Activity ratios measure how efficiently a company performs day-to-day tasks, such us the collection of receivables and management of inventory.
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Short-term Activity Ratios (Summary)
Based on: 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), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).
The financial ratios and periods presented reveal several notable trends in operational efficiency and liquidity management over the timeline from March 2018 to March 2023.
- Inventory Turnover
- Starting at 6.47 in March 2019, the inventory turnover ratio initially increased to a peak around mid-2020 (7.59), indicating improved efficiency in inventory management. However, from 2021 onward there is a gradual decline, falling to 4.77 by March 2023. This suggests a slowing in inventory movement, possibly due to challenges in demand or supply chain.
- Receivables Turnover
- The receivables turnover shows fluctuations around the mid-5 to 7 range. A notable peak occurred in June 2020 at 7.49, representing rapid collection of receivables during that period. Following this, the ratio stabilized mostly between 5.3 and 6.3 indicating relatively steady credit management practices with slight improvements by March 2023.
- Payables Turnover
- Payables turnover likewise peaked at 7.49 in June 2020 before steadily declining to around 5.7 by the end of the period. This trend reflects a lengthening of payment periods to suppliers or reduced turn in payable accounts, which could influence working capital management.
- Working Capital Turnover
- The working capital turnover ratio exhibited significant volatility. After an initial dip after March 2019, there was a sharp increase towards the end of 2021 and the first half of 2022, with values reaching nearly 30 in September 2022. This dramatic spike suggests marked improvement in generating sales relative to working capital, but subsequently, the ratio lowered to 13.11 by March 2023, indicating normalization or adjustment.
- Average Inventory Processing Period
- The average days inventory is held varied from 56 days in early 2019, briefly decreased to about 48-50 days around late 2020, then substantially rose to 76 days by March 2023. The increasing holding period aligns with the observed decrease in inventory turnover and may point to slower inventory movement or possible overstocking.
- Average Receivable Collection Period
- This metric showed some fluctuation, decreasing to a low of 49 days in June 2020, then generally ranging between 58 to 68 days over the remaining periods. The absence of a consistent downward trend suggests credit collection terms and effectiveness have remained relatively stable but with some variability.
- Operating Cycle
- The operating cycle ranged from about 117 days in early 2019 to a high near 135 days in the early 2022 period, reflecting a lengthening of the full cycle from inventory acquisition through receivables collection. This increase signals potential delays or inefficiencies at some stages in the operating process.
- Average Payables Payment Period
- The days payable outstanding fluctuated moderately, increasing from approximately 57 days in early 2019 to a peak around 73 days in mid-2021 and slightly declining thereafter to 64 days by March 2023. This pattern suggests a willingness to extend payment terms to suppliers, possibly to conserve cash flow.
- Cash Conversion Cycle
- The cash conversion cycle showed variability, with a decrease to 49 days during mid-2020 followed by moderate increases, reaching 70 days by the latest period. The extended cash conversion cycle towards the end of the timeline may reflect increased time to convert investments in inventory and receivables back into cash, which might impact liquidity.
Overall, the data indicate that the company experienced improvements in efficiency and cash flow management around 2020, likely influenced by external economic conditions. Post-2021 trends point towards lengthening cycles and reduced turnover ratios, suggesting challenges in inventory and receivables management that could require strategic adjustments.
Turnover Ratios
Average No. Days
Inventory Turnover
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 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data (US$ in thousands) | ||||||||||||||||||||||||||||
Cost of goods sold | ||||||||||||||||||||||||||||
Inventories | ||||||||||||||||||||||||||||
Short-term Activity Ratio | ||||||||||||||||||||||||||||
Inventory turnover1 | ||||||||||||||||||||||||||||
Benchmarks | ||||||||||||||||||||||||||||
Inventory Turnover, Competitors2 | ||||||||||||||||||||||||||||
Boeing Co. | ||||||||||||||||||||||||||||
Caterpillar Inc. | ||||||||||||||||||||||||||||
Eaton Corp. plc | ||||||||||||||||||||||||||||
GE Aerospace | ||||||||||||||||||||||||||||
Honeywell International Inc. | ||||||||||||||||||||||||||||
Lockheed Martin Corp. | ||||||||||||||||||||||||||||
RTX Corp. |
Based on: 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), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).
1 Q1 2023 Calculation
Inventory turnover
= (Cost of goods soldQ1 2023
+ Cost of goods soldQ4 2022
+ Cost of goods soldQ3 2022
+ Cost of goods soldQ2 2022)
÷ Inventories
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The cost of goods sold (COGS) exhibits a fluctuating trend over the observed periods. Initially, from March 2018 to December 2019, COGS increased, peaking in June 2019 and then decreasing somewhat by the end of that year. A significant drop is evident in the first quarter of 2020, possibly impacted by external factors affecting production or sales. Following this decline, there was a gradual increase through 2020 and 2021, reaching higher levels in the latter part of 2021. In 2022, COGS generally rose again, peaking around September, before dropping noticeably in the first quarter of 2023.
Inventories show a somewhat cyclical pattern but with an overall upward trajectory toward the end of the period. Initially, inventories slightly declined from March 2018 through the end of 2018, with some recovery in early 2019 before dipping again in late 2019. There is a more pronounced decline during 2020, reaching the lowest point at the end of that year. However, from early 2021 onwards, inventory levels steadily increased, accelerating especially in late 2022 and reaching the highest recorded level in March 2023.
The inventory turnover ratio, calculated for quarters starting in September 2018, indicates a pattern of decreasing turnover over time. The ratio peaked around December 2019 and then generally trended downward with some minor fluctuations. This suggests that the company has been turning over its inventory less frequently in recent periods, particularly evident in the final quarters of 2022 and the first quarter of 2023, where the ratio fell below 5.0, indicating slower inventory movement relative to earlier years.
- Cost of Goods Sold Analysis
-
Overall, COGS rose sharply in the first years, experienced a marked drop in early 2020, and showed a recovery trend through 2021 and 2022, but experienced another decline early in 2023. This may reflect changing demand, supply chain disruptions, or strategic changes in operations.
- Inventories Movement
-
The level of inventories decreased during periods of rising COGS until 2020, then reversed with a consistent increase post-2020, culminating in the highest inventory levels in early 2023. This increase in inventories alongside fluctuating COGS might indicate stockpiling or slower sales.
- Inventory Turnover Ratio Trends
-
The inventory turnover ratio has generally decreased since late 2019, pointing to less efficient inventory management or slower sales cycles, especially notable towards the end of the analyzed period. The declining turnover ratio along with increasing inventory levels warrants attention for potential impacts on liquidity and storage costs.
Receivables Turnover
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 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data (US$ in thousands) | ||||||||||||||||||||||||||||
Net revenues | ||||||||||||||||||||||||||||
Accounts and notes receivable, net | ||||||||||||||||||||||||||||
Short-term Activity Ratio | ||||||||||||||||||||||||||||
Receivables turnover1 | ||||||||||||||||||||||||||||
Benchmarks | ||||||||||||||||||||||||||||
Receivables Turnover, Competitors2 | ||||||||||||||||||||||||||||
Boeing Co. | ||||||||||||||||||||||||||||
Caterpillar Inc. | ||||||||||||||||||||||||||||
Eaton Corp. plc | ||||||||||||||||||||||||||||
GE Aerospace | ||||||||||||||||||||||||||||
Honeywell International Inc. | ||||||||||||||||||||||||||||
Lockheed Martin Corp. | ||||||||||||||||||||||||||||
RTX Corp. |
Based on: 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), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).
1 Q1 2023 Calculation
Receivables turnover
= (Net revenuesQ1 2023
+ Net revenuesQ4 2022
+ Net revenuesQ3 2022
+ Net revenuesQ2 2022)
÷ Accounts and notes receivable, net
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The financial data reveals several noteworthy trends in revenues, receivables, and efficiency over the analyzed periods.
- Net Revenues
- Net revenues demonstrate a general pattern of fluctuations with periods of growth and contraction. From March 2018 to December 2019, revenues show a moderate upward trend interrupted by seasonal variations, peaking in mid-2019. A significant decline is observed starting March 2020, coinciding with the early phases of the global pandemic, with revenues dropping sharply to the lowest level recorded in this dataset. Following this trough, there is a gradual recovery trajectory from mid-2020 into 2022, with a marked increase through mid-2022. The revenue levels decrease slightly again towards the first quarter of 2023, though remaining above the lowest pandemic values.
- Accounts and Notes Receivable, Net
- Outstanding receivables follow a somewhat similar cyclical and trend pattern as revenues, with levels increasing consistently until mid-2019, followed by a noticeable decline reaching their lowest in early 2020. Post the initial pandemic impact, receivables exhibit a moderate recovery and stabilization pattern, with some periodic fluctuations but remaining mostly within a consistent range. This suggests effective management of credit and collections despite external disruptions.
- Receivables Turnover Ratio
- The receivables turnover ratio, a measure of how efficiently the company collects its receivables, fluctuates between approximately 5.16 and 7.49. The highest turnover is recorded in the second quarter of 2020, indicating a strong collection performance during a challenging period. Following this peak, turnover ratios stabilize within a mid-range band (around 5.3 to 6.3), implying relatively consistent efficiency in receivables management over time, with some variations corresponding to revenue cycles.
Overall, the data indicates that while the company experienced significant external shocks affecting revenues and receivables in early 2020, it demonstrated resilience and recovery in subsequent quarters. The receivables turnover suggests continued robust credit control practices. The seasonal and cyclical nature of the figures points to recurring dynamics likely tied to market demand and operational factors.
Payables Turnover
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 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data (US$ in thousands) | ||||||||||||||||||||||||||||
Cost of goods sold | ||||||||||||||||||||||||||||
Accounts payable | ||||||||||||||||||||||||||||
Short-term Activity Ratio | ||||||||||||||||||||||||||||
Payables turnover1 | ||||||||||||||||||||||||||||
Benchmarks | ||||||||||||||||||||||||||||
Payables Turnover, Competitors2 | ||||||||||||||||||||||||||||
Boeing Co. | ||||||||||||||||||||||||||||
Caterpillar Inc. | ||||||||||||||||||||||||||||
Eaton Corp. plc | ||||||||||||||||||||||||||||
GE Aerospace | ||||||||||||||||||||||||||||
Honeywell International Inc. | ||||||||||||||||||||||||||||
Lockheed Martin Corp. | ||||||||||||||||||||||||||||
RTX Corp. |
Based on: 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), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).
1 Q1 2023 Calculation
Payables turnover
= (Cost of goods soldQ1 2023
+ Cost of goods soldQ4 2022
+ Cost of goods soldQ3 2022
+ Cost of goods soldQ2 2022)
÷ Accounts payable
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The cost of goods sold (COGS) exhibited notable fluctuations over the observed periods. Starting at approximately 2,420,200 thousand US dollars in March 2018, COGS increased to a peak near 3,094,100 thousand US dollars by June 2019. Subsequently, there was a marked decline to 1,898,800 thousand US dollars in March 2020, likely reflecting disruptions or changes in operational volume. After this drop, COGS displayed a gradual upward trend, reaching 2,927,900 thousand US dollars by September 2022 before decreasing again to 2,522,300 thousand US dollars in March 2023.
Accounts payable followed a somewhat similar but less volatile pattern. Starting at 1,666,100 thousand US dollars in March 2018, payables increased steadily to a high of 2,091,600 thousand US dollars in December 2022. A slight reduction to 1,962,600 thousand US dollars occurred in the most recent period observed, March 2023. This trend indicates growing obligations to suppliers over the long term, with minor adjustments towards the end of the timeline.
The payables turnover ratio, which measures how frequently payables are paid off during a period, varied between 5.03 and 7.49 times. The highest turnover ratio appeared in June 2020 at 7.49, suggesting quicker payment practices around that time. From mid-2019 onward, the ratio generally trended downward until December 2021, hitting a low of 5.03, signaling that payables were being settled less frequently. Slight recovery occurred thereafter, with the ratio increasing to about 5.7 by March 2023.
- Cost of Goods Sold (COGS)
- Experienced a peak in mid-2019, followed by a sharp decline in early 2020, likely influenced by external factors impacting sales or production volume, before gradually recovering through late 2022 and showing a moderate decrease entering 2023.
- Accounts Payable
- Showed a steady increase over the multi-year period with some fluctuations, indicating a growing accumulation of supplier obligations, with a minor reduction noted in the most recent quarter.
- Payables Turnover Ratio
- Displayed variability with a peak in mid-2020, followed by a decreasing trend suggesting slower payment cycles up to late 2021, then partial normalization through early 2023.
Overall, the data suggest a period of instability beginning in early 2020, with operational and payment metrics adjusting in response. The recovery trajectory in COGS and partial improvement in payables turnover imply efforts to normalize operations and payment efficiency. Monitoring these metrics moving forward will provide insight into the company's ongoing operational resilience and supplier relationship management.
Working Capital Turnover
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 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data (US$ in thousands) | ||||||||||||||||||||||||||||
Current assets | ||||||||||||||||||||||||||||
Less: Current liabilities | ||||||||||||||||||||||||||||
Working capital | ||||||||||||||||||||||||||||
Net revenues | ||||||||||||||||||||||||||||
Short-term Activity Ratio | ||||||||||||||||||||||||||||
Working capital turnover1 | ||||||||||||||||||||||||||||
Benchmarks | ||||||||||||||||||||||||||||
Working Capital Turnover, Competitors2 | ||||||||||||||||||||||||||||
Boeing Co. | ||||||||||||||||||||||||||||
Caterpillar Inc. | ||||||||||||||||||||||||||||
Eaton Corp. plc | ||||||||||||||||||||||||||||
GE Aerospace | ||||||||||||||||||||||||||||
Honeywell International Inc. | ||||||||||||||||||||||||||||
Lockheed Martin Corp. | ||||||||||||||||||||||||||||
RTX Corp. |
Based on: 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), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).
1 Q1 2023 Calculation
Working capital turnover
= (Net revenuesQ1 2023
+ Net revenuesQ4 2022
+ Net revenuesQ3 2022
+ Net revenuesQ2 2022)
÷ Working capital
= ( + + + )
÷ =
2 Click competitor name to see calculations.
- Working Capital
- The working capital values demonstrate a fluctuating trend over the examined period. Initially, the working capital decreased from about 1,750,800 thousand USD in March 2018 to 1,419,300 thousand USD in December 2018. This was followed by a significant increase reaching a peak of approximately 2,596,200 thousand USD in March 2019. Subsequently, working capital values generally declined with intermittent increases, dropping notably in the latter part of the period, reaching lows around 494,900 thousand USD in September 2022 before slightly recovering to 1,243,400 thousand USD by March 2023.
- Net Revenues
- Net revenues exhibit a similar pattern of volatility but with some distinct fluctuations. Revenues started at 3,384,500 thousand USD in March 2018 and showed a general rising trend through 2019, peaking several times above 4,500,000 thousand USD in mid-2018 and 2019. There was a marked decline during 2020, corresponding to the early impacts of global economic disruptions, with the lowest point in March 2020 at 2,641,300 thousand USD. Recovery trends are visible thereafter, with revenues increasing again to peaks above 4,300,000 thousand USD in mid to late 2022. The most recent quarter in March 2023 showed a modest decline to 3,665,800 thousand USD.
- Working Capital Turnover
- The working capital turnover ratio, available from 2019 onwards, indicates significant variability. The ratio started very high at 11.06 in March 2019, followed by fluctuations ranging mostly between 4.79 and 13.69 throughout 2019 and 2020. From 2021 to early 2022, the ratio hovered steadily around values between 4.85 and 10.08, which suggests a relatively stable operational efficiency in managing working capital against net revenues during that period. However, a dramatic increase occurred in late 2022, with the ratio reaching extremely high levels of 29.98 in September and remaining elevated above 20 until the end of the year before dropping back to 13.11 in March 2023. This sharp spike points to an unusual efficiency or a significant decrease in working capital relative to revenues during that time, possibly due to liquidity management, inventory reductions, or changes in payables and receivables.
- Summary of Trends and Insights
- The data reveals a pattern of cyclicality and volatility in both working capital and net revenues, typical of businesses exposed to seasonal factors or market fluctuations. The sharp reduction in working capital during 2022 accompanied by very high working capital turnover ratios suggests the company managed its liquidity more aggressively during this period, potentially to cope with external economic pressures or operational shifts. The net revenues, while resilient, show susceptibility to downturns similar to those seen during global economic slowdowns in 2020. The recovering trend in revenues in late 2022 and early 2023 signifies potential stabilization or growth pickup. Overall, the financial data points to active management of working capital resources to maintain operational efficiency amidst fluctuating revenue streams, with periodic stresses reflected in the financial ratios and absolute values.
Average Inventory Processing Period
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 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data | ||||||||||||||||||||||||||||
Inventory turnover | ||||||||||||||||||||||||||||
Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||
Average inventory processing period1 | ||||||||||||||||||||||||||||
Benchmarks (no. days) | ||||||||||||||||||||||||||||
Average Inventory Processing Period, Competitors2 | ||||||||||||||||||||||||||||
Boeing Co. | ||||||||||||||||||||||||||||
Caterpillar Inc. | ||||||||||||||||||||||||||||
Eaton Corp. plc | ||||||||||||||||||||||||||||
GE Aerospace | ||||||||||||||||||||||||||||
Honeywell International Inc. | ||||||||||||||||||||||||||||
Lockheed Martin Corp. | ||||||||||||||||||||||||||||
RTX Corp. |
Based on: 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), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).
1 Q1 2023 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =
2 Click competitor name to see calculations.
The analysis of inventory management metrics over the reported periods reveals notable fluctuations and trends in operational efficiency.
- Inventory Turnover Ratio
- The inventory turnover ratio shows an upward trend starting from March 31, 2019, where it was 6.47, reaching a peak of 7.59 by December 31, 2020. This indicates an improvement in the speed at which inventory is sold and replaced during that period. Following this peak, the turnover ratio declines steadily, falling to 4.77 by March 31, 2023. This reduction suggests a slower movement of inventory in the most recent periods, which may point to changes in demand, inventory management strategies, or supply chain factors impacting efficiency.
- Average Inventory Processing Period (Number of Days)
- The average inventory processing period, which inversely relates to the inventory turnover ratio, shows an initial decrease from 66 days in June 2019 to 48 days by December 2020, reflecting faster inventory turnover and improved management. However, after this period, the processing time begins to lengthen, increasing from 50 days in March 2021 to 76 days by March 31, 2023. The extended processing period aligns with the decline in inventory turnover ratio, reinforcing the observation of slower inventory movement in recent quarters.
In summary, the data indicates that inventory management was more efficient around the 2019 to 2020 timeframe, with higher turnover ratios and shorter processing periods. However, starting in early 2021, these metrics deteriorate, pointing to potential challenges in inventory handling, slower sales cycles, or external factors affecting inventory levels. This change warrants further investigation to identify underlying causes and to assess possible operational adjustments to enhance inventory efficiency going forward.
Average Receivable Collection Period
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 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data | ||||||||||||||||||||||||||||
Receivables turnover | ||||||||||||||||||||||||||||
Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||
Average receivable collection period1 | ||||||||||||||||||||||||||||
Benchmarks (no. days) | ||||||||||||||||||||||||||||
Average Receivable Collection Period, Competitors2 | ||||||||||||||||||||||||||||
Boeing Co. | ||||||||||||||||||||||||||||
Caterpillar Inc. | ||||||||||||||||||||||||||||
Eaton Corp. plc | ||||||||||||||||||||||||||||
GE Aerospace | ||||||||||||||||||||||||||||
Honeywell International Inc. | ||||||||||||||||||||||||||||
Lockheed Martin Corp. | ||||||||||||||||||||||||||||
RTX Corp. |
Based on: 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), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).
1 Q1 2023 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =
2 Click competitor name to see calculations.
- Receivables Turnover Ratio
- The receivables turnover ratio shows moderate fluctuations over the observed periods starting from March 31, 2019. Initially, the ratio decreased from 5.85 to 5.16 by September 30, 2019, indicating a slight decline in the efficiency of collecting receivables. This was followed by a recovery to 5.5 by December 31, 2019. A notable peak is observed in the second quarter of 2020, reaching 7.49, suggesting an improvement in collection efficiency during that time. Subsequently, the ratio generally declined, hovering around mid-5s with some volatility and ending at 6.26 in the first quarter of 2023. Overall, the turnover ratio reflects some variability but tends to stabilize near 5.5 to 6.0 in recent quarters.
- Average Receivable Collection Period
- The average receivable collection period exhibits an inverse relationship to the receivables turnover ratio, as expected. Starting at 62 days in early 2019, the collection period increased to 71 days by September 2019, indicating slower collections. It then improved, dropping to 49 days in the second quarter of 2020, congruent with the peak in turnover ratio during the same period. Afterward, the collection period fluctuated between approximately 58 and 68 days through 2021 to early 2023, showing periods of both slight elongation and contraction. The most recent data point shows a collection period of 58 days, reflecting an improvement in efficiency compared to some previous quarters.
- Summary of Trends and Insights
- The data points to a generally stable yet moderately fluctuating efficiency in receivables management over the observed period. The peak in collection efficiency during mid-2020 likely reflects operational adjustments or external factors affecting receivables turnover during that time. The subsequent stabilization suggests consistent management practices, with some variability possibly related to seasonal or market factors. The collection period's range of roughly 58 to 68 days indicates that the company typically collects receivables within two months, with occasional deviations. This pattern suggests a focus on maintaining steady cash flow through relatively consistent receivable collection efforts.
Operating Cycle
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 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | ||||||||
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Selected Financial Data | ||||||||||||||||||||||||||||
Average inventory processing period | ||||||||||||||||||||||||||||
Average receivable collection period | ||||||||||||||||||||||||||||
Short-term Activity Ratio | ||||||||||||||||||||||||||||
Operating cycle1 | ||||||||||||||||||||||||||||
Benchmarks | ||||||||||||||||||||||||||||
Operating Cycle, Competitors2 | ||||||||||||||||||||||||||||
Boeing Co. | ||||||||||||||||||||||||||||
Caterpillar Inc. | ||||||||||||||||||||||||||||
Eaton Corp. plc | ||||||||||||||||||||||||||||
GE Aerospace | ||||||||||||||||||||||||||||
Honeywell International Inc. | ||||||||||||||||||||||||||||
Lockheed Martin Corp. | ||||||||||||||||||||||||||||
RTX Corp. |
Based on: 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), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).
1 Q1 2023 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= + =
2 Click competitor name to see calculations.
- Average Inventory Processing Period
- The average inventory processing period exhibits fluctuations over the analyzed quarters. Starting at 56 days in March 2019, the period increased to a peak of 66 days by June 2019, before gradually decreasing to a low of 48 days in December 2020. Subsequently, a rising trend is apparent with values reaching 58 days in December 2021, followed by a further increase to 76 days by March 2023. This indicates variability in inventory turnover efficiency, with more recent quarters reflecting longer inventory holding periods, suggesting potential challenges in inventory management or changes in inventory strategy.
- Average Receivable Collection Period
- The receivable collection period shows a relatively stable but somewhat inconsistent pattern. Starting at 62 days in March 2019, the period slightly increased to 71 days in September 2019 and then fluctuated around the low 60s to high 60s throughout 2020 and 2021. From March 2022 onwards, figures generally range between 58 and 68 days, with a slight decreasing trend observable by March 2023 at 58 days. This trend suggests moderate improvement in receivables collection efficiency in the most recent period compared to earlier years.
- Operating Cycle
- The operating cycle, representing the sum of the average inventory processing period and average receivable collection period, demonstrates a rising and fluctuating trend. From 118 days in March 2019, the cycle increased to 135 days by September 2019, declined to a low of 98 days in June 2020, then progressively increased again, peaking at 135 days around September 2022. The cycle remains elevated at 134 days as of March 2023. This suggests that the overall working capital conversion process has lengthened over time, primarily driven by the increases in inventory processing period despite some improvements in receivable collection.
Average Payables Payment Period
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 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | ||||||||
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Selected Financial Data | ||||||||||||||||||||||||||||
Payables turnover | ||||||||||||||||||||||||||||
Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||
Average payables payment period1 | ||||||||||||||||||||||||||||
Benchmarks (no. days) | ||||||||||||||||||||||||||||
Average Payables Payment Period, Competitors2 | ||||||||||||||||||||||||||||
Boeing Co. | ||||||||||||||||||||||||||||
Caterpillar Inc. | ||||||||||||||||||||||||||||
Eaton Corp. plc | ||||||||||||||||||||||||||||
GE Aerospace | ||||||||||||||||||||||||||||
Honeywell International Inc. | ||||||||||||||||||||||||||||
Lockheed Martin Corp. | ||||||||||||||||||||||||||||
RTX Corp. |
Based on: 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), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).
1 Q1 2023 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ =
2 Click competitor name to see calculations.
The analysis of the payables turnover ratio and the average payables payment period over the reported periods reveals distinct trends and fluctuations.
- Payables Turnover Ratio
- Beginning from the first recorded figure in March 2019 at 6.36, the ratio experienced a gradual decrease until September 2021, reaching a low of 5.03. This decline suggests a slowing rate in the frequency of payables cycles during this timeframe. However, from this point onward, the ratio showed signs of recovery, increasing to 5.7 by March 2023, indicating an improved speed in settling payables.
- Average Payables Payment Period (number of days)
- Corresponding with the inverse nature of the payables turnover, the average payables payment period increased from 57 days in March 2019 to a peak of 73 days in September 2021, implying that the company took longer to pay its suppliers during this period. Following this peak, a reduction trend is observed, declining to 64 days by March 2023, reflecting a shortened payment cycle and potentially better liquidity management or changes in payment policy.
- Overall Observations
- These patterns demonstrate a period of extended payment terms or slower payment execution between mid-2019 and late 2021, followed by a reversal toward quicker payments in the most recent quarters. Such shifts might be related to changes in working capital strategies, supplier agreements, or overall financial conditions influencing payment behaviors.
Cash Conversion Cycle
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 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data | ||||||||||||||||||||||||||||
Average inventory processing period | ||||||||||||||||||||||||||||
Average receivable collection period | ||||||||||||||||||||||||||||
Average payables payment period | ||||||||||||||||||||||||||||
Short-term Activity Ratio | ||||||||||||||||||||||||||||
Cash conversion cycle1 | ||||||||||||||||||||||||||||
Benchmarks | ||||||||||||||||||||||||||||
Cash Conversion Cycle, Competitors2 | ||||||||||||||||||||||||||||
Boeing Co. | ||||||||||||||||||||||||||||
Caterpillar Inc. | ||||||||||||||||||||||||||||
Eaton Corp. plc | ||||||||||||||||||||||||||||
GE Aerospace | ||||||||||||||||||||||||||||
Honeywell International Inc. | ||||||||||||||||||||||||||||
Lockheed Martin Corp. | ||||||||||||||||||||||||||||
RTX Corp. |
Based on: 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), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).
1 Q1 2023 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= + – =
2 Click competitor name to see calculations.
- Average Inventory Processing Period
- The average inventory processing period shows moderate fluctuations throughout the observed quarters. Starting at 56 days in early 2019, it rises to a peak of 66 days by mid-2019 before gradually declining to around 48-50 days in late 2020. Subsequently, the period increases again, reaching higher levels of approximately 67-69 days during 2022, and peaks at 76 days in the first quarter of 2023. This indicates variability in inventory turnover efficiency, with recent quarters reflecting slower inventory processing times.
- Average Receivable Collection Period
- The receivable collection period demonstrates some volatility but remains generally within the range of late 40s to high 60s in days. It starts around the low 60s in early 2019, fluctuates upward reaching highs around 71 days in late 2019, and then decreases to approximately 49 days during the mid-2020 period. From late 2020 through 2022, it stabilizes mostly between 60 and 68 days, with a slight decline to 58 days by the first quarter of 2023, suggesting a gradual improvement in collections towards the end of the period analyzed.
- Average Payables Payment Period
- The payables payment period exhibits an upward trend for much of the period under review. Beginning near the upper 50s in early 2019, it climbs steadily to reach peak values in the low 70s days during 2021 and 2022. This trend indicates the company is extending the time it takes to settle payables, possibly to optimize cash management. A slight decrease is observed in the first quarter of 2023, reducing the period back to 64 days.
- Cash Conversion Cycle
- The cash conversion cycle follows a generally stable but somewhat fluctuating pattern. From around 61 days in early 2019, it peaks at 73 days in late 2019, declines through 2020 to low 50s days, and then maintains near 50-55 days through most of 2021. In 2022, it begins to rise again, reaching mid-60s to 70 days by early 2023. This indicates periods where the net operating cycle either lengthened or shortened, reflecting variations in working capital management. The recent increase suggests a longer cash cycle, possibly driven by slower inventory processing and longer receivables or payment terms adjustments.