Analysis of Short-term (Operating) Activity Ratios
Quarterly Data
Activity ratios measure how efficiently a company performs day-to-day tasks, such us the collection of receivables and management of inventory.
Short-term Activity Ratios (Summary)
United States Steel Corp., short-term (operating) activity ratios (quarterly data)
Based on: 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31).
- Inventory Turnover
- The inventory turnover ratio displayed fluctuations across the observed periods, with values ranging from a low of 5.39 to a high of 7.12. Notably, there was a decline during early 2020, followed by a recovery toward the end of 2020. The ratio generally stabilized around 6.5 in 2023, indicating consistent inventory management efficiency.
- Receivables Turnover
- Receivables turnover showed variability with an upward trend in mid-2020 and a notable peak in the first half of 2023, reaching above 12. This suggests that the company improved its ability to collect receivables more quickly during certain periods, although there were intermittent declines mainly in 2021.
- Payables Turnover
- The payables turnover ratio fluctuated between approximately 3.97 and 7.24, with generally lower turnover observed in 2021 and a relative increase in late 2020. This pattern indicates changes in the rate at which the company paid its suppliers, with slower payments in 2021 followed by a modest recovery.
- Working Capital Turnover
- The working capital turnover exhibited significant variation, with a marked decline in early 2020 reaching below 4, followed by partial recoveries. The ratio tended to trend lower after 2019, suggesting reduced efficiency in utilizing working capital to generate sales.
- Average Inventory Processing Period
- The average inventory processing period shifted from approximately 60 days in 2019 to a peak near 68 days in mid-2022, before shortening to around 55-57 days in 2023. This indicates some periods of slower inventory movement, though recent data points to improvements in inventory turnover speed.
- Average Receivable Collection Period
- This metric decreased from about 43 days in early 2019 to approximately 28 days in mid-2023, highlighting enhanced effectiveness in collecting receivables, particularly in the most recent periods. There were fluctuations, with an increase in 2021 before the subsequent reduction.
- Operating Cycle
- The operating cycle displayed a general decline from around 104 days in early 2019 to below 90 days by mid-2023. This reduction points to improved operational efficiency in converting inventory and receivables into cash, despite some intermittent increases, notably during 2021-2022.
- Average Payables Payment Period
- The payment period to suppliers showed an upward trend from approximately 62 days at the end of 2019 to over 90 days during 2021, which indicates longer payment terms or slower payment processes during that time. This period shortened again in recent years but remained higher than pre-2020 levels.
- Cash Conversion Cycle
- The cash conversion cycle remained relatively stable with values mostly ranging from around 13 to 38 days. It decreased to its shortest duration near 13 days in late 2022, representing an improvement in the overall liquidity management process. The cycle lengthened slightly thereafter but stayed at moderate levels.
Turnover Ratios
Average No. Days
Inventory Turnover
United States Steel Corp., inventory turnover calculation (quarterly data)
| 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 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||
| Cost of sales | 4,161) | 3,953) | 3,934) | 4,359) | 4,661) | 3,823) | 3,894) | 3,881) | 3,678) | 3,080) | 2,384) | 2,295) | 2,274) | 2,605) | 2,781) | 2,902) | 3,227) | 3,172) | ||||||
| Inventories | 2,540) | 2,541) | 2,359) | 2,759) | 3,014) | 2,663) | 2,210) | 2,086) | 1,914) | 1,750) | 1,402) | 1,398) | 1,634) | 2,075) | 1,785) | 2,071) | 2,166) | 2,133) | ||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||
| Inventory turnover1 | 6.46 | 6.65 | 7.11 | 6.07 | 5.39 | 5.74 | 6.58 | 6.24 | 5.98 | 5.73 | 6.82 | 7.12 | 6.46 | 5.55 | 6.77 | 6.04 | 5.90 | 5.94 | ||||||
| Benchmarks | ||||||||||||||||||||||||
| Inventory Turnover, Competitors2 | ||||||||||||||||||||||||
| Freeport-McMoRan Inc. | 2.68 | 2.62 | 2.91 | 3.07 | 3.09 | 3.25 | 3.12 | 3.25 | 3.01 | 2.84 | — | — | — | — | — | — | — | — | ||||||
Based on: 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31).
1 Q2 2023 Calculation
Inventory turnover
= (Cost of salesQ2 2023
+ Cost of salesQ1 2023
+ Cost of salesQ4 2022
+ Cost of salesQ3 2022)
÷ Inventories
= (4,161 + 3,953 + 3,934 + 4,359)
÷ 2,540 = 6.46
2 Click competitor name to see calculations.
- Cost of Sales
- The cost of sales shows notable fluctuations over the examined periods. From early 2019 through the end of 2019, there is a clear downward trend, with costs decreasing from approximately $3.17 billion to $2.78 billion. This decline continues into mid-2020, reaching a low around $2.27 billion. However, starting from late 2020, the cost of sales begins to increase again, with a pronounced rise observed throughout 2021, peaking near $3.9 billion by the end of 2021. The upward trend persists into 2022, reaching the highest values observed in this timeframe, close to $4.66 billion in mid-2022. Early 2023 data indicates a slight decrease but costs remain elevated around $4.1 billion.
- Inventories
- Inventory levels exhibit a generally stable to slightly increasing pattern through 2019, ranging from approximately $2.13 billion to $1.78 billion, with a minor dip in late 2019. During 2020, inventories decline sharply in the first half but stabilize in the second half, falling from $2.08 billion to around $1.4 billion. Starting in 2021, inventories take an upward trajectory, increasing steadily to more than $2.2 billion by the end of 2021. This growth trend intensifies in 2022, with inventories peaking above $3 billion mid-year. However, early 2023 sees a reduction in inventory levels, settling between $2.5 billion and $2.6 billion.
- Inventory Turnover
- The inventory turnover ratio fluctuates moderately across the periods. It begins at about 5.94 in early 2019 with a slight decline towards mid-2019 and an increase towards the end of 2019, reflecting improved efficiency in inventory management going into year-end. In 2020, the ratio varies between 5.55 and 7.12, indicating periods of both slower and faster inventory movement. The ratio dips somewhat in early 2021 but generally maintains an upward trend throughout the year, peaking near 6.58 by year-end. In 2022 and early 2023, inventory turnover shows modest variability, peaking above 7 in late 2022 before settling into the mid-6 range in early 2023. These variations suggest operational adjustments in inventory handling corresponding with market conditions and cost fluctuations.
Receivables Turnover
United States Steel Corp., receivables turnover calculation (quarterly data)
| Jun 30, 2023 | Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||
| Net sales | 5,008) | 4,470) | 4,338) | 5,203) | 6,290) | 5,234) | 5,622) | 5,964) | 5,025) | 3,664) | 2,562) | 2,340) | 2,091) | 2,748) | 2,824) | 3,069) | 3,545) | 3,499) | ||||||
| Receivables, less allowance | 1,864) | 1,808) | 1,635) | 2,035) | 2,602) | 2,415) | 2,089) | 2,403) | 2,010) | 1,619) | 994) | 1,099) | 939) | 1,172) | 1,177) | 1,400) | 1,638) | 1,729) | ||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||
| Receivables turnover1 | 10.20 | 11.23 | 12.88 | 10.98 | 8.88 | 9.05 | 9.71 | 7.16 | 6.76 | 6.58 | 9.80 | 9.10 | 11.43 | 10.40 | 10.99 | 9.86 | 8.83 | 8.40 | ||||||
| Benchmarks | ||||||||||||||||||||||||
| Receivables Turnover, Competitors2 | ||||||||||||||||||||||||
| Freeport-McMoRan Inc. | 32.43 | 19.02 | 17.05 | 27.47 | 24.84 | 16.00 | 19.56 | 22.75 | 17.22 | 13.02 | — | — | — | — | — | — | — | — | ||||||
Based on: 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31).
1 Q2 2023 Calculation
Receivables turnover
= (Net salesQ2 2023
+ Net salesQ1 2023
+ Net salesQ4 2022
+ Net salesQ3 2022)
÷ Receivables, less allowance
= (5,008 + 4,470 + 4,338 + 5,203)
÷ 1,864 = 10.20
2 Click competitor name to see calculations.
The financial data indicates fluctuations in net sales, receivables, and receivables turnover ratios across the observed quarters.
- Net Sales
- Net sales exhibit a cyclical trend with notable declines and recoveries. Initially, net sales decreased from approximately 3,499 million US dollars at the end of the first quarter of 2019 to a low point near 2,091 million US dollars by mid-2020, reflecting a significant downturn. Following this, a strong recovery is observed, with net sales peaking at 5,964 million US dollars in the third quarter of 2021. After this peak, net sales fluctuated but generally trended downwards to around 4,338 million US dollars by mid-2023, with slight recovery to about 5,008 million US dollars in the latest quarter reported.
- Receivables, Less Allowance
- Receivables mirrored the sales trend to some extent but with less volatility. They declined from 1,729 million US dollars in early 2019 to a low near 939 million US dollars mid-2020, coinciding with the sales dip. Subsequently, receivables increased sharply, reaching a high of approximately 2,603 million US dollars by mid-2022. From that peak, receivables decreased gradually to about 1,864 million US dollars by mid-2023.
- Receivables Turnover Ratio
- The receivables turnover ratio presented variability with values ranging between about 6.58 and 12.88 times. Early in 2019, turnover ratios ranged from 8.4 to 10.99, briefly increasing during the mid-2020 downturn, peaking at around 11.43. However, turnover decreased significantly to near 6.58 during the first quarter of 2021, indicating slower collections relative to sales. Afterward, turnover ratios rose again, peaking at nearly 12.88 by mid-2022 before moderating to just above 10 by mid-2023. This suggests that the efficiency in collecting receivables relative to sales fluctuated over the period, correlated with the changes in sales and receivables balances.
Overall, the data reflects a period of volatility influenced likely by external factors impacting demand and credit management. The trends in receivables and turnover ratios emphasize changes in collection efficiency and possibly credit terms in response to the varying sales volumes.
Payables Turnover
United States Steel Corp., payables turnover calculation (quarterly data)
Based on: 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31).
1 Q2 2023 Calculation
Payables turnover
= (Cost of salesQ2 2023
+ Cost of salesQ1 2023
+ Cost of salesQ4 2022
+ Cost of salesQ3 2022)
÷ Accounts payable and other accrued liabilities
= (4,161 + 3,953 + 3,934 + 4,359)
÷ 3,112 = 5.27
- Cost of Sales
- The cost of sales shows a fluctuating trend over the periods analyzed. It started at $3,172 million in March 2019, exhibited a downward movement through 2019 and mid-2020 reaching a low around $2,274 million in June 2020. After this trough, costs rebounded strongly, peaking at $4,661 million by June 2022. Subsequently, the cost of sales demonstrated some variability but remained elevated above $3,900 million through mid-2023. This pattern reflects an overall increase in cost levels in recent years, possibly driven by rising input prices, production volumes, or operational factors.
- Accounts Payable and Other Accrued Liabilities
- Accounts payable and related liabilities mirrored some of the fluctuations seen in the cost of sales. Starting at $2,547 million in March 2019, the figure declined through mid-2020, falling to a low around $1,459 million in June 2020. From that point, the values increased significantly, reaching a peak of $3,385 million in June 2022. After peaking, the liabilities trended slightly downward but remained above $3,000 million levels through mid-2023, indicating increased reliance on supplier credit or accrued expenses consistent with higher operational scale or cost environment.
- Payables Turnover Ratio
- The payables turnover ratio, which indicates the rate at which the company pays off its suppliers, showed substantial variation. Beginning at 4.97 in March 2019, the ratio increased during the first half of 2020, reaching a maximum of 7.24 in June 2020, suggesting quicker payments during that period likely due to reduced payables balance or strategic liquidity management. Following this peak, the turnover decreased to around 3.97 - 4.06 through early 2021, reflecting slower payments or increased balances. In subsequent periods, the ratio stabilized mostly between 4.5 and 5.5, with some upticks, indicating a return to a more normalized payment rhythm.
- Overall Insights
- The data illustrates notable volatility during the period from 2019 to mid-2023, especially around the mid-2020 timeframe, likely corresponding to external economic factors influencing cost structures and payment practices. The significant recovery and growth in cost of sales and accounts payable from mid-to-late 2020 onward suggest operational scale expansion or inflationary pressures. Meanwhile, the payables turnover ratio fluctuations indicate the company’s dynamic approach to managing supplier relationships and cash flows in response to changing financial conditions.
Working Capital Turnover
United States Steel Corp., working capital turnover calculation (quarterly data)
| Jun 30, 2023 | Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||
| Current assets | 7,835) | 7,548) | 7,866) | 8,452) | 9,035) | 8,380) | 7,152) | 6,799) | 5,638) | 4,250) | 4,432) | 4,244) | 4,924) | 4,686) | 3,813) | 4,042) | 4,547) | 4,630) | ||||||
| Less: Current liabilities | 4,072) | 4,015) | 3,959) | 4,162) | 4,568) | 4,405) | 3,852) | 4,030) | 4,451) | 3,144) | 2,656) | 2,463) | 2,141) | 2,777) | 2,625) | 2,850) | 3,223) | 3,140) | ||||||
| Working capital | 3,763) | 3,533) | 3,907) | 4,290) | 4,467) | 3,975) | 3,300) | 2,769) | 1,187) | 1,106) | 1,776) | 1,781) | 2,783) | 1,909) | 1,188) | 1,192) | 1,324) | 1,490) | ||||||
| Net sales | 5,008) | 4,470) | 4,338) | 5,203) | 6,290) | 5,234) | 5,622) | 5,964) | 5,025) | 3,664) | 2,562) | 2,340) | 2,091) | 2,748) | 2,824) | 3,069) | 3,545) | 3,499) | ||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||
| Working capital turnover1 | 5.05 | 5.75 | 5.39 | 5.21 | 5.17 | 5.50 | 6.14 | 6.22 | 11.45 | 9.64 | 5.48 | 5.62 | 3.86 | 6.38 | 10.89 | 11.58 | 10.92 | 9.75 | ||||||
| Benchmarks | ||||||||||||||||||||||||
| Working Capital Turnover, Competitors2 | ||||||||||||||||||||||||
| Freeport-McMoRan Inc. | 2.36 | 2.28 | 2.46 | 2.47 | 2.37 | 2.78 | 2.56 | 2.56 | 2.68 | 2.60 | — | — | — | — | — | — | — | — | ||||||
Based on: 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31).
1 Q2 2023 Calculation
Working capital turnover
= (Net salesQ2 2023
+ Net salesQ1 2023
+ Net salesQ4 2022
+ Net salesQ3 2022)
÷ Working capital
= (5,008 + 4,470 + 4,338 + 5,203)
÷ 3,763 = 5.05
2 Click competitor name to see calculations.
The analysis of the quarterly financial data reveals several key trends regarding working capital, net sales, and working capital turnover ratios over the observed periods.
- Working Capital
- The working capital figures exhibit notable fluctuation throughout the periods. Initially, there was a downward trend from 1490 million US$ in early 2019 to a low of 1188 million US$ by the end of 2019. Subsequently, working capital experienced a significant increase starting in the first quarter of 2020, peaking at 2783 million US$ mid-year, followed by some volatility but retaining elevated levels through 2021 and 2022. The highest working capital was recorded at 4467 million US$ in mid-2022, with a gradual decline thereafter but still maintaining a relatively high level around 3700 million US$ in mid-2023 compared to earlier years.
- Net Sales
- Net sales demonstrate a varying pattern with periods of both decline and growth. Initially, sales slightly declined from 3499 million US$ to 2824 million US$ by the end of 2019. A sharp decrease was observed in the first half of 2020, coinciding with global economic challenges, reaching 2091 million US$ in mid-2020. Following this low point, net sales recovered substantially, peaking at 6290 million US$ in mid-2022. However, after this peak, there was a notable decrease in net sales in late 2022 and early 2023, though sales remained higher than the pre-pandemic figures from 2019.
- Working Capital Turnover
- The working capital turnover ratio, which measures the efficiency in utilizing working capital to generate sales, varied inversely with the changes in working capital values. High turnover ratios near or above 10 were recorded through most of 2019, indicating efficient use of working capital. This ratio dropped markedly during 2020, corresponding with reduced sales and increased working capital, with values falling as low as 3.86. The ratio partially recovered in 2021 but remained below the high levels of 2019. From 2022 into 2023, turnover ratios stabilized between 5 and 6, reflecting a moderate level of efficiency that is lower compared to the pre-2020 period but consistent with elevated working capital levels.
Overall, the data shows a period of initial contraction in both working capital and sales in 2019 and early 2020, followed by a recovery phase through 2021 and peak performance in mid-2022. The elevated working capital levels in recent periods, combined with moderate turnover ratios, suggest a shift towards maintaining higher liquidity or inventory positions relative to sales, potentially reflecting strategic operational adjustments or market conditions.
Average Inventory Processing Period
United States Steel Corp., average inventory processing period calculation (quarterly data)
| 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 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||
| Inventory turnover | 6.46 | 6.65 | 7.11 | 6.07 | 5.39 | 5.74 | 6.58 | 6.24 | 5.98 | 5.73 | 6.82 | 7.12 | 6.46 | 5.55 | 6.77 | 6.04 | 5.90 | 5.94 | ||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||
| Average inventory processing period1 | 57 | 55 | 51 | 60 | 68 | 64 | 56 | 58 | 61 | 64 | 54 | 51 | 56 | 66 | 54 | 60 | 62 | 61 | ||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||
| Average Inventory Processing Period, Competitors2 | ||||||||||||||||||||||||
| Freeport-McMoRan Inc. | 136 | 139 | 125 | 119 | 118 | 112 | 117 | 112 | 121 | 129 | — | — | — | — | — | — | — | — | ||||||
Based on: 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31).
1 Q2 2023 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ 6.46 = 57
2 Click competitor name to see calculations.
- Inventory Turnover
- The inventory turnover ratio exhibits moderate fluctuations over the analyzed period. Initially, the ratio remained relatively stable around the range of 5.9 to 6.8 from early 2019 through the end of 2020, indicating consistent inventory efficiency during that timeframe. A noticeable dip occurred in the first quarter of 2020, with the ratio dropping to approximately 5.55, potentially reflecting inventory management challenges or reduced sales turnover during that period. Subsequently, the ratio improved substantially in late 2020, reaching a peak near 7.12 in the third quarter, suggesting enhanced inventory utilization or increased sales velocity. In 2021, the turnover ratio declined again to a range generally between 5.7 and 6.6, with another decrease becoming evident in mid-2022, hitting a low of about 5.39. However, late 2022 and early 2023 saw a recovery, with ratios rising above 6.4 to 7.1, indicating renewed inventory efficiency.
- Average Inventory Processing Period
- The average inventory processing period inversely parallels the inventory turnover, reflecting the number of days inventory is held before sale. Early in 2019, this period hovered around 60 days, decreasing to a low of 54 days by the end of that year, implying faster inventory turnover during this interval. An increase to approximately 66 days in the first quarter of 2020 suggests slower inventory movement, which could correlate with the earlier observed dip in turnover during the same period. This period shortened again toward the end of 2020, reaching approximately 51 days in the third quarter, indicating improved inventory processing speed. During 2021, the processing period generally ranged between 56 and 64 days, with a gradual increase peaking again near 68 days by mid-2022, signaling slower inventory turnover. By late 2022 and into early 2023, the average processing period decreased notably to a range of 51 to 57 days, consistent with improvements in inventory management or sales.
- Overall Interpretation
- The data reveals cyclical trends in inventory efficiency, with periods of improvement and decline over the years analyzed. Notable disruptions in inventory turnover and processing periods coincide with the early 2020 timeframe, suggestive of external factors influencing inventory management. Subsequent recovery phases indicate adaptive measures or market conditions improving inventory handling and sales. The inverse relationship between inventory turnover and average processing period is well illustrated, highlighting the dynamic nature of inventory management within the reporting periods.
Average Receivable Collection Period
United States Steel Corp., average receivable collection period calculation (quarterly data)
| 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 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||
| Receivables turnover | 10.20 | 11.23 | 12.88 | 10.98 | 8.88 | 9.05 | 9.71 | 7.16 | 6.76 | 6.58 | 9.80 | 9.10 | 11.43 | 10.40 | 10.99 | 9.86 | 8.83 | 8.40 | ||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||
| Average receivable collection period1 | 36 | 33 | 28 | 33 | 41 | 40 | 38 | 51 | 54 | 55 | 37 | 40 | 32 | 35 | 33 | 37 | 41 | 43 | ||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||
| Average Receivable Collection Period, Competitors2 | ||||||||||||||||||||||||
| Freeport-McMoRan Inc. | 11 | 19 | 21 | 13 | 15 | 23 | 19 | 16 | 21 | 28 | — | — | — | — | — | — | — | — | ||||||
Based on: 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31).
1 Q2 2023 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ 10.20 = 36
2 Click competitor name to see calculations.
- Receivables turnover
- The receivables turnover ratio exhibits notable fluctuations over the analyzed periods. Initially, there is a clear upward trend from March 2019 through December 2019, increasing from 8.4 to 10.99. This indicates improved efficiency in collecting receivables during that timeframe. In the first half of 2020, the ratio remains relatively high, peaking at 11.43 in June 2020, before declining towards the end of 2020. During 2021, the ratio notably decreases to its lowest levels observed in the dataset, with values around 6.58 to 7.16 in the early to mid-year, followed by a recovery in the latter part of the year. In 2022 and early 2023, the ratio generally trends upward again, reaching a peak of 12.88 in December 2022 before slightly declining in mid-2023. Overall, these variations suggest periods of both improving and weakening efficiency in receivables collection across the quarters.
- Average receivable collection period
- The average receivable collection period shows an inverse pattern to the receivables turnover, as expected. From March 2019 to December 2019, the collection period shortens steadily from 43 to 33 days, reflecting improved collection efficiency. In 2020, the collection period fluctuates moderately, ranging between 32 and 40 days, suggesting some variability in collections during this period. However, in 2021, the collection period extends significantly, peaking at 55 days in March and maintaining elevated levels through mid-year before shortening in the last quarter. This indicates a slowdown in collections during 2021. From 2022 into the first half of 2023, the collection period again decreases, reaching a low of 28 days in December 2022, and then slightly increases to 36 days by June 2023. This pattern aligns with the observed receivables turnover ratio, pointing to periods of both delayed and expedited cash collection from customers.
- Overall insights
- The data reflects a cyclical behavior in the company's receivables management over the analyzed quarters. Periods of high receivables turnover and shorter collection periods generally correspond with more effective credit and collection practices, while periods of reduced turnover and extended collection days suggest temporary challenges or changes in customer payment behavior. The pronounced dip in collection efficiency during 2021 is particularly notable and may require further investigation to understand underlying causes. The subsequent recovery and improvement into 2022 and 2023 imply efforts toward enhancing working capital management were likely effective. Monitoring these metrics is crucial for maintaining liquidity and optimizing cash flow.
Operating Cycle
United States Steel Corp., operating cycle calculation (quarterly data)
No. days
| 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 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||
| Average inventory processing period | 57 | 55 | 51 | 60 | 68 | 64 | 56 | 58 | 61 | 64 | 54 | 51 | 56 | 66 | 54 | 60 | 62 | 61 | ||||||
| Average receivable collection period | 36 | 33 | 28 | 33 | 41 | 40 | 38 | 51 | 54 | 55 | 37 | 40 | 32 | 35 | 33 | 37 | 41 | 43 | ||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||
| Operating cycle1 | 93 | 88 | 79 | 93 | 109 | 104 | 94 | 109 | 115 | 119 | 91 | 91 | 88 | 101 | 87 | 97 | 103 | 104 | ||||||
| Benchmarks | ||||||||||||||||||||||||
| Operating Cycle, Competitors2 | ||||||||||||||||||||||||
| Freeport-McMoRan Inc. | 147 | 158 | 146 | 132 | 133 | 135 | 136 | 128 | 142 | 157 | — | — | — | — | — | — | — | — | ||||||
Based on: 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31).
1 Q2 2023 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= 57 + 36 = 93
2 Click competitor name to see calculations.
The analysis of the quarterly financial data reveals notable fluctuations in the company's operational efficiency metrics over the observed periods.
- Average Inventory Processing Period
- This metric generally ranges between 51 and 68 days throughout the timeline. Initially, the period was around 60-62 days in early 2019, with a noticeable increase to 66 days by March 2020. Following this peak, a decreasing trend emerges toward the end of 2020, dipping to approximately 51 days. However, the inventory days rose again in early to mid-2022, reaching up to 68 days in June 2022, before decreasing once more to the mid-50s by mid-2023. These fluctuations suggest varying inventory management efficiency, with occasional periods of slower turnover and others with more effective inventory movement.
- Average Receivable Collection Period
- This period demonstrates a downtrend from the higher levels observed in the first quarter of 2021. Starting at 43 days in March 2019, the collection period decreased to the low 30s by the end of 2020. Entering 2021, the receivable days increased markedly, peaking at 55 days in March 2021. Thereafter, the collection period steadily shortened through 2022 and into 2023, reaching as low as 28 days in June 2023. Overall, this indicates phases of slower receivables collection followed by progressive improvements in cash conversion from sales.
- Operating Cycle
- The operating cycle mirrors the combined influence of the previous two periods, showing variability across the reviewed timeline. It declined from 104 days in early 2019 to a lower range around 87-91 days by the end of 2019 and 2020. However, in 2021, there is a marked increase, with the operating cycle peaking at 119 days in March 2021. Following that peak, a general downward trend is observed, with the operating cycle decreasing progressively through 2022 and 2023, reaching as low as 79 days by December 2022 and slightly rising to 93 days by June 2023. This indicates overall operational cycles becoming more efficient after 2021, reflecting enhanced management of inventory and receivables collectively.
In summary, the data points to variable operational efficiency over the periods, with 2021 representing a year of extended cycles and delays, particularly in receivables collection, whereas subsequent quarters demonstrate a trend toward improvement and shorter durations in both inventory turnover and receivables collection, leading to a more streamlined operating cycle.
Average Payables Payment Period
United States Steel Corp., average payables payment period calculation (quarterly data)
Based on: 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31).
1 Q2 2023 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ 5.27 = 69
The analysis of the payables turnover ratio over the observed quarterly periods reveals a fluctuating trend with notable cyclical behavior. Initially, the ratio remains relatively stable around 5 in early 2019. It then peaks sharply to over 7 in mid-2020, followed by a decline to just above 5 at the end of 2020. In 2021, the turnover ratio decreases further to a low near 4, before gradually increasing again through 2022 and early 2023, reaching approximately 5.3.
Correspondingly, the average payables payment period displays an inverse relationship with the turnover ratio, as expected. Starting near 73 days in early 2019, the payment period shortens to around 50 days in mid-2020, coinciding with the peak in turnover. Subsequently, the payment period expands to over 90 days in early 2021, paralleling the dip in turnover. Following this, the payment period progressively declines through 2022 and into 2023, settling near 69 days.
- Payables Turnover Ratio Trend
- Shows cyclical fluctuations between approximately 4 and 7, peaking mid-2020, dipping in 2021, and recovering by mid-2023.
- Average Payables Payment Period Trend
- Varies inversely to turnover, shortening notably in mid-2020, lengthening significantly in early 2021, then gradually shortening again through early 2023.
- Relationship Between Metrics
- The inverse correlation between payables turnover and payment period suggests effective management of payables timing, with faster turnover accompanied by shorter payment durations and vice versa.
- Possible Implications
- The peak in turnover and reduction in payment period in 2020 may indicate strategic efforts to optimize cash flow or supplier payment terms amidst challenging conditions. The extended payment period in early 2021 could reflect a shift towards conserving cash or renegotiation of payment terms.
Overall, the patterns indicate responsive payables management adapting to changing operational or market circumstances over the analyzed timeframe.
Cash Conversion Cycle
United States Steel Corp., cash conversion cycle calculation (quarterly data)
No. days
Based on: 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31).
1 Q2 2023 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= 57 + 36 – 69 = 24
The analysis of the company's quarterly financial metrics related to working capital management reveals the following trends and patterns over the observed periods:
- Average Inventory Processing Period
- The inventory processing period exhibits some fluctuation throughout the periods. It begins at 61 days and remains relatively stable around the low 60s until the end of 2019, with a notable dip to 54 days in December 2019. In 2020, the period shows a decline from 66 days in March to 51 days in September, indicating an improvement in inventory turnover, before slightly increasing again toward the end of the year. From 2021 onwards, the period varies between 51 and 68 days, with the lowest recorded in December 2022 (51 days), suggesting periodic enhancements in inventory efficiency, though there is an overall somewhat inconsistent pattern.
- Average Receivable Collection Period
- The receivable collection period shows more volatility. Starting from 43 days in March 2019, it declines steadily to 33 days in December 2019, reflecting improved collection efficiency. The period slightly increases to 40 days by March 2020 and fluctuates around mid to high 30s for the rest of 2020. Notably, in 2021, there is a marked increase, peaking at 55 days in March 2021, indicating slower collections. Afterwards, it gradually decreases to 28 days in June 2023, demonstrating a positive trend toward quicker receivable collection in recent quarters.
- Average Payables Payment Period
- The payables payment period generally trends higher in 2021, with a peak at 92 days in March 2021, which indicates slower payment to suppliers during that time. Before 2021, the period mostly ranges between 50 and 75 days with some variability. After the peak in early 2021, it gradually declines back to the high 60s by mid-2023. This movement suggests a temporary strategic extension of payables in 2021 followed by normalization in subsequent quarters.
- Cash Conversion Cycle
- The cash conversion cycle (CCC) remains relatively stable with moderate fluctuations over the observed quarters. It starts around 31 days, dips to a low of 19 days in December 2020, and remains mostly in the 20-30 day range throughout the following years. The lowest CCC is observed in December 2022 at 13 days, signaling an efficient management of working capital during that period. Despite some variation, the overall trend suggests effective control over the cycle, balancing inventory management, receivables, and payables efficiently.
In summary, the company displays a generally effective working capital management approach with periodic improvements in inventory turnover and receivable collections. The significant spike in the payables payment period during early 2021 may reflect a strategic decision to optimize cash flow. The cash conversion cycle trends confirm a proficient balance of operational liquidity, with the most efficient period noted in late 2022. Variability in these metrics indicates active management responding to changing operational or market conditions.