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: 2020-09-27), 10-Q (reporting date: 2020-06-28), 10-Q (reporting date: 2020-03-29), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-29), 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: 2018-07-01), 10-Q (reporting date: 2018-04-01), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-10-01), 10-Q (reporting date: 2017-07-02), 10-Q (reporting date: 2017-04-02), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-10-02), 10-Q (reporting date: 2016-07-03), 10-Q (reporting date: 2016-04-03).
- Inventory Turnover
- The inventory turnover ratio exhibited a marked decline from early 2016 through 2017, dropping from above 7.0 to below 5.0. Starting in 2018, the ratio stabilized somewhat between approximately 4.4 and 5.1, indicating a slower pace of inventory movement compared to earlier periods. This suggests a lengthening of the time inventory remains on hand before being sold.
- Receivables Turnover
- The receivables turnover ratio displayed a generally positive trend, beginning around 8.6 in early 2016 and rising steadily to a peak above 11 by late 2019. A slight decrease was observed in 2020 but remained near 10. This indicates improved efficiency in collecting receivables over much of the period, with some moderation during the most recent quarters.
- Payables Turnover
- Payables turnover declined noticeably from nearly 12 in early 2016 to a low near 7.7 by the end of 2017, reflecting a slower payment rate to suppliers. From 2018 onward, the ratio reversed course, increasing above 13 at one point in 2020, signaling a faster rate of payment to vendors in more recent quarters.
- Working Capital Turnover
- The working capital turnover ratio experienced significant volatility. After a peak near 18 in early 2016, it fell sharply to below 6 by late 2017. Thereafter, it fluctuated considerably—with a notable spike above 24 in mid-2019—before declining again in 2020. This variability indicates changing efficiency in utilizing working capital to generate sales, with some pronounced swings.
- Average Inventory Processing Period
- The average inventory processing period increased notably from approximately 51 days in early 2016 to an extended duration above 85 days by 2017, reflecting slower inventory turnover. While there was a gradual reduction after this peak, the period remained elevated relative to early years, maintaining around 70 to 80 days through 2020.
- Average Receivable Collection Period
- The average collection period for receivables showed a general decline from 42 days in 2016 to about 33 days by late 2019, indicating improved collection efficiency. A slight increase toward 37 days occurred in 2020, suggesting a minor easing in collection speed during this later period.
- Operating Cycle
- The operating cycle, representing the total time from inventory acquisition to cash collection, lengthened from approximately 93 days in 2016 to a peak near 130 days in 2017. Afterwards, it shortened gradually to around 104 days by late 2019 but rose again slightly in 2020, consistent with changes in inventory and receivable periods over the same timeline.
- Average Payables Payment Period
- The average payment period to suppliers lengthened from 31 days in early 2016 to nearly 47 days by the end of 2017, indicating extended payment terms or slower disbursements. From 2018 onwards, the period generally shortened, reaching as low as 27 days in mid-2020 before a slight increase, reflecting a shift toward faster payments.
- Cash Conversion Cycle
- The cash conversion cycle showed significant fluctuation. Starting around 60 days in 2016, it rose sharply to over 90 days in 2017, then declined to a low 56 days by the end of 2016 before lengthening again in subsequent years. By 2020, it stabilized near 80 days, reflecting the combined effects of longer inventory holding periods and variable collections and payment timings.
Turnover Ratios
Average No. Days
Inventory Turnover
| Sep 27, 2020 | Jun 28, 2020 | Mar 29, 2020 | Dec 31, 2019 | Sep 29, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jul 1, 2018 | Apr 1, 2018 | Dec 31, 2017 | Oct 1, 2017 | Jul 2, 2017 | Apr 2, 2017 | Dec 31, 2016 | Oct 2, 2016 | Jul 3, 2016 | Apr 3, 2016 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | |||||||||||||||||||||||||
| Cost of revenue | |||||||||||||||||||||||||
| 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: 2020-09-27), 10-Q (reporting date: 2020-06-28), 10-Q (reporting date: 2020-03-29), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-29), 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: 2018-07-01), 10-Q (reporting date: 2018-04-01), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-10-01), 10-Q (reporting date: 2017-07-02), 10-Q (reporting date: 2017-04-02), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-10-02), 10-Q (reporting date: 2016-07-03), 10-Q (reporting date: 2016-04-03).
1 Q3 2020 Calculation
Inventory turnover
= (Cost of revenueQ3 2020
+ Cost of revenueQ2 2020
+ Cost of revenueQ1 2020
+ Cost of revenueQ4 2019)
÷ Inventories
= ( + + + )
÷ =
2 Click competitor name to see calculations.
- Cost of Revenue
- The cost of revenue exhibited fluctuations over the analyzed periods. Initially, it showed moderate variations around the 6000–6600 million USD range during 2016, followed by a general upward trend starting in 2018. Notably, the cost peaked in December 2018 at 8572 million USD, indicating increased expenses associated with revenue generation. Although there was a slight decline thereafter, the cost remained elevated relative to earlier periods, suggesting growing operational costs or higher sales volume in recent quarters.
- Inventories
- Inventory levels showed a rising trend from 2016 through early 2019, initially ranging near 3500 million USD and increasing substantially to over 6500 million USD by late 2019. After this peak, inventories displayed some volatility but remained generally high, staying within the 6400 to 6800 million USD range during 2020. The increase in inventories over these years could imply accumulation of stock, possibly due to growth in production or slower inventory turnover.
- Inventory Turnover
- The inventory turnover ratio experienced a notable decline from above 7 in 2016 to around 4.2 during 2017, indicating slower movement of inventory relative to the cost of revenue. Following this drop, the ratio stabilized with minor fluctuations, hovering mostly between 4.4 and 5.1 through 2018 and 2020. The reduced and stabilized turnover suggests that inventory was being replenished less frequently relative to previous years, reflecting changes in sales pace, inventory management, or product demand.
- General Observations
- The data illustrates increasing costs and inventory levels accompanied by a declining but steady inventory turnover. This combination may indicate strategic inventory buildup, expanded production capacity, or shifts in market conditions influencing the turnover rates. The elevated cost of revenue alongside higher inventories points to potential pressures on working capital and efficiency that may warrant further operational review.
Receivables Turnover
| Sep 27, 2020 | Jun 28, 2020 | Mar 29, 2020 | Dec 31, 2019 | Sep 29, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jul 1, 2018 | Apr 1, 2018 | Dec 31, 2017 | Oct 1, 2017 | Jul 2, 2017 | Apr 2, 2017 | Dec 31, 2016 | Oct 2, 2016 | Jul 3, 2016 | Apr 3, 2016 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | |||||||||||||||||||||||||
| Revenue | |||||||||||||||||||||||||
| Accounts receivable | |||||||||||||||||||||||||
| 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: 2020-09-27), 10-Q (reporting date: 2020-06-28), 10-Q (reporting date: 2020-03-29), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-29), 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: 2018-07-01), 10-Q (reporting date: 2018-04-01), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-10-01), 10-Q (reporting date: 2017-07-02), 10-Q (reporting date: 2017-04-02), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-10-02), 10-Q (reporting date: 2016-07-03), 10-Q (reporting date: 2016-04-03).
1 Q3 2020 Calculation
Receivables turnover
= (RevenueQ3 2020
+ RevenueQ2 2020
+ RevenueQ1 2020
+ RevenueQ4 2019)
÷ Accounts receivable
= ( + + + )
÷ =
2 Click competitor name to see calculations.
- Revenue Trends
- Revenue shows a variable pattern over the observed quarters. Initially, the figures fluctuate around the 7,700 to 8,200 million USD range from early 2016 to the end of 2017, with a general pattern of slight increases followed by minor decreases. From 2018 onward, there is a marked upward trend, peaking at over 10,700 million USD in the last quarter of 2019. However, in 2020, revenue declines somewhat, with values in the high 8,700 to mid-9,400 million USD range, indicating some contraction compared to the peak in late 2019.
- Accounts Receivable Patterns
- The accounts receivable values show a relatively stable range throughout the entire period, generally fluctuating between approximately 3,300 and 3,900 million USD. There is no strong upward or downward trend overall. Minor periodic fluctuations occur without an apparent sustained increase or decrease. The consistency in accounts receivable suggests steady credit policies or collection practices despite revenue variability.
- Receivables Turnover Ratio Analysis
- The receivables turnover ratio exhibits an overall increasing trend from about 8.6 in early 2016 to a peak exceeding 11.1 in late 2019. This indicates an improvement in the efficiency of collecting receivables over time. Around 2020, the ratio slightly decreases to just under 10, though it remains higher than early period values. Higher turnover suggests that the company has become more effective in converting receivables into cash, enhancing liquidity management during most of the timeframe.
- Combined Insights
- Despite revenue fluctuations, particularly the spike in late 2019 followed by a moderate 2020 decline, accounts receivable levels remain relatively constant. This consistency, combined with improving receivables turnover ratios for most of the period, suggests better credit management and collection practices strengthening over time. The decline in turnover ratio in 2020 may reflect emerging challenges in collection efficiency possibly linked to broader economic conditions. The alignment of stable receivables with growing turnover ratios signals enhanced operational efficiency in working capital management until recent quarters.
Payables Turnover
| Sep 27, 2020 | Jun 28, 2020 | Mar 29, 2020 | Dec 31, 2019 | Sep 29, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jul 1, 2018 | Apr 1, 2018 | Dec 31, 2017 | Oct 1, 2017 | Jul 2, 2017 | Apr 2, 2017 | Dec 31, 2016 | Oct 2, 2016 | Jul 3, 2016 | Apr 3, 2016 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | |||||||||||||||||||||||||
| Cost of revenue | |||||||||||||||||||||||||
| 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: 2020-09-27), 10-Q (reporting date: 2020-06-28), 10-Q (reporting date: 2020-03-29), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-29), 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: 2018-07-01), 10-Q (reporting date: 2018-04-01), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-10-01), 10-Q (reporting date: 2017-07-02), 10-Q (reporting date: 2017-04-02), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-10-02), 10-Q (reporting date: 2016-07-03), 10-Q (reporting date: 2016-04-03).
1 Q3 2020 Calculation
Payables turnover
= (Cost of revenueQ3 2020
+ Cost of revenueQ2 2020
+ Cost of revenueQ1 2020
+ Cost of revenueQ4 2019)
÷ Accounts payable
= ( + + + )
÷ =
2 Click competitor name to see calculations.
- Cost of Revenue
- The cost of revenue experienced fluctuations throughout the observed periods, generally showing an upward trend. Initially, values hovered around the 6,000 to 6,600 million US dollar range until the close of 2016. From 2017 onwards, there was a visible increase with several notable spikes, especially in the last quarters of 2017 and 2018, reaching highs above 8,500 million US dollars. Although slight decreases occurred in early 2019, costs increased again toward the end of 2019 and into 2020, peaking around 8,800 million US dollars. This pattern suggests expanding operational scale or rising production costs over time, with some volatility evident across quarters.
- Accounts Payable
- The accounts payable balances showed a gradual overall increase over the periods analyzed. Starting from around 2,100 million US dollars in early 2016, the payable amounts grew steadily to peak near 3,200 million US dollars by the end of 2017. Thereafter, values generally ranged in the 2,800 to 3,200 million US dollar band without a clear directional trend through 2018 and 2019. In 2020, there was a decline followed by a modest recovery, with amounts fluctuating between approximately 2,300 and 2,800 million US dollars. This suggests that although the company expanded payables over time, there has been some recent contraction or tighter management of these obligations.
- Payables Turnover Ratio
- The payables turnover ratio exhibited substantial variation throughout the quarters. Early ratios in 2016 were relatively high, near 11.7 to 11.8, indicating quicker payment to suppliers. This ratio declined progressively throughout 2016 and reached a low below 8 by the end of 2017, reflecting slower payment cycles or increasing payable days. Subsequently, from early 2018 through mid-2019, the ratio generally increased, returning to and surpassing prior levels, peaking above 13 in mid-2020. The rise in turnover ratio suggests an improvement in payment efficiency or possibly favorable changes in supplier terms during that later period.
- Summary
- Overall, the financial data indicate growing cost structures alongside corresponding increases in accounts payable, with some moderation in recent quarters. The variability in the payables turnover ratio points to changing management of liabilities and payment timing, initially relaxing during periods of rising payables but later tightening significantly. These trends may reflect strategic adjustments in working capital management responding to operational demands and market conditions.
Working Capital Turnover
| Sep 27, 2020 | Jun 28, 2020 | Mar 29, 2020 | Dec 31, 2019 | Sep 29, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jul 1, 2018 | Apr 1, 2018 | Dec 31, 2017 | Oct 1, 2017 | Jul 2, 2017 | Apr 2, 2017 | Dec 31, 2016 | Oct 2, 2016 | Jul 3, 2016 | Apr 3, 2016 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | |||||||||||||||||||||||||
| Current assets | |||||||||||||||||||||||||
| Less: Current liabilities | |||||||||||||||||||||||||
| Working capital | |||||||||||||||||||||||||
| Revenue | |||||||||||||||||||||||||
| 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: 2020-09-27), 10-Q (reporting date: 2020-06-28), 10-Q (reporting date: 2020-03-29), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-29), 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: 2018-07-01), 10-Q (reporting date: 2018-04-01), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-10-01), 10-Q (reporting date: 2017-07-02), 10-Q (reporting date: 2017-04-02), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-10-02), 10-Q (reporting date: 2016-07-03), 10-Q (reporting date: 2016-04-03).
1 Q3 2020 Calculation
Working capital turnover
= (RevenueQ3 2020
+ RevenueQ2 2020
+ RevenueQ1 2020
+ RevenueQ4 2019)
÷ Working capital
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The quarterly financial data reveal several notable trends in working capital, revenue, and working capital turnover over the observed periods.
- Working Capital
- Working capital exhibits considerable fluctuations throughout the quarters. Initially, there is an upward trend from 1,765 million USD to a peak of 5,229 million USD by December 2017. Following this peak, working capital declines sharply in mid-2018, reaching a low of 1,543 million USD by June 2019. Subsequently, it recovers steadily, culminating in a significant increase to 6,301 million USD by March 2020, before falling back somewhat in the following quarters to around 4,529 and 4,745 million USD.
- Revenue
- Revenue demonstrates general growth with some variability. Starting near 7,700 million USD in early 2016, revenue experiences periodic increases, peaking at 10,778 million USD in December 2019. After this peak, revenue falls to 8,749 million USD in March 2020 but shows partial recovery by the subsequent quarters, closing near 9,400 million USD. Despite fluctuations, the overall trend supports moderate growth across the period.
- Working Capital Turnover
- The working capital turnover ratio, which measures how efficiently working capital is used to generate revenue, varies noticeably. The ratio starts high at 17.8 in early 2016, steadily decreases over subsequent quarters to a low near 5.92 in late 2017, indicating less efficient use of working capital during this period. It then rises again, peaking significantly at 24.81 in June 2019, coinciding with the period when working capital was at one of its lower points. Post-peak, turnover declines sharply to around 6.16 by March 2020, showing reduced efficiency during times of higher working capital.
Overall, the data suggest a cyclical pattern in working capital levels linked inversely to turnover efficiency. Periods of high working capital correspond to lower turnover rates, suggesting increased capital tied up in the business relative to revenue generated. Conversely, periods of lower working capital see higher turnover ratios, signaling more efficient use of available capital. Revenue growth remains generally positive but is accompanied by volatility that may reflect operational or market influences during the period.
Average Inventory Processing Period
| Sep 27, 2020 | Jun 28, 2020 | Mar 29, 2020 | Dec 31, 2019 | Sep 29, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jul 1, 2018 | Apr 1, 2018 | Dec 31, 2017 | Oct 1, 2017 | Jul 2, 2017 | Apr 2, 2017 | Dec 31, 2016 | Oct 2, 2016 | Jul 3, 2016 | Apr 3, 2016 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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: 2020-09-27), 10-Q (reporting date: 2020-06-28), 10-Q (reporting date: 2020-03-29), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-29), 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: 2018-07-01), 10-Q (reporting date: 2018-04-01), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-10-01), 10-Q (reporting date: 2017-07-02), 10-Q (reporting date: 2017-04-02), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-10-02), 10-Q (reporting date: 2016-07-03), 10-Q (reporting date: 2016-04-03).
1 Q3 2020 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =
2 Click competitor name to see calculations.
- Inventory Turnover
- The inventory turnover ratio exhibited a declining trend from early 2016 through 2017, beginning at approximately 7.2 and decreasing to around 4.3 by the end of 2017. This indicates a reduction in the frequency with which inventory was sold and replaced during this period. From 2018 onwards, the ratio showed moderate fluctuations, generally ranging between 4.4 and 5.1, suggesting some improvement in inventory efficiency but not returning to the higher turnover levels seen in 2016.
- Average Inventory Processing Period
- The average inventory processing period increased significantly between early 2016 and 2017, rising from about 51 days to a peak of 86 days. This corresponds inversely with the decline observed in inventory turnover, reflecting longer holding times for inventory. After peaking in 2017, the processing period gradually decreased and stabilized between 70 and 83 days through to late 2020, indicating a more consistent inventory management period after the initial increase.
- Overall Analysis
- The data shows a clear shift in inventory management dynamics around 2017. Initially, inventory was turned over more frequently with shorter processing periods, but this reversed, leading to longer holding times and reduced turnover. In subsequent years, there was some recovery in turnover rates and a corresponding decrease in the processing period, though levels did not return to the 2016 standards. The moderate improvements suggest ongoing efforts to optimize inventory management, but with an overall trend towards longer inventory cycles compared to earlier periods.
Average Receivable Collection Period
| Sep 27, 2020 | Jun 28, 2020 | Mar 29, 2020 | Dec 31, 2019 | Sep 29, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jul 1, 2018 | Apr 1, 2018 | Dec 31, 2017 | Oct 1, 2017 | Jul 2, 2017 | Apr 2, 2017 | Dec 31, 2016 | Oct 2, 2016 | Jul 3, 2016 | Apr 3, 2016 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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: 2020-09-27), 10-Q (reporting date: 2020-06-28), 10-Q (reporting date: 2020-03-29), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-29), 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: 2018-07-01), 10-Q (reporting date: 2018-04-01), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-10-01), 10-Q (reporting date: 2017-07-02), 10-Q (reporting date: 2017-04-02), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-10-02), 10-Q (reporting date: 2016-07-03), 10-Q (reporting date: 2016-04-03).
1 Q3 2020 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =
2 Click competitor name to see calculations.
- Receivables Turnover Ratio
- The receivables turnover ratio exhibits a generally increasing trend over the analyzed periods. Starting from 8.6 in early April 2016, the ratio fluctuates slightly but progressively rises to reach a peak of 11.17 in September 2019. After this peak, there is a slight decline, with the ratio settling near 9.89 by late September 2020. This overall increase suggests an improvement in the efficiency with which receivables are collected, indicating potentially stronger credit management or accelerated cash collections during this timeframe.
- Average Receivable Collection Period
- The average receivable collection period demonstrates a decreasing trend over the same periods. Initially, the collection period is about 42 days and remains relatively stable with minor fluctuations between 40 and 44 days until early 2018. From there, a gradual reduction occurs, reaching its shortest span of 33 days between late 2019 and mid-2020. Toward the end of the period, it rises slightly to 37 days. This downward trend complements the observed increase in receivables turnover, reflecting faster conversion of receivables into cash.
- Overall Analysis
- The concurrent increase in receivables turnover and decrease in collection period over multiple quarters indicate enhanced effectiveness in managing accounts receivable. The company appears to have accelerated its cash inflows from customers, leading to a shorter duration of outstanding receivables. Although there is a minor reversal in these trends toward the last observed quarter, the overall pattern signifies improved liquidity and operational efficiency in this segment of financial management during the period under review.
Operating Cycle
| Sep 27, 2020 | Jun 28, 2020 | Mar 29, 2020 | Dec 31, 2019 | Sep 29, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jul 1, 2018 | Apr 1, 2018 | Dec 31, 2017 | Oct 1, 2017 | Jul 2, 2017 | Apr 2, 2017 | Dec 31, 2016 | Oct 2, 2016 | Jul 3, 2016 | Apr 3, 2016 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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: 2020-09-27), 10-Q (reporting date: 2020-06-28), 10-Q (reporting date: 2020-03-29), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-29), 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: 2018-07-01), 10-Q (reporting date: 2018-04-01), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-10-01), 10-Q (reporting date: 2017-07-02), 10-Q (reporting date: 2017-04-02), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-10-02), 10-Q (reporting date: 2016-07-03), 10-Q (reporting date: 2016-04-03).
1 Q3 2020 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 demonstrated a notable increase beginning in the second quarter of the fiscal year 2017, rising from a consistent range around 51-54 days in 2016 to a peak of 86 days in mid-2017. Following this peak, the period gradually declined throughout late 2017 and 2018, fluctuating between the low 70s and mid-80s. In 2019, this trend slightly stabilized, maintaining around 73-75 days until the end of 2019. In 2020, the period exhibited moderate variability, ranging between 74 and 78 days, indicating a relatively stable but elevated inventory processing duration compared to the pre-2017 period.
- Average Receivable Collection Period
- The average receivable collection period remained relatively steady, generally fluctuating in a narrow band between 33 and 44 days over the entire observed timeframe. A minor downward trend is visible from early 2018 through 2019, with the collection period decreasing from approximately 44 days to a lower boundary near 33 days by the end of 2019. During 2020, this period showed some slight increase but remained within the same overall range, indicating consistent efficiency in receivables collection without significant deterioration or improvement.
- Operating Cycle
- The operating cycle period closely mirrors the trends observed in the inventory processing period. The cycle increased sharply from the low 90-day range in 2016 to a peak exceeding 125 days during 2017 and early 2018. From mid-2018 onward, the operating cycle length progressively contracted, showing improvement in operating efficiency, declining to approximately 104 days by the end of 2019. In the first three quarters of 2020, the operating cycle experienced some fluctuations but remained slightly above the late 2019 levels, suggesting overall stabilization with minor variation in the company’s working capital management cycle.
Average Payables Payment Period
| Sep 27, 2020 | Jun 28, 2020 | Mar 29, 2020 | Dec 31, 2019 | Sep 29, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jul 1, 2018 | Apr 1, 2018 | Dec 31, 2017 | Oct 1, 2017 | Jul 2, 2017 | Apr 2, 2017 | Dec 31, 2016 | Oct 2, 2016 | Jul 3, 2016 | Apr 3, 2016 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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: 2020-09-27), 10-Q (reporting date: 2020-06-28), 10-Q (reporting date: 2020-03-29), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-29), 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: 2018-07-01), 10-Q (reporting date: 2018-04-01), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-10-01), 10-Q (reporting date: 2017-07-02), 10-Q (reporting date: 2017-04-02), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-10-02), 10-Q (reporting date: 2016-07-03), 10-Q (reporting date: 2016-04-03).
1 Q3 2020 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ =
2 Click competitor name to see calculations.
- Payables Turnover Trend
- The payables turnover ratio exhibits a fluctuating trend over the observed periods. Initially, the ratio started at a relatively high level near 11.77 and remained stable through mid-2016. Afterwards, it declined steadily reaching a low point of approximately 7.73 in the last quarter of 2017. Following this trough, the ratio ascended gradually, recovering to around 10.35 by the first quarter of 2019, and later demonstrating a generally increasing pattern to peak at 13.39 by mid-2020 before slightly retracting to 12.16 at the end of the analyzed timeframe.
- Average Payables Payment Period Trend
- The average payables payment period shows an inverse movement relative to the payables turnover ratio. Beginning around 31 days in early 2016, the payment period gradually lengthened, peaking at approximately 47 days in the final quarter of 2017. Subsequent to this peak, the payment period shortened steadily through 2018 and into 2019, reaching a low near 33 days in mid-2019. A minor increase occurred toward the end of 2019 and early 2020, followed by further reduction to around 27 days by the third quarter of 2020, before marginally increasing to 30 days in the final recorded period.
- Relationship Between Ratios
- An inverse correlation between the payables turnover ratio and the average payables payment period is evident. When the turnover ratio declines, indicating slower payment cycles, the payment period extends, signifying more days taken to settle payables. Conversely, as the turnover ratio improves, the payment period shortens, indicating faster payment practices during those intervals.
- Overall Observations
- The data reflects dynamic management of payables over the time span. The elongation of the payment period toward late 2017 suggests a strategic stretching of payables possibly to conserve cash. Subsequently, the reduction in the payment period and increase in turnover indicates a tightening of payment schedules, perhaps reflecting improved liquidity or changes in supplier negotiation terms. The marked peak in payables turnover during mid-2020 suggests a significant acceleration in payments during that period, coupled with the shortest average payment days, which may highlight operational adjustments in response to external factors influencing cash flow management.
Cash Conversion Cycle
| Sep 27, 2020 | Jun 28, 2020 | Mar 29, 2020 | Dec 31, 2019 | Sep 29, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jul 1, 2018 | Apr 1, 2018 | Dec 31, 2017 | Oct 1, 2017 | Jul 2, 2017 | Apr 2, 2017 | Dec 31, 2016 | Oct 2, 2016 | Jul 3, 2016 | Apr 3, 2016 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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: 2020-09-27), 10-Q (reporting date: 2020-06-28), 10-Q (reporting date: 2020-03-29), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-29), 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: 2018-07-01), 10-Q (reporting date: 2018-04-01), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-10-01), 10-Q (reporting date: 2017-07-02), 10-Q (reporting date: 2017-04-02), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-10-02), 10-Q (reporting date: 2016-07-03), 10-Q (reporting date: 2016-04-03).
1 Q3 2020 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 exhibited an initial stability around 51 days through the first four quarters up to December 2016. Beginning in April 2017, there was a significant increase to 86 days, maintaining that elevated level across the middle of 2017 before gradually decreasing to 74 days by the end of 2018. In 2019 and 2020, the period fluctuated modestly around the mid-70s to high 70s range, indicating a sustained longer inventory turnover time compared to the earlier years within the dataset.
- Average Receivable Collection Period
- The average receivable collection period remained relatively consistent between 40 and 44 days throughout the observed intervals. A slight downward trend is visible starting in early 2018, reaching a low of approximately 33 days by the end of 2019 and maintaining near that level through the first three quarters of 2020. This suggests an improvement in the efficiency of receivables collection over the latter part of the timeline.
- Average Payables Payment Period
- The average payables payment period showed a gradual increase from 31 days at the start of the period in 2016 to a peak of 47 days by December 2017. Subsequently, a decline occurred throughout 2018 and 2019, dropping to the lower 30-day range by mid-2019. A slight recovery to around 30 days was noted again by the third quarter of 2020, indicating a tightening in payment terms or cash outflow management after the earlier extension.
- Cash Conversion Cycle
- The cash conversion cycle reflected the combined effect of the above components. It started around 61-62 days in 2016, rising sharply to approximately 90 days during 2017. Following this peak, there was a downward correction to about 73 days by the end of 2018. The cycle remained somewhat stable in the mid-70s range through 2019, with a noticeable increase to low 80s during mid- to late 2020. This overall pattern indicates periods of both extended and improved working capital efficiency, with a tendency towards longer cash conversion times in the latter part of the dataset.