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)
Based on: 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), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-27), 10-Q (reporting date: 2015-06-28), 10-Q (reporting date: 2015-03-29).
- Inventory Turnover
- The inventory turnover ratio exhibited fluctuations over the observed periods, starting from 27.68 and varying between approximately 21.83 and 32.11. There was a notable peak around early 2017 and late 2019, reaching above 30, while several quarters exhibited a downward trend closer to the lower twenties. This indicates variability in how efficiently inventory was managed, with periods of both heightened and reduced turnover speed.
- Receivables Turnover
- The receivables turnover ratio, available from early 2017 onward, showed variation between 15.63 and 21.39. The ratio demonstrated some volatility with intermittent dips around mid-2017 and early 2018 and a general rising tendency towards late 2019, peaking at 21.39. This suggests some inconsistency in credit collection efficiency but with improvement over the longer term.
- Payables Turnover
- The payables turnover ratio moved between 9.97 and 15.2 throughout the periods reported. A relatively stable range was observed around 12 to 15, except for one notable dip near the end of 2018 where the ratio fell below 10. This points to generally consistent payment practices, albeit with occasional extension or delay in payments.
- Working Capital Turnover
- Working capital turnover fluctuated between 5.64 and 8.87, exhibiting an upward trend overall, particularly evident towards the end of the data set where higher ratios above 7.5 were noted. The highest values appeared in the final quarters observed, indicating potentially more efficient use of working capital to generate revenue.
- Average Inventory Processing Period
- The average inventory processing period mostly ranged from 11 to 17 days, with intermittent rises and falls. The shortest periods appeared in early 2017 and late 2019 at around 11 days, while the longest durations were found in mid-2019 with values of up to 17 days. Despite some fluctuations, inventory was generally processed in about two weeks’ time, reflecting a relatively consistent inventory management cycle.
- Average Receivable Collection Period
- The average receivable collection period varied mainly between 17 and 23 days from early 2017 onward. Slight increases and decreases were noted but the period generally remained stable near the lower twenties, suggesting steady efficiency in collecting payments from customers.
- Operating Cycle
- The operating cycle remained mostly stable in the 28 to 38 days range, with a slight contraction observed towards the end of the reporting periods. This slight reduction in cycle length could imply an increase in overall operational efficiency, reducing the time cash is tied up in operations.
- Average Payables Payment Period
- The average payables payment period oscillated between 24 and 37 days. Periods of shorter payment durations around 24-26 days alternate with longer stretches closer to one month or more, including a peak at 37 days in early 2019. This implies some variability in the timing of payments to suppliers, which could affect working capital management.
- Cash Conversion Cycle
- The cash conversion cycle showed significant volatility, ranging from -3 to 13 days. There were instances of negative values towards the end of 2017 and again in late 2018, indicating periods where payables were managed so efficiently that cash was collected before paying suppliers. Positive peaks around 13 days highlight times when cash was tied up longer in operations. Overall, the cash conversion cycle indicates moderate effectiveness in converting resources into cash throughout the periods, with room for improvement.
Turnover Ratios
Average No. Days
Inventory Turnover
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 | Dec 31, 2015 | Sep 27, 2015 | Jun 28, 2015 | Mar 29, 2015 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||
Cost of sales, products and services | 5,832) | 5,499) | 5,205) | 4,877) | 5,393) | 4,871) | 4,777) | 4,532) | 5,171) | 4,690) | 4,685) | 4,530) | 4,655) | 4,512) | 4,380) | 4,400) | 4,808) | 4,408) | 4,525) | 3,833) | ||||||
Inventories | 671) | 802) | 932) | 882) | 758) | 804) | 725) | 640) | 594) | 693) | 581) | 599) | 659) | 651) | 671) | 637) | 635) | 619) | 519) | 506) | ||||||
Short-term Activity Ratio | ||||||||||||||||||||||||||
Inventory turnover1 | 31.91 | 26.15 | 21.83 | 22.58 | 25.82 | 24.07 | 26.44 | 29.81 | 32.11 | 26.78 | 31.64 | 30.18 | 27.23 | 27.80 | 26.82 | 28.48 | 27.68 | — | — | — | ||||||
Benchmarks | ||||||||||||||||||||||||||
Inventory Turnover, Competitors2 | ||||||||||||||||||||||||||
Boeing Co. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Caterpillar Inc. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Eaton Corp. plc | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
GE Aerospace | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Honeywell International Inc. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Lockheed Martin Corp. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
RTX Corp. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
Based on: 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), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-27), 10-Q (reporting date: 2015-06-28), 10-Q (reporting date: 2015-03-29).
1 Q4 2019 Calculation
Inventory turnover
= (Cost of sales, products and servicesQ4 2019
+ Cost of sales, products and servicesQ3 2019
+ Cost of sales, products and servicesQ2 2019
+ Cost of sales, products and servicesQ1 2019)
÷ Inventories
= (5,832 + 5,499 + 5,205 + 4,877)
÷ 671 = 31.91
2 Click competitor name to see calculations.
- Cost of Sales, Products and Services
- The cost of sales shows a generally increasing trend over the analyzed periods. Starting from 3,833 million USD in March 2015, this figure rises with some fluctuation to reach 5,832 million USD by the end of December 2019. Notable increases occur towards the end of 2017 and throughout 2018 and 2019, which may indicate expanded operations, rising production costs, or increased sales volume.
- Inventories
- The inventory levels also exhibit an overall upward trend with some variability across quarters. From 506 million USD in March 2015, inventories grow, peaking at 932 million USD in June 2019 before decreasing to 671 million USD by December 2019. This pattern suggests periods of inventory buildup possibly in anticipation of higher sales demand, followed by inventory reduction phases.
- Inventory Turnover Ratio
- The inventory turnover ratio fluctuates considerably throughout the reporting periods, with values generally ranging between approximately 21.8 and 32.1. Higher turnover ratios in certain quarters, such as in July 2017 (32.11) and December 2019 (31.91), indicate improved efficiency in managing inventory relative to cost of sales during those times. Conversely, lower ratios observed around mid-2019 indicate slower inventory movement. Overall, the fluctuations reflect varying inventory management effectiveness and possibly changing sales dynamics.
- Summary
- The financial data depict a company experiencing growth in cost of sales alongside increased inventory holdings. The inventory turnover ratio variability points to inconsistent inventory management efficiency, with periods of both strong and weaker turnover performance. The rising cost of sales combined with fluctuating inventory levels and turnover suggest an adaptive operational environment, possibly responding to market demand changes, production scale fluctuations, or supply chain considerations over the reviewed quarters.
Receivables Turnover
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 | Dec 31, 2015 | Sep 27, 2015 | Jun 28, 2015 | Mar 29, 2015 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||
Net sales | 7,842) | 7,446) | 7,159) | 6,729) | 7,360) | 6,806) | 6,625) | 6,267) | 6,783) | 6,284) | 6,281) | 6,000) | 6,238) | 6,033) | 6,035) | 5,763) | 6,328) | 5,783) | 5,848) | 5,288) | ||||||
Receivables, net | 1,364) | 1,473) | 1,607) | 1,424) | 1,648) | 1,527) | 1,317) | 1,639) | 1,324) | 1,393) | 1,560) | 1,319) | —) | —) | —) | —) | —) | —) | —) | —) | ||||||
Short-term Activity Ratio | ||||||||||||||||||||||||||
Receivables turnover1 | 21.39 | 19.48 | 17.46 | 19.33 | 16.42 | 17.34 | 19.71 | 15.63 | 19.15 | 17.81 | 15.74 | 18.43 | — | — | — | — | — | — | — | — | ||||||
Benchmarks | ||||||||||||||||||||||||||
Receivables Turnover, Competitors2 | ||||||||||||||||||||||||||
Boeing Co. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Caterpillar Inc. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Eaton Corp. plc | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
GE Aerospace | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Honeywell International Inc. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Lockheed Martin Corp. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
RTX Corp. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
Based on: 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), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-27), 10-Q (reporting date: 2015-06-28), 10-Q (reporting date: 2015-03-29).
1 Q4 2019 Calculation
Receivables turnover
= (Net salesQ4 2019
+ Net salesQ3 2019
+ Net salesQ2 2019
+ Net salesQ1 2019)
÷ Receivables, net
= (7,842 + 7,446 + 7,159 + 6,729)
÷ 1,364 = 21.39
2 Click competitor name to see calculations.
Over the observed periods, net sales exhibit a generally upward trend with fluctuations across quarters. Starting at 5,288 million US dollars in March 2015, net sales increase to 7,842 million US dollars by December 2019. Despite some intermittent declines, such as from December 2015 to April 2016 and April 2017 to April 2018, the overall trajectory is positive, indicating growth in revenue generation over the nearly five-year span.
Regarding net receivables, data is available from the April 2017 quarter onwards. Receivables values fluctuate between approximately 1,317 million and 1,648 million US dollars during this timeframe. There is no clear trend of consistent increase or decrease, as the figures oscillate within this range, suggesting stability in the company's accounts receivable balances with minor variations quarter to quarter.
The receivables turnover ratio, also available starting in April 2017, reflects the efficiency with which the company collects its receivables. Values vary between 15.63 and 21.39, showing some volatility. Higher turnover ratios are generally observed at the end of the years 2017 and 2019, indicating more effective collection periods in those quarters. The fluctuations suggest variability in collection efficiency, but with a tendency towards improvement by the final quarter recorded, as evidenced by the highest turnover ratio in December 2019.
Overall, the data depicts a company with growing sales revenue, stable accounts receivable levels in recent periods, and a generally improving trend in receivables turnover, suggesting enhanced collection management toward the end of the reported period.
- Net Sales
- Demonstrates a growing trajectory from 5,288 million US dollars to 7,842 million US dollars over the analysis period, with some seasonal or cyclical fluctuations.
- Receivables, Net
- Remain relatively stable between 1,317 million and 1,648 million US dollars since first reported, without a clear upward or downward trend.
- Receivables Turnover
- Varies between 15.63 and 21.39, indicating fluctuations in collection efficiency; highest ratios observed in late 2017 and late 2019 suggest periods of improved receivables management.
Payables Turnover
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 | Dec 31, 2015 | Sep 27, 2015 | Jun 28, 2015 | Mar 29, 2015 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||
Cost of sales, products and services | 5,832) | 5,499) | 5,205) | 4,877) | 5,393) | 4,871) | 4,777) | 4,532) | 5,171) | 4,690) | 4,685) | 4,530) | 4,655) | 4,512) | 4,380) | 4,400) | 4,808) | 4,408) | 4,525) | 3,833) | ||||||
Accounts payable | 1,796) | 1,470) | 1,368) | 1,361) | 1,964) | 1,392) | 1,380) | 1,255) | 1,519) | 1,347) | 1,278) | 1,282) | 1,520) | 1,415) | 1,405) | 1,304) | 1,402) | 1,334) | 1,171) | 1,141) | ||||||
Short-term Activity Ratio | ||||||||||||||||||||||||||
Payables turnover1 | 11.92 | 14.27 | 14.87 | 14.63 | 9.97 | 13.90 | 13.89 | 15.20 | 12.56 | 13.78 | 14.38 | 14.10 | 11.81 | 12.79 | 12.81 | 13.91 | 12.53 | — | — | — | ||||||
Benchmarks | ||||||||||||||||||||||||||
Payables Turnover, Competitors2 | ||||||||||||||||||||||||||
Boeing Co. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Caterpillar Inc. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Eaton Corp. plc | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
GE Aerospace | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Honeywell International Inc. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Lockheed Martin Corp. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
RTX Corp. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
Based on: 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), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-27), 10-Q (reporting date: 2015-06-28), 10-Q (reporting date: 2015-03-29).
1 Q4 2019 Calculation
Payables turnover
= (Cost of sales, products and servicesQ4 2019
+ Cost of sales, products and servicesQ3 2019
+ Cost of sales, products and servicesQ2 2019
+ Cost of sales, products and servicesQ1 2019)
÷ Accounts payable
= (5,832 + 5,499 + 5,205 + 4,877)
÷ 1,796 = 11.92
2 Click competitor name to see calculations.
- Cost of Sales, Products and Services
- The cost of sales exhibits a generally increasing trend over the observed periods. Starting from 3,833 million USD in March 2015, the cost rose steadily with some fluctuations, reaching a peak of 5,832 million USD by December 2019. This represents an overall growth with notable increases in the latter quarters of 2018 and throughout 2019, indicating either higher sales volume, increased input costs, or both. Despite some minor downward adjustments, the upward momentum is predominant.
- Accounts Payable
- Accounts payable amounts show variability but an overall upward tendency during the period. Beginning around 1,141 million USD in the first quarter of 2015, the payable balance experienced fluctuations with occasional dips, such as in April 2017 and April 2018. However, the balance surged significantly to reach 1,964 million USD by the first quarter of 2019, before settling around 1,796 million USD at the end of 2019. The variability may suggest changing payment policies or timing differences in supplier payments that correlate with the changes in cost of sales.
- Payables Turnover Ratio
- The payables turnover ratio demonstrates notable volatility over the quarters analyzed. Starting at 12.53 in April 2016, it experienced increases and decreases with the highest turnover recorded at 15.2 in April 2018. The ratio then declined sharply to 9.97 by December 2018 before fluctuating back above 11 towards the end of 2019. This variation indicates shifts in the company's payment pace to suppliers, where high ratios suggest faster payment and lower ratios suggest slower payment relative to the credit purchases. The drop towards the end of 2018 could reflect a strategic adjustment in accounts payable management or cash flow considerations.
Working Capital Turnover
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 | Dec 31, 2015 | Sep 27, 2015 | Jun 28, 2015 | Mar 29, 2015 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||
Current assets | 13,082) | 12,029) | 11,526) | 10,956) | 12,136) | 10,635) | 11,315) | 10,960) | 11,326) | 10,778) | 10,937) | 10,515) | 10,678) | 10,155) | 9,850) | 9,359) | 9,812) | 9,528) | 8,704) | 10,241) | ||||||
Less: Current liabilities | 9,791) | 7,815) | 7,871) | 7,680) | 8,288) | 7,156) | 7,017) | 6,779) | 7,348) | 6,492) | 6,587) | 6,307) | 6,427) | 6,001) | 6,014) | 5,749) | 6,126) | 6,328) | 5,641) | 5,635) | ||||||
Working capital | 3,291) | 4,214) | 3,655) | 3,276) | 3,848) | 3,479) | 4,298) | 4,181) | 3,978) | 4,286) | 4,350) | 4,208) | 4,251) | 4,154) | 3,836) | 3,610) | 3,686) | 3,200) | 3,063) | 4,606) | ||||||
Net sales | 7,842) | 7,446) | 7,159) | 6,729) | 7,360) | 6,806) | 6,625) | 6,267) | 6,783) | 6,284) | 6,281) | 6,000) | 6,238) | 6,033) | 6,035) | 5,763) | 6,328) | 5,783) | 5,848) | 5,288) | ||||||
Short-term Activity Ratio | ||||||||||||||||||||||||||
Working capital turnover1 | 8.87 | 6.81 | 7.68 | 8.40 | 7.03 | 7.61 | 6.04 | 6.13 | 6.37 | 5.79 | 5.64 | 5.78 | 5.66 | 5.82 | 6.23 | 6.57 | 6.31 | — | — | — | ||||||
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-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), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-27), 10-Q (reporting date: 2015-06-28), 10-Q (reporting date: 2015-03-29).
1 Q4 2019 Calculation
Working capital turnover
= (Net salesQ4 2019
+ Net salesQ3 2019
+ Net salesQ2 2019
+ Net salesQ1 2019)
÷ Working capital
= (7,842 + 7,446 + 7,159 + 6,729)
÷ 3,291 = 8.87
2 Click competitor name to see calculations.
The analysis of the quarterly financial data reveals several notable trends and insights regarding working capital, net sales, and working capital turnover ratios over the observed periods.
- Working Capital
- Working capital shows fluctuations throughout the periods, beginning at 4,606 million USD in March 2015 and generally declining until a low point at 3,063 million USD in June 2015. Subsequent quarters witness a gradual recovery with intermittent increases and decreases, reaching peaks around 4,298 million USD by mid-2018. However, notable volatility is present, evidenced by a decline toward the end of 2018 and fiscal 2019. The working capital drops again sharply from 4,214 million USD in September 2019 to 3,291 million USD by December 2019, indicating potential tightening of liquidity or changes in current asset and liability management.
- Net Sales
- Net sales display a generally consistent upward trajectory over the periods analyzed. Starting from 5,288 million USD in March 2015, net sales increase with some minor fluctuations, culminating at 7,842 million USD by December 2019. This growth suggests expanding revenue generation capabilities and possibly increased market demand or improved operational execution. Each fiscal year tends to end with higher sales figures compared to previous years, revealing a steady growth pattern with occasional quarterly variations typical of seasonal or market-driven influences.
- Working Capital Turnover Ratio
- The working capital turnover ratio starts being reported from December 2015, with a value of 6.31. Through the subsequent periods, this ratio exhibits a generally increasing trend, peaking at 8.87 in December 2019. This rising turnover ratio indicates that the company is generating more sales per unit of working capital, which may reflect enhanced efficiency in managing current assets and liabilities or stronger sales growth relative to working capital. Periodic fluctuations occur; however, the overall trend points to improved working capital utilization over time.
Overall, the data suggests that while working capital levels demonstrate variability and some volatility, net sales have consistently grown, contributing to an improvement in working capital turnover ratios. This indicates increasing operational efficiency and possibly tighter working capital management, notwithstanding fluctuations that may require further investigation to understand underlying causes such as changes in inventory, receivables, payables, or external economic factors.
Average Inventory Processing Period
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 | Dec 31, 2015 | Sep 27, 2015 | Jun 28, 2015 | Mar 29, 2015 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data | ||||||||||||||||||||||||||
Inventory turnover | 31.91 | 26.15 | 21.83 | 22.58 | 25.82 | 24.07 | 26.44 | 29.81 | 32.11 | 26.78 | 31.64 | 30.18 | 27.23 | 27.80 | 26.82 | 28.48 | 27.68 | — | — | — | ||||||
Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||
Average inventory processing period1 | 11 | 14 | 17 | 16 | 14 | 15 | 14 | 12 | 11 | 14 | 12 | 12 | 13 | 13 | 14 | 13 | 13 | — | — | — | ||||||
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-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), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-27), 10-Q (reporting date: 2015-06-28), 10-Q (reporting date: 2015-03-29).
1 Q4 2019 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ 31.91 = 11
2 Click competitor name to see calculations.
- Inventory Turnover
- The inventory turnover ratio displays fluctuations across the analyzed periods. Starting from the earliest available data in March 2015, the ratio is not reported until April 2016, when it registers at 27.68. From this point, the ratio initially rises to 28.48 and then experiences a slight decline with intermittent variability, reaching a low of 22.58 by December 2018. Following this trough, the turnover again picks up steadily, peaking at 31.91 by the end of 2019. This pattern suggests periods of both improved and reduced efficiency in inventory management throughout the reporting timeframe.
- Average Inventory Processing Period
- The average inventory processing period, measured in days, inversely correlates with the turnover ratio trends. Beginning at 13 days in April 2016, the period remains relatively stable with minor oscillations around 12 to 14 days for multiple quarters. Notably, there is a gradual increase starting in late 2017, reaching a peak of 17 days in the third quarter of 2019. By the final quarter of 2019, the period diminishes back down to 11 days. This trajectory indicates variable inventory velocity where slower processing coincides with lower turnover, while faster cycles coincide with higher turnover rates.
- Overall Analysis
- The data reveals that inventory management efficiency experienced several shifts over the examined timeline. The inverse relationship between inventory turnover and processing period is consistent, reflecting that as the company turns over inventory more rapidly, the duration that inventory is held reduces correspondingly. The peak turnover and shortest processing period observed at the end of 2019 compared to earlier periods indicate an improvement in operational efficiency and possibly better alignment of inventory levels with sales demand. Nevertheless, intermittent periods of reduced turnover and extended processing suggest occasional challenges in maintaining optimal inventory levels.
Average Receivable Collection Period
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 | Dec 31, 2015 | Sep 27, 2015 | Jun 28, 2015 | Mar 29, 2015 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data | ||||||||||||||||||||||||||
Receivables turnover | 21.39 | 19.48 | 17.46 | 19.33 | 16.42 | 17.34 | 19.71 | 15.63 | 19.15 | 17.81 | 15.74 | 18.43 | — | — | — | — | — | — | — | — | ||||||
Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||
Average receivable collection period1 | 17 | 19 | 21 | 19 | 22 | 21 | 19 | 23 | 19 | 20 | 23 | 20 | — | — | — | — | — | — | — | — | ||||||
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-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), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-27), 10-Q (reporting date: 2015-06-28), 10-Q (reporting date: 2015-03-29).
1 Q4 2019 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ 21.39 = 17
2 Click competitor name to see calculations.
The receivables turnover ratio exhibits variability over the observed periods starting from April 2017. The ratio fluctuates between a low of 15.63 and a high of 21.39. After initially declining from 18.43 to 15.63 between April 2017 and April 2018, the ratio generally trends upwards with intermittent decreases. The most recent data point, December 2019, shows the highest ratio of 21.39, indicating an improvement in the efficiency of collecting receivables toward the end of the period.
Correspondingly, the average receivable collection period shows an inverse pattern relative to the turnover ratio. Starting from 20 days in April 2017, the collection period increases to a maximum of 23 days by April 2018, reflecting slower collections during that timeframe. Subsequently, the collection period decreases, reaching 17 days by December 2019. The reduction in number of days to collect receivables aligns with the improved turnover ratio observed in the later periods.
- Receivables turnover ratio
- - Fluctuated between 15.63 and 21.39 from April 2017 to December 2019
- - Shows a general upward trend after a dip in early 2018
- - Highest efficiency in receivables collection at the end of 2019
- Average receivable collection period
- - Varied between 17 and 23 days in the same timeframe
- - Increased initially, indicating slower collection in early 2018
- - Declined towards the end of 2019, suggesting improved collection speed
Overall, the data indicates that the company's receivables management improved in the latter part of the observed periods, with paying customers settling their accounts more quickly and the company efficiently turning over its receivables.
Operating Cycle
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 | Dec 31, 2015 | Sep 27, 2015 | Jun 28, 2015 | Mar 29, 2015 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data | ||||||||||||||||||||||||||
Average inventory processing period | 11 | 14 | 17 | 16 | 14 | 15 | 14 | 12 | 11 | 14 | 12 | 12 | 13 | 13 | 14 | 13 | 13 | — | — | — | ||||||
Average receivable collection period | 17 | 19 | 21 | 19 | 22 | 21 | 19 | 23 | 19 | 20 | 23 | 20 | — | — | — | — | — | — | — | — | ||||||
Short-term Activity Ratio | ||||||||||||||||||||||||||
Operating cycle1 | 28 | 33 | 38 | 35 | 36 | 36 | 33 | 35 | 30 | 34 | 35 | 32 | — | — | — | — | — | — | — | — | ||||||
Benchmarks | ||||||||||||||||||||||||||
Operating Cycle, Competitors2 | ||||||||||||||||||||||||||
Boeing Co. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Caterpillar Inc. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Eaton Corp. plc | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
GE Aerospace | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Honeywell International Inc. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Lockheed Martin Corp. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
RTX Corp. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
Based on: 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), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-27), 10-Q (reporting date: 2015-06-28), 10-Q (reporting date: 2015-03-29).
1 Q4 2019 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= 11 + 17 = 28
2 Click competitor name to see calculations.
The analysis of the quarterly financial data reveals several key trends in the company's operational efficiency over the observed periods.
- Average Inventory Processing Period
- The average inventory processing period shows some fluctuation with values initially around 13 to 14 days in early periods, dipping to as low as 11 days in April 2018, then rising towards the end of the period explored. Notably, there was an increase to 16 and 17 days in mid-2019, before declining again to 11 days by the end of 2019. This pattern suggests some variability in the speed at which inventory is converted, with occasional improvements followed by slower processing intervals.
- Average Receivable Collection Period
- This period demonstrates a varying trend, starting with a moderate level around 20 to 23 days from 2017 onwards. There is no consistent directional movement but rather oscillation between 19 and 23 days until mid-2019, after which there is a slight decline to 17 days by the end of 2019. These fluctuations indicate some inconsistency in the collection efficiency of receivables, though the overall trend towards the end of the period suggests potential improvement in collection speed.
- Operating Cycle
- The operating cycle, representing the total time taken for the company to convert its inventory and receivables into cash, follows a pattern closely linked with the other two metrics. Beginning around 32 to 35 days, the cycle remains relatively stable with some fluctuations between 30 and 38 days during 2017 to 2019. The highest points occur in late 2018 and early 2019, indicating periods of slower operational turnaround. However, there is a noticeable decrease to 28 days by the end of 2019, implying enhanced overall operational efficiency at that time.
In summary, the data suggest that while there were some periods of increased processing and collection times, the company generally maintained a stable operating cycle over the observed quarters. The improvements noted towards the end of 2019 could reflect better inventory management and receivable collections, contributing to a more efficient operating cycle overall.
Average Payables Payment Period
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 | Dec 31, 2015 | Sep 27, 2015 | Jun 28, 2015 | Mar 29, 2015 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data | ||||||||||||||||||||||||||
Payables turnover | 11.92 | 14.27 | 14.87 | 14.63 | 9.97 | 13.90 | 13.89 | 15.20 | 12.56 | 13.78 | 14.38 | 14.10 | 11.81 | 12.79 | 12.81 | 13.91 | 12.53 | — | — | — | ||||||
Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||
Average payables payment period1 | 31 | 26 | 25 | 25 | 37 | 26 | 26 | 24 | 29 | 26 | 25 | 26 | 31 | 29 | 28 | 26 | 29 | — | — | — | ||||||
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-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), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-27), 10-Q (reporting date: 2015-06-28), 10-Q (reporting date: 2015-03-29).
1 Q4 2019 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ 11.92 = 31
2 Click competitor name to see calculations.
- Payables Turnover Ratio
- The payables turnover ratio data begins in the period ending March 31, 2016. Initially, the ratio was at 12.53 and showed fluctuations over the subsequent quarters. There was a general increase peaking at 15.2 for the quarter ending July 1, 2018, indicating a higher efficiency in paying suppliers during this period. This was followed by a decline to a low of 9.97 in the quarter ending December 31, 2018, reflecting a slower payables turnover. Subsequently, the ratio recovered somewhat, fluctuating between 14.63 and 11.92 in the latest quarters ending December 31, 2019, suggesting some variability in the payment speed but generally maintaining a moderate pace of payables turnover.
- Average Payables Payment Period (Number of Days)
- The average payables payment period shows an inverse relationship to payables turnover, starting at 29 days for the quarter ending April 3, 2016. Over time, the payment period varied moderately, decreasing to 24 days in the quarter ending July 1, 2018, which corresponds with the higher turnover ratio in that same period. Notably, there was a significant increase to 37 days in the quarter ending December 31, 2018, coinciding with the lowest payables turnover ratio observed, indicating slower payments during that time. In subsequent periods, the payment period stabilized around the mid-to-high 20s, highlighting a return to a more consistent and efficient payment cycle.
Cash Conversion Cycle
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 | Dec 31, 2015 | Sep 27, 2015 | Jun 28, 2015 | Mar 29, 2015 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Selected Financial Data | ||||||||||||||||||||||||||
Average inventory processing period | 11 | 14 | 17 | 16 | 14 | 15 | 14 | 12 | 11 | 14 | 12 | 12 | 13 | 13 | 14 | 13 | 13 | — | — | — | ||||||
Average receivable collection period | 17 | 19 | 21 | 19 | 22 | 21 | 19 | 23 | 19 | 20 | 23 | 20 | — | — | — | — | — | — | — | — | ||||||
Average payables payment period | 31 | 26 | 25 | 25 | 37 | 26 | 26 | 24 | 29 | 26 | 25 | 26 | 31 | 29 | 28 | 26 | 29 | — | — | — | ||||||
Short-term Activity Ratio | ||||||||||||||||||||||||||
Cash conversion cycle1 | -3 | 7 | 13 | 10 | -1 | 10 | 7 | 11 | 1 | 8 | 10 | 6 | — | — | — | — | — | — | — | — | ||||||
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-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), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-27), 10-Q (reporting date: 2015-06-28), 10-Q (reporting date: 2015-03-29).
1 Q4 2019 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= 11 + 17 – 31 = -3
2 Click competitor name to see calculations.
- Average inventory processing period
- The inventory processing period is generally stable, fluctuating between 11 and 17 days over the observed time frame. Notably, there is an increase in the period towards the end of 2018 and mid-2019, peaking at 17 days, before decreasing again to 11 days by the last recorded quarter. This suggests slight variability but an overall tendency to maintain relatively consistent inventory turnover timing.
- Average receivable collection period
- The receivable collection period exhibits moderate fluctuations, ranging from 17 to 23 days. Early 2017 shows a peak at 23 days, followed by variations around 19 to 22 days for several quarters. Towards the end of the period, a slight decrease is observed, reaching 17 days in the last quarter. This indicates some improvements in the efficiency of receivables collection over time.
- Average payables payment period
- The payables payment period displays variability with values between 24 and 37 days. The period generally remains in the mid-to-high 20s, with a notable spike to 37 days in the first quarter of 2019 before returning to around 25-31 days afterward. This suggests occasional extensions in payment timing, possibly reflecting strategic cash management efforts.
- Cash conversion cycle
- The cash conversion cycle (CCC) shows notable variability, fluctuating between -3 and 13 days. After an initial period with positive CCC values around single digits, there are occasional dips into negative territory, notably in the final quarters of 2018 and 2019. Negative values indicate that the company is able to collect cash from sales faster than it pays its suppliers, which can be viewed as a favorable liquidity position. Overall, the CCC trend demonstrates efforts towards optimizing working capital management with varying short-term effectiveness.