Phillips 66 (PSX)

Days of inventory on hand (DOH)

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
Inventory turnover 33.49 22.88 21.50 21.43 35.10 22.92 21.26 27.10 46.26 33.94 29.38 25.85 30.56 20.32 16.07 14.22 15.18 14.30 15.45 17.68
DOH days 10.90 15.95 16.98 17.03 10.40 15.93 17.17 13.47 7.89 10.76 12.43 14.12 11.95 17.96 22.71 25.68 24.04 25.52 23.63 20.64

December 31, 2024 calculation

DOH = 365 ÷ Inventory turnover
= 365 ÷ 33.49
= 10.90

The days of inventory on hand (DOH) for Phillips 66 has shown some fluctuations over the past few years. From March 31, 2020, to June 30, 2020, DOH increased from 20.64 days to 23.63 days. Subsequently, there was a further increase to 25.52 days by September 30, 2020. However, by December 31, 2020, there was a slight decrease to 24.04 days.

The trend changed in the following year, with a rise in DOH to 25.68 days by March 31, 2021, followed by a significant drop to 22.71 days by June 30, 2021. The decrease continued, reaching 17.96 days by September 30, 2021, and a notable decline to 11.95 days by December 31, 2021.

The trend of decreasing DOH continued in the next year, dropping to 10.76 days by September 30, 2022, and further to 7.89 days by December 31, 2022. However, there was an increase to 13.47 days by March 31, 2023, followed by fluctuation in the range of 15-17 days until June 30, 2024.

Overall, the trend indicates that Phillips 66 managed its inventory more efficiently as DOH decreased over the period under review. A lower DOH reflects a quicker turnover of inventory, suggesting effective inventory management practices. However, it is essential to monitor inventory levels to ensure they are at an optimal level to support operations without causing stockouts or excess inventory costs.


See also:

Phillips 66 Average Inventory Processing Period (Quarterly Data)