 11,600 77,300 63,300 67,100 63,500 74,900 1,582,600 1,589,300 65,500 64,300 70,600 69,200 48,000 53,600 57,600 49,800 43,600
Inventory turnover 154.81 21.55 25.51 22.15 21.42 16.60 0.74 0.74 17.93 17.90 15.52 15.28 18.44 16.05 15.26 17.53 22.94

December 31, 2024 calculation

Inventory turnover = Cost of revenue (ttm) ÷ Inventory
= $1,795,800K ÷ $11,600K
= 154.81

The inventory turnover ratio for Churchill Downs Incorporated has shown some fluctuations over the past few years. The ratio indicates how efficiently the company is managing its inventory by measuring the number of times inventory is sold and replaced within a specific period.

From March 31, 2020, to June 30, 2022, the inventory turnover ranged from 22.94 to 0.74, showing a significant decline. This sharp decrease may suggest potential issues with inventory management or fluctuations in sales volume during this period.

However, from December 31, 2022, to March 31, 2024, the inventory turnover ratio has stabilized and improved, ranging between 16.60 and 154.81. The sudden spike in the ratio to 154.81 on December 31, 2024, may indicate a possible anomaly or irregularity in inventory turnover that requires further investigation.

Overall, Churchill Downs Incorporated's inventory turnover ratio has shown variability, reflecting fluctuations in sales and inventory management practices. It is essential for the company to closely monitor and analyze this ratio to ensure efficient inventory utilization and optimize operational performance.