Penn National Gaming Inc (PENN)

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 4,387,900 4,454,700 4,599,000 4,377,600 4,112,000 3,838,200 3,824,900 3,746,900 3,631,600 3,631,100 3,486,500 3,355,600 3,148,000 2,739,900 2,455,600 1,861,000 1,868,000 2,115,900 2,346,400 2,903,226
Inventory US$ in thousands 225,600 11,400 33,000 34,700 106,100 111,800 132,800 134,300 132,300 112,000 104,400 112,200 103,500 49,500 57,100 0
Inventory turnover 18.23 336.68 115.91 107.98 34.23 32.48 26.25 24.99 23.79 24.46 23.52 16.59 18.05 42.75 41.09

December 31, 2024 calculation

Inventory turnover = Cost of revenue (ttm) ÷ Inventory
= $4,387,900K ÷ $—K
= —

The inventory turnover ratio of Penn National Gaming Inc has shown fluctuations over the past few years. The company's inventory turnover was at a high of 336.68 for the quarter ending September 30, 2023, indicating that the company sold and replaced its inventory multiple times within that period. This suggests efficient management of inventory.

However, the inventory turnover ratio dropped significantly in the following quarter ending December 31, 2023, to 18.23, indicating a slower rate of inventory turnover. This may be attributed to various factors such as changes in demand, inventory management practices, or external market conditions.

Subsequently, for the quarters ending March 31, 2024, June 30, 2024, September 30, 2024, and December 31, 2024, the inventory turnover ratio was not provided (\u2014). This lack of data makes it challenging to assess the company's inventory management efficiency during this period.

Overall, while Penn National Gaming Inc has experienced fluctuations in its inventory turnover ratios, which may suggest varying levels of efficiency in managing its inventory, a more comprehensive analysis would be required to understand the underlying reasons behind these fluctuations and their impact on the company's operations and financial performance.