Analysis of Short-term (Operating) Activity Ratios
Quarterly Data
Activity ratios measure how efficiently a company performs day-to-day tasks, such us the collection of receivables and management of inventory.
Short-term Activity Ratios (Summary)
Roper Technologies Inc., short-term (operating) activity ratios (quarterly data)
Based on: 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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 analysis of the quarterly financial ratios and cycle periods reveals several noteworthy trends over the observed periods.
- Inventory Turnover
- This ratio remained relatively stable from 2018 through 2021, fluctuating mostly between 8.95 and 10.92 times. A marked increase occurred in 2022, peaking at 18.84 in the first quarter, before gradually declining but still maintaining elevated levels around 14.7 to 14.8 in 2023. This suggests a significant improvement in inventory management efficiency beginning in 2022.
- Receivables Turnover
- The receivables turnover ratio showed moderate fluctuation, generally ranging between 6.4 and 8.8 times across the periods. A slight dip occurred in early 2020, possibly indicating slower collections, but the ratio recovered in subsequent quarters. The overall trend lacks a clear sustained increase or decrease, indicating steady management of receivables with some variability.
- Payables Turnover
- This ratio experienced fluctuations between approximately 9.2 and 13.9 times throughout the timeline. Notable variance occurred in late 2021 and into 2022, when the ratio increased significantly, suggesting faster payments to suppliers during this period. Payables turnover generally stayed at a high level, reflecting efficient accounts payable management.
- Working Capital Turnover
- Data for this ratio is sporadic. High values are observed in 2018 and 2019 (31.95 to 45.13), indicating strong utilization of working capital in these years. However, there is a dramatic drop to values below 8 in later years, with some missing data. The decline hints at a reduced efficiency in employing working capital during the more recent periods analyzed.
- Average Inventory Processing Period
- The average days to process inventory remained fairly consistent around 35 to 41 days up until 2021. A significant decrease appeared in 2022, dropping to roughly 19-25 days, maintaining this shorter period through 2023. This corresponds with the noted improvement in inventory turnover, implying faster inventory turnover and improved operational efficiency.
- Average Receivable Collection Period
- The collection period varied between 41 and 57 days, with a tendency toward longer collection periods during 2020 and early 2021. Starting from 2022, this period shortened closer to the lower end of the range, indicating quicker collections relative to prior years and enhanced cash flow management.
- Operating Cycle
- The operating cycle fluctuated between 60 and 93 days, with values generally trending downward beginning in 2022. The shortening cycle indicates improvements in the overall efficiency from inventory purchase to cash collection.
- Average Payables Payment Period
- Payment periods to suppliers decreased from about 36-40 days in 2020 and 2021 to around 26-29 days in 2022 and 2023. This suggests quicker payments to suppliers in recent periods, aligning with increases in payables turnover.
- Cash Conversion Cycle
- The cash conversion cycle remained relatively high, ranging mostly from 50 to 60 days, before showing a sharp decline to the 33-46 day range starting in 2022 and onward. This reduction signals more efficient cash flow management, as the company is able to convert investments in inventory and receivables into cash more rapidly.
Overall, the data indicates that starting in 2022, there was a significant improvement in efficiency concerning inventory management, receivables collection, and the cash conversion cycle. Inventory turnover surged while inventory holding periods shortened substantially. Concurrently, faster payments to suppliers and an improved cash conversion cycle reflect enhanced working capital management and operational efficiency in the most recent periods.
Turnover Ratios
Average No. Days
Inventory Turnover
Roper Technologies Inc., inventory turnover calculation (quarterly data)
| Sep 30, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | 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 sales | 467,100) | 464,100) | 451,100) | 428,600) | 408,500) | 399,300) | 382,600) | 494,300) | 466,700) | 459,300) | 440,100) | 538,700) | 490,200) | 461,300) | 493,900) | 501,900) | 480,900) | 480,300) | 476,600) | 503,200) | 478,700) | 477,800) | 452,000) | |||||||
| Inventories, net | 122,500) | 118,000) | 115,000) | 111,300) | 101,000) | 92,500) | 202,700) | 176,100) | 174,400) | 212,700) | 206,000) | 198,400) | 214,900) | 216,600) | 206,200) | 198,600) | 205,000) | 203,500) | 207,500) | 190,800) | 212,200) | 201,900) | 216,700) | |||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||
| Inventory turnover1 | 14.78 | 14.85 | 14.67 | 14.55 | 16.68 | 18.84 | 8.89 | 10.56 | 10.92 | 9.07 | 9.37 | 10.00 | 9.06 | 8.95 | 9.49 | 9.77 | 9.47 | 9.53 | 9.33 | 10.02 | — | — | — | |||||||
| Benchmarks | ||||||||||||||||||||||||||||||
| Inventory Turnover, Competitors2 | ||||||||||||||||||||||||||||||
| Apple Inc. | 29.54 | 29.24 | 32.36 | 45.20 | 40.43 | 40.07 | 36.69 | 32.37 | 39.55 | 37.48 | 36.21 | 41.75 | 42.55 | 49.75 | 40.54 | 39.40 | — | — | — | — | — | — | — | |||||||
| Arista Networks Inc. | 1.16 | 1.12 | 1.15 | 1.32 | 1.36 | 1.53 | 1.65 | 1.64 | 1.74 | 1.75 | 1.85 | 1.74 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Cisco Systems Inc. | 6.01 | 6.45 | 7.41 | 7.52 | 8.52 | 9.19 | 10.06 | 11.50 | 11.15 | 11.98 | 13.25 | 13.74 | 14.85 | 13.73 | 14.14 | 13.91 | — | — | — | — | — | — | — | |||||||
| Dell Technologies Inc. | 13.40 | 14.38 | 13.11 | 13.45 | 13.76 | 16.63 | 17.53 | 19.05 | 18.62 | 17.40 | 17.47 | 19.27 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Super Micro Computer Inc. | 3.49 | 3.84 | 2.88 | 2.84 | 2.50 | 2.58 | 2.77 | 2.90 | 3.18 | 3.39 | 3.59 | 3.30 | 3.19 | 3.91 | 4.12 | 4.48 | — | — | — | — | — | — | — | |||||||
Based on: 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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 Q3 2023 Calculation
Inventory turnover
= (Cost of salesQ3 2023
+ Cost of salesQ2 2023
+ Cost of salesQ1 2023
+ Cost of salesQ4 2022)
÷ Inventories, net
= (467,100 + 464,100 + 451,100 + 428,600)
÷ 122,500 = 14.78
2 Click competitor name to see calculations.
The financial data presents various trends regarding cost of sales, inventories, and inventory turnover over multiple quarters from March 2018 to September 2023.
- Cost of Sales
- The cost of sales displayed fluctuations across the quarters without a clear linear trend. From March 2018 to December 2018, it generally increased from 452,000 to 503,200 thousand US dollars. In 2019, the values hovered around the 476,000 to 501,900 thousand range, showing relative stability. Entering 2020, a noticeable decline was observed, reaching a low of 461,300 thousand in June 2020 before rising again to 538,700 thousand by December 2020. The year 2021 saw a decrease followed by a recovery, with figures ranging between 440,100 and 494,300 thousand. In 2022, there was a pronounced decline in cost of sales, dropping from 382,600 in March to 408,500 in September and slightly rebounding towards the end of the year. The first three quarters of 2023 exhibited moderate increases, with cost of sales moving from 451,100 thousand in March to 467,100 thousand in September.
- Inventories, Net
- The inventory levels showed a general downward trend during the early quarters, decreasing from 216,700 thousand in March 2018 to 190,800 thousand by December 2018. This was followed by fluctuating inventory levels throughout 2019 and 2020, with peaks around mid-2020 (216,600 thousand in June) and troughs toward the end of 2020 (198,400 thousand in December). In 2021, there was some volatility, including a notable dip to 174,400 thousand in September, but inventories increased later in the year. Noteworthy is the sharp decline in inventories in 2022, with a marked drop to 92,500 thousand in March, indicating significant inventory reduction. Subsequent quarters in 2022 and into 2023 show a gradual increase in inventory levels again, reaching 122,500 thousand by September 2023.
- Inventory Turnover
- Inventory turnover values were not provided until the March 2019 quarter. From that point, the ratio generally ranged between approximately 8.89 and 10.92 during 2019 through 2021, indicating moderate efficiency in inventory management. A striking change occurred in 2022, where the turnover ratios surged dramatically, peaking at 18.84 in March and remaining elevated through subsequent quarters (16.68 to 14.55). This sharp increase in turnover coincides with the substantial decline in inventory levels during the same period, suggesting enhanced inventory utilization or accelerated sales relative to available stock. The early 2023 data maintain higher turnover levels than previous years, though with a slight decrease compared to 2022, stabilizing around 14.67 to 14.85.
Overall, the data suggests a period of relatively stable cost of sales and inventories through 2018 to 2021 followed by pronounced changes in 2022 characterized by reduced inventory levels and significantly higher inventory turnover. These patterns may reflect adjustments in operational efficiency, inventory management strategies, or market conditions affecting sales and supply chain dynamics.
Receivables Turnover
Roper Technologies Inc., receivables turnover calculation (quarterly data)
| Sep 30, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | 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 | 1,563,400) | 1,531,200) | 1,469,700) | 1,430,900) | 1,350,300) | 1,310,800) | 1,279,800) | 1,512,300) | 1,462,800) | 1,426,600) | 1,376,100) | 1,505,300) | 1,366,100) | 1,305,000) | 1,350,700) | 1,394,800) | 1,354,500) | 1,330,300) | 1,287,200) | 1,376,300) | 1,318,700) | 1,293,700) | 1,202,500) | |||||||
| Accounts receivable, net | 746,400) | 684,400) | 629,100) | 724,500) | 630,300) | 628,500) | 755,300) | 839,400) | 749,400) | 804,200) | 792,000) | 863,000) | 773,400) | 738,800) | 712,200) | 791,600) | 697,600) | 698,200) | 629,300) | 700,800) | 671,700) | 669,300) | 631,200) | |||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||
| Receivables turnover1 | 8.03 | 8.45 | 8.84 | 7.41 | 8.65 | 8.86 | 7.52 | 6.88 | 7.70 | 7.06 | 7.01 | 6.40 | 7.00 | 7.32 | 7.62 | 6.78 | 7.67 | 7.61 | 8.38 | 7.41 | — | — | — | |||||||
| Benchmarks | ||||||||||||||||||||||||||||||
| Receivables Turnover, Competitors2 | ||||||||||||||||||||||||||||||
| Apple Inc. | 19.64 | 21.47 | 16.32 | 13.99 | 17.77 | 18.55 | 12.52 | 13.92 | 19.87 | 17.59 | 10.85 | 17.03 | 15.31 | 17.04 | 12.77 | 11.35 | — | — | — | — | — | — | — | |||||||
| Arista Networks Inc. | 6.71 | 6.75 | 5.63 | 4.75 | 6.03 | 5.98 | 4.87 | 5.71 | 7.01 | 7.22 | 6.47 | 5.95 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Cisco Systems Inc. | 10.76 | 10.15 | 9.61 | 7.79 | 8.92 | 8.59 | 9.57 | 8.64 | 11.04 | 11.15 | 12.08 | 9.01 | 11.07 | 11.91 | 10.66 | 9.45 | — | — | — | — | — | — | — | |||||||
| Dell Technologies Inc. | 9.21 | 7.96 | 8.85 | 7.84 | 7.01 | 7.46 | 8.70 | 7.37 | 8.10 | 7.86 | 8.53 | 7.38 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Super Micro Computer Inc. | 9.78 | 8.65 | 8.17 | 6.23 | 6.81 | 8.38 | 8.36 | 7.67 | 8.31 | 10.10 | 10.23 | 8.27 | 9.90 | 9.07 | 9.35 | 8.89 | — | — | — | — | — | — | — | |||||||
Based on: 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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 Q3 2023 Calculation
Receivables turnover
= (Net revenuesQ3 2023
+ Net revenuesQ2 2023
+ Net revenuesQ1 2023
+ Net revenuesQ4 2022)
÷ Accounts receivable, net
= (1,563,400 + 1,531,200 + 1,469,700 + 1,430,900)
÷ 746,400 = 8.03
2 Click competitor name to see calculations.
The financial data indicates a generally positive trend in net revenues over the examined periods, with some fluctuations reflecting seasonal or market variability. From March 2018 through September 2023, net revenues increased overall, moving from approximately $1.2 billion to over $1.56 billion. Notably, there was a slight dip in revenues around March 2020, coinciding with early stages of global economic disruptions, but recovery and growth consistently followed this period.
Accounts receivable, net, presents a more variable pattern. Initially, receivables grew steadily from March 2018 to December 2019, suggesting expanding sales on credit. A peak occurs around December 2020 with a value surpassing $860 million, reflecting potentially extended credit terms or increased sales volume on account. Subsequently, a decline is notable through the mid-2022 period, falling below $630 million, followed by another upward trend nearing $750 million by September 2023. This fluctuation may indicate adjustments in credit management or shifts in customer payment behavior over time.
The receivables turnover ratio, though absent for initial quarters, provides insight from March 2019 onward. The ratio displays variability, typically fluctuating between approximately 6.4 and 8.86, illustrating changes in how efficiently the company collects its receivables during different quarters. Peaks in the turnover ratio, such as in June 2022 and March 2023, indicate periods of improved collection efficiency. Conversely, troughs, such as in March 2019 and September 2020, suggest slower collections during those intervals. Overall, the ratio trends imply that the company manages receivables effectively, with occasional fluctuations possibly tied to external factors impacting customer payments.
- Net Revenues
- Demonstrated a steady growth trajectory across most periods, with a temporary decline in early 2020 followed by a recovery and continued increase through 2023.
- Accounts Receivable, Net
- Experienced periods of growth and decline reflecting changing credit sales volume and collection policies, with the highest values recorded in late 2020 and a subsequent decrease in 2021 and early 2022 before rising again toward the later periods.
- Receivables Turnover Ratio
- Exhibited variability quarter to quarter, generally maintaining levels indicative of effective receivables management. Fluctuations suggest responsiveness to external economic influences and adjustments in internal credit collection practices.
Payables Turnover
Roper Technologies Inc., payables turnover calculation (quarterly data)
| Sep 30, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | 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 sales | 467,100) | 464,100) | 451,100) | 428,600) | 408,500) | 399,300) | 382,600) | 494,300) | 466,700) | 459,300) | 440,100) | 538,700) | 490,200) | 461,300) | 493,900) | 501,900) | 480,900) | 480,300) | 476,600) | 503,200) | 478,700) | 477,800) | 452,000) | |||||||
| Accounts payable | 135,800) | 141,100) | 134,000) | 122,600) | 121,200) | 128,800) | 167,800) | 150,800) | 146,900) | 209,600) | 190,900) | 177,800) | 173,100) | 185,400) | 180,800) | 162,000) | 156,800) | 162,200) | 172,600) | 165,300) | 163,700) | 165,200) | 171,100) | |||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||
| Payables turnover1 | 13.34 | 12.42 | 12.59 | 13.21 | 13.90 | 13.53 | 10.74 | 12.34 | 12.97 | 9.20 | 10.11 | 11.16 | 11.25 | 10.45 | 10.82 | 11.97 | 12.38 | 11.95 | 11.22 | 11.57 | — | — | — | |||||||
| Benchmarks | ||||||||||||||||||||||||||||||
| Payables Turnover, Competitors2 | ||||||||||||||||||||||||||||||
| Apple Inc. | 4.65 | 5.10 | 3.81 | 3.49 | 4.54 | 4.15 | 2.90 | 3.89 | 5.07 | 4.88 | 2.82 | 4.01 | 4.79 | 5.12 | 3.68 | 3.50 | — | — | — | — | — | — | — | |||||||
| Arista Networks Inc. | 8.16 | 5.95 | 5.84 | 7.33 | 5.39 | 4.74 | 5.61 | 5.27 | 7.39 | 6.54 | 6.52 | 6.23 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Cisco Systems Inc. | 8.55 | 8.69 | 8.53 | 8.47 | 8.31 | 9.00 | 8.15 | 7.59 | 7.22 | 9.22 | 7.53 | 7.94 | 7.52 | 9.60 | 9.43 | 9.34 | — | — | — | — | — | — | — | |||||||
| Dell Technologies Inc. | 3.67 | 3.34 | 3.22 | 2.92 | 2.80 | 3.05 | 3.11 | 2.99 | 3.19 | 3.21 | 3.43 | 3.15 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Super Micro Computer Inc. | 8.38 | 9.76 | 6.38 | 6.71 | 5.09 | 5.18 | 5.82 | 4.94 | 6.18 | 6.91 | 8.33 | 6.74 | 5.97 | 7.02 | 8.51 | 8.34 | — | — | — | — | — | — | — | |||||||
Based on: 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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 Q3 2023 Calculation
Payables turnover
= (Cost of salesQ3 2023
+ Cost of salesQ2 2023
+ Cost of salesQ1 2023
+ Cost of salesQ4 2022)
÷ Accounts payable
= (467,100 + 464,100 + 451,100 + 428,600)
÷ 135,800 = 13.34
2 Click competitor name to see calculations.
The analyzed financial data reveals a series of trends in the cost of sales, accounts payable, and payables turnover ratios over the given periods.
- Cost of Sales
- The cost of sales exhibits fluctuations across the quarters with a general pattern of increase followed by declines and subsequent recovery phases. Initially, from March 2018 to December 2018, there is a gradual upward trajectory from approximately 452 million USD to over 503 million USD. This is followed by a period spanning early 2019 to early 2020 where values remain relatively stable around the high 400 million USD mark, peaking at 501.9 million in December 2019.
- In 2020, a decline occurs in the mid-year quarter (June 2020) to about 461 million USD, yet the figure rebounds by the end of that year to approximately 538.7 million USD, the highest in the dataset. The first three quarters of 2021 show a decrease, with the cost of sales dropping to around 440 million USD and stabilizing near 466 million USD by September, then increasing again towards December 2021.
- From 2022 onwards, a noticeable decline in the cost of sales is observed, reaching the lowest point at 382.6 million USD in March 2022, followed by a moderate increase peaking near 428.6 million USD at the end of 2022 and a continuous rise into mid-2023 where figures approach the mid-460 million USD range. This pattern may indicate variability in production or service costs, supply chain dynamics, or changes in sales volume.
- Accounts Payable
- Accounts payable values demonstrate volatility with no consistent long-term trend but notable fluctuations within given years. Between March 2018 and December 2019, the values oscillate between approximately 156.8 million USD and 180.8 million USD without a clear upward or downward trend. The first half of 2020 shows a spike reaching 185.4 million USD in June before decreasing again by year-end.
- The year 2021 starts with an uptrend in payables, peaking at about 209.6 million USD in June 2021, then sharply dropping to below 150 million USD by September and December 2021. A pronounced decrease is evident at the start of 2022, reaching approximately 121.2 million USD in June, and remaining relatively stable at lower levels through September 2023 compared to previous years. This decrease could be reflective of improved payment terms, changes in supplier relationships, or operational efficiency gains.
- Payables Turnover Ratio
- The payables turnover ratio, available from March 2019 onward, shows moderate fluctuations with values generally ranging between 9.2 and 13.9. Early ratios in 2019 indicate a level around 11 to 12, followed by a decline toward 9.2 in September 2020, suggesting slower payments or increased credit terms during that time.
- The ratio peaks at 13.9 in June 2022, indicating faster payments or shorter payables cycles during that period. Following this peak, the ratio trends slightly downward but remains above 12, suggesting a general improvement in the efficiency of payables management compared to earlier periods. The variability implies that the company may have adjusted payment policies or supplier terms in response to changing cash flow needs or market conditions.
Overall, the data reflects dynamic operational conditions affecting cost structure and payables management. The cost of sales shows cyclical variations with a recent trend toward recovery after a significant dip. Accounts payable decreased notably from 2021 to 2023, coinciding with an increase in payables turnover ratio, which together suggest an acceleration in payment cycles and potential improvements in working capital management. These insights could be valuable for strategic financial planning and operational adjustments.
Working Capital Turnover
Roper Technologies Inc., working capital turnover calculation (quarterly data)
| Sep 30, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | 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 | 1,504,500) | 2,606,100) | 2,232,200) | 1,932,400) | 3,991,400) | 4,992,000) | 4,485,600) | 2,421,100) | 2,375,200) | 1,796,700) | 1,739,400) | 1,752,300) | 1,706,200) | 3,179,200) | 2,273,400) | 1,999,500) | 1,619,400) | 1,602,300) | 1,586,000) | 1,610,700) | 1,608,000) | 1,651,100) | 1,502,000) | |||||||
| Less: Current liabilities | 2,812,700) | 2,763,900) | 2,775,400) | 2,892,500) | 2,840,400) | 3,166,100) | 3,501,800) | 3,121,800) | 2,861,100) | 2,503,100) | 2,462,900) | 2,444,400) | 2,339,900) | 2,498,600) | 2,366,100) | 2,397,400) | 1,500,900) | 1,443,200) | 1,444,700) | 1,448,200) | 2,119,300) | 2,066,400) | 2,047,500) | |||||||
| Working capital | (1,308,200) | (157,800) | (543,200) | (960,100) | 1,151,000) | 1,825,900) | 983,800) | (700,700) | (485,900) | (706,400) | (723,500) | (692,100) | (633,700) | 680,600) | (92,700) | (397,900) | 118,500) | 159,100) | 141,300) | 162,500) | (511,300) | (415,300) | (545,500) | |||||||
| Net revenues | 1,563,400) | 1,531,200) | 1,469,700) | 1,430,900) | 1,350,300) | 1,310,800) | 1,279,800) | 1,512,300) | 1,462,800) | 1,426,600) | 1,376,100) | 1,505,300) | 1,366,100) | 1,305,000) | 1,350,700) | 1,394,800) | 1,354,500) | 1,330,300) | 1,287,200) | 1,376,300) | 1,318,700) | 1,293,700) | 1,202,500) | |||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||
| Working capital turnover1 | — | — | — | — | 4.74 | 3.05 | 5.78 | — | — | — | — | — | — | 7.94 | — | — | 45.13 | 33.39 | 37.34 | 31.95 | — | — | — | |||||||
| Benchmarks | ||||||||||||||||||||||||||||||
| Working Capital Turnover, Competitors2 | ||||||||||||||||||||||||||||||
| Apple Inc. | — | — | — | — | — | — | 67.80 | 39.10 | 52.06 | 21.58 | 13.62 | 7.16 | 6.12 | 5.62 | 4.38 | 4.56 | — | — | — | — | — | — | — | |||||||
| Arista Networks Inc. | 0.96 | 1.01 | 1.04 | 1.03 | 1.04 | 1.01 | 0.85 | 0.80 | 0.76 | 0.76 | 0.77 | 0.76 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Cisco Systems Inc. | 4.89 | 4.72 | 4.65 | 4.65 | 4.36 | 4.74 | 3.54 | 3.88 | 3.82 | 2.89 | 3.00 | 2.70 | 3.29 | 2.87 | 3.04 | 3.24 | — | — | — | — | — | — | — | |||||||
| Dell Technologies Inc. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Super Micro Computer Inc. | 4.05 | 3.84 | 3.94 | 3.89 | 3.91 | 3.81 | 4.09 | 3.96 | 3.95 | 3.74 | 3.71 | 3.77 | 3.82 | 3.85 | 4.00 | 4.29 | — | — | — | — | — | — | — | |||||||
Based on: 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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 Q3 2023 Calculation
Working capital turnover
= (Net revenuesQ3 2023
+ Net revenuesQ2 2023
+ Net revenuesQ1 2023
+ Net revenuesQ4 2022)
÷ Working capital
= (1,563,400 + 1,531,200 + 1,469,700 + 1,430,900)
÷ -1,308,200 = —
2 Click competitor name to see calculations.
- Working Capital
- The working capital figures exhibit significant volatility over the observed periods. Initially, from March 2018 through the end of 2018, working capital fluctuates from a substantial negative position (-545,500 thousand USD) to a positive balance at year-end (162,500 thousand USD). Subsequently, the trend reverts to negative territory for much of 2019 and 2020, including notable fluctuations such as a positive spike of 680,600 thousand USD in mid-2020 followed by two quarters of deep negative working capital (-633,700 to -692,100 thousand USD). The pattern of negative working capital continues through 2021, with slight improvements observed into 2022 when the company posts substantial positive working capital reaching as high as 1,825,900 thousand USD by mid-2022. However, this upward momentum reverses again toward the end of 2022 and early 2023 with a steep decline back into negative figures, culminating at -1,308,200 thousand USD in September 2023. Overall, the working capital indicates erratic short-term liquidity positions, with alternating periods of deficit and surplus, suggesting fluctuating operational funding and current asset/liability management challenges.
- Net Revenues
- Net revenues show a generally upward trajectory over the time frame analyzed. Starting at approximately 1,202,500 thousand USD in the first quarter of 2018, revenues display periodic increases across most quarters. Despite some minor quarter-to-quarter variations, the trend remains positive. Notably, through 2019 and 2020, revenues fluctuate around the 1,300,000 to 1,500,000 thousand USD range, accelerating further into 2021 and beyond. By the third quarter of 2023, net revenues reach 1,563,400 thousand USD, marking a considerable growth of about 30% over the period. This steady increase may reflect enhanced sales performance, expanded operations, or improved market positioning over the years.
- Working Capital Turnover
- The working capital turnover ratio data is incomplete with values provided only for specific years and quarters. In 2018 and 2019, when available, the turnover ratios are exceptionally high (31.95 to 45.13), indicating efficient use of working capital relative to sales during those quarters. However, the ratios drastically decline in the periods reported later, with readings such as 7.94 and further down to 5.78, 3.05, and 4.74 in 2022, reflecting reduced efficiency in utilizing working capital to generate revenue. Such a decrease may be symptomatic of the earlier observed volatility in working capital balances, particularly the sharp swings between positive and negative values which could distort operational efficiency.
- General Insights
- The data suggest that despite a consistent increase in net revenues, operational liquidity as measured by working capital is highly unstable. This instability likely impacts the company's working capital turnover negatively as the capacity to manage current assets and liabilities efficiently diminishes. The high variance in working capital alongside the moderate decline in turnover ratios underlines potential risks associated with cash flow management and short-term financial health. Continuous monitoring and targeted improvements in working capital management could benefit operational efficiency and support sustained revenue growth.
Average Inventory Processing Period
Roper Technologies Inc., average inventory processing period calculation (quarterly data)
| Sep 30, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | 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 | 14.78 | 14.85 | 14.67 | 14.55 | 16.68 | 18.84 | 8.89 | 10.56 | 10.92 | 9.07 | 9.37 | 10.00 | 9.06 | 8.95 | 9.49 | 9.77 | 9.47 | 9.53 | 9.33 | 10.02 | — | — | — | |||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||||
| Average inventory processing period1 | 25 | 25 | 25 | 25 | 22 | 19 | 41 | 35 | 33 | 40 | 39 | 36 | 40 | 41 | 38 | 37 | 39 | 38 | 39 | 36 | — | — | — | |||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||||
| Average Inventory Processing Period, Competitors2 | ||||||||||||||||||||||||||||||
| Apple Inc. | 12 | 12 | 11 | 8 | 9 | 9 | 10 | 11 | 9 | 10 | 10 | 9 | 9 | 7 | 9 | 9 | — | — | — | — | — | — | — | |||||||
| Arista Networks Inc. | 315 | 325 | 318 | 276 | 268 | 239 | 221 | 222 | 210 | 209 | 197 | 210 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Cisco Systems Inc. | 61 | 57 | 49 | 49 | 43 | 40 | 36 | 32 | 33 | 30 | 28 | 27 | 25 | 27 | 26 | 26 | — | — | — | — | — | — | — | |||||||
| Dell Technologies Inc. | 27 | 25 | 28 | 27 | 27 | 22 | 21 | 19 | 20 | 21 | 21 | 19 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Super Micro Computer Inc. | 105 | 95 | 127 | 128 | 146 | 141 | 132 | 126 | 115 | 108 | 102 | 110 | 114 | 93 | 89 | 81 | — | — | — | — | — | — | — | |||||||
Based on: 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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 Q3 2023 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ 14.78 = 25
2 Click competitor name to see calculations.
- Inventory Turnover
- The inventory turnover ratio exhibits a general upward trend over the analyzed period. Starting at 10.02 in the first quarter of 2018, it experienced slight fluctuations but remained mostly stable around the 9 to 10 range until the end of 2021.
- From early 2022 onwards, a significant increase is observed, with the ratio reaching 18.84 in the first quarter of 2022. Following this spike, the turnover ratio slightly declines but stays elevated compared to previous years, fluctuating between approximately 14.5 and 14.9 in subsequent quarters up to the third quarter of 2023.
- This indicates a marked improvement in the efficiency with which inventory is converted into sales during the recent period, suggesting enhanced inventory management or increased sales volume relative to inventory levels.
- Average Inventory Processing Period
- The average inventory processing period inversely mirrors the trend seen in inventory turnover, as expected. It maintained a relatively stable range between 33 and 41 days from 2018 through 2021, mostly hovering around 36 to 40 days.
- Beginning in 2022, the processing period sharply decreases to 19 days in the first quarter, signifying faster inventory turnover. In the following quarters, the days increase slightly but remain significantly lower than the pre-2022 period, stabilizing around 25 days through the third quarter of 2023.
- This reduction in days aligns with the increase in inventory turnover ratio and reflects more rapid inventory movement, indicating improvements in sales velocity or inventory control mechanisms.
- Overall Insights
- The data suggests a strategic or operational change around early 2022 that substantially enhanced inventory turnover efficiency. The sustained higher turnover ratio combined with shorter processing periods points towards optimized inventory levels and/or improved market demand conditions.
- Prior to 2022, inventory management was stable but less dynamic, with moderate turnover ratios and longer average processing periods. The dramatic changes from 2022 onwards could be attributed to shifts in business strategy, supply chain adjustments, or external market factors influencing sales and inventory handling.
Average Receivable Collection Period
Roper Technologies Inc., average receivable collection period calculation (quarterly data)
| Sep 30, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | 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 | 8.03 | 8.45 | 8.84 | 7.41 | 8.65 | 8.86 | 7.52 | 6.88 | 7.70 | 7.06 | 7.01 | 6.40 | 7.00 | 7.32 | 7.62 | 6.78 | 7.67 | 7.61 | 8.38 | 7.41 | — | — | — | |||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||||
| Average receivable collection period1 | 45 | 43 | 41 | 49 | 42 | 41 | 49 | 53 | 47 | 52 | 52 | 57 | 52 | 50 | 48 | 54 | 48 | 48 | 44 | 49 | — | — | — | |||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||||
| Average Receivable Collection Period, Competitors2 | ||||||||||||||||||||||||||||||
| Apple Inc. | 19 | 17 | 22 | 26 | 21 | 20 | 29 | 26 | 18 | 21 | 34 | 21 | 24 | 21 | 29 | 32 | — | — | — | — | — | — | — | |||||||
| Arista Networks Inc. | 54 | 54 | 65 | 77 | 61 | 61 | 75 | 64 | 52 | 51 | 56 | 61 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Cisco Systems Inc. | 34 | 36 | 38 | 47 | 41 | 43 | 38 | 42 | 33 | 33 | 30 | 41 | 33 | 31 | 34 | 39 | — | — | — | — | — | — | — | |||||||
| Dell Technologies Inc. | 40 | 46 | 41 | 47 | 52 | 49 | 42 | 50 | 45 | 46 | 43 | 49 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Super Micro Computer Inc. | 37 | 42 | 45 | 59 | 54 | 44 | 44 | 48 | 44 | 36 | 36 | 44 | 37 | 40 | 39 | 41 | — | — | — | — | — | — | — | |||||||
Based on: 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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 Q3 2023 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ 8.03 = 45
2 Click competitor name to see calculations.
The receivables turnover ratio data, available from March 31, 2018 onward, indicates fluctuations over the analyzed periods. Initially, the ratio increased from 7.41 in March 2018 to a peak around 8.38 in June 2018, suggesting improved efficiency in collecting receivables. This was followed by periods of decline and recovery, with the ratio dipping to approximately 6.4 by December 2020 before rising again to around 8.86 by June 2022. The most recent values show a slight decrease but remain relatively high, with 8.03 recorded by September 2023.
Correspondingly, the average receivable collection period, expressed in days, demonstrates an inverse pattern to the turnover ratio, as expected. The collection period began at 49 days in March 2018, dropped to a low of 41 days in September 2022 and June 2023, and peaked at 57 days in December 2020. These variations reflect changes in the speed at which the company collects outstanding receivables. Periods with higher turnover ratios coincide with shorter collection periods, indicating improved collection efficiency, whereas lower turnover periods correspond with longer collection durations.
Overall, the data reveal cyclical trends in receivables management, with fluctuations in turnover and collection period that may be influenced by operational changes, economic conditions, or changes in credit policies. The general trend since 2020 suggests recovery and improvement in receivables turnover efficiency, as evidenced by the rising turnover ratios and decreasing average collection periods, implying enhanced liquidity and potentially more effective credit control processes.
- Receivables Turnover Ratio
- Fluctuated between approximately 6.4 and 8.86, peaking in mid-2022, with recent values showing some stabilization above 8.0.
- Average Receivable Collection Period
- Varied inversely with turnover, fluctuating between 41 and 57 days, with prolonged collection in late 2020 and improvements seen thereafter.
- Trend Insights
- The inverse relationship between turnover ratio and collection period indicates cycles of varying collection efficiency, with recent improvements suggesting enhanced accounts receivable management.
Operating Cycle
Roper Technologies Inc., operating cycle calculation (quarterly data)
No. days
| Sep 30, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | 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 | 25 | 25 | 25 | 25 | 22 | 19 | 41 | 35 | 33 | 40 | 39 | 36 | 40 | 41 | 38 | 37 | 39 | 38 | 39 | 36 | — | — | — | |||||||
| Average receivable collection period | 45 | 43 | 41 | 49 | 42 | 41 | 49 | 53 | 47 | 52 | 52 | 57 | 52 | 50 | 48 | 54 | 48 | 48 | 44 | 49 | — | — | — | |||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||
| Operating cycle1 | 70 | 68 | 66 | 74 | 64 | 60 | 90 | 88 | 80 | 92 | 91 | 93 | 92 | 91 | 86 | 91 | 87 | 86 | 83 | 85 | — | — | — | |||||||
| Benchmarks | ||||||||||||||||||||||||||||||
| Operating Cycle, Competitors2 | ||||||||||||||||||||||||||||||
| Apple Inc. | 31 | 29 | 33 | 34 | 30 | 29 | 39 | 37 | 27 | 31 | 44 | 30 | 33 | 28 | 38 | 41 | — | — | — | — | — | — | — | |||||||
| Arista Networks Inc. | 369 | 379 | 383 | 353 | 329 | 300 | 296 | 286 | 262 | 260 | 253 | 271 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Cisco Systems Inc. | 95 | 93 | 87 | 96 | 84 | 83 | 74 | 74 | 66 | 63 | 58 | 68 | 58 | 58 | 60 | 65 | — | — | — | — | — | — | — | |||||||
| Dell Technologies Inc. | 67 | 71 | 69 | 74 | 79 | 71 | 63 | 69 | 65 | 67 | 64 | 68 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Super Micro Computer Inc. | 142 | 137 | 172 | 187 | 200 | 185 | 176 | 174 | 159 | 144 | 138 | 154 | 151 | 133 | 128 | 122 | — | — | — | — | — | — | — | |||||||
Based on: 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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 Q3 2023 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= 25 + 45 = 70
2 Click competitor name to see calculations.
The data reveals several noteworthy trends regarding the company's working capital management over the observed periods.
- Average Inventory Processing Period
- This metric generally fluctuates within a moderate range from 2018 through early 2021, primarily oscillating between approximately 33 and 41 days. Notably, a significant decrease is observed beginning in March 2022, when the period drops sharply to 19 days, marking a considerable improvement in inventory turnover efficiency. After this drop, the inventory processing period stabilizes around 22 to 25 days through mid-2023.
- Average Receivable Collection Period
- The receivable collection period exhibits a relatively stable pattern from early 2018 to early 2022, mainly varying between 40 and 57 days. Peaks are seen around late 2020 and early 2021 (up to 57 days), indicating slower collections during those quarters. From March 2022 onward, the collection period demonstrates improvement, declining to the low 40s, indicative of enhanced receivables management and faster cash recovery.
- Operating Cycle
- The operating cycle mirrors the inventory and receivables trends, experiencing moderate fluctuations above 80 days through 2021, including peaks exceeding 90 days in some quarters. Starting in the first quarter of 2022, there is a marked reduction in the operating cycle, dropping to as low as 60 days and remaining within the 60 to 70-day range through mid-2023. This suggests improved overall efficiency in converting inventory and receivables into cash.
In summary, the company's working capital efficiency has improved significantly beginning in early 2022, as evidenced by reductions in inventory processing time, receivable collection, and overall operating cycle durations. These changes imply better inventory management and cash flow operations, potentially reflecting strategic adjustments or operational improvements implemented during that period.
Average Payables Payment Period
Roper Technologies Inc., average payables payment period calculation (quarterly data)
| Sep 30, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | 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 | ||||||||||||||||||||||||||||||
| Payables turnover | 13.34 | 12.42 | 12.59 | 13.21 | 13.90 | 13.53 | 10.74 | 12.34 | 12.97 | 9.20 | 10.11 | 11.16 | 11.25 | 10.45 | 10.82 | 11.97 | 12.38 | 11.95 | 11.22 | 11.57 | — | — | — | |||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||||
| Average payables payment period1 | 27 | 29 | 29 | 28 | 26 | 27 | 34 | 30 | 28 | 40 | 36 | 33 | 32 | 35 | 34 | 30 | 29 | 31 | 33 | 32 | — | — | — | |||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||||
| Average Payables Payment Period, Competitors2 | ||||||||||||||||||||||||||||||
| Apple Inc. | 79 | 72 | 96 | 105 | 80 | 88 | 126 | 94 | 72 | 75 | 129 | 91 | 76 | 71 | 99 | 104 | — | — | — | — | — | — | — | |||||||
| Arista Networks Inc. | 45 | 61 | 62 | 50 | 68 | 77 | 65 | 69 | 49 | 56 | 56 | 59 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Cisco Systems Inc. | 43 | 42 | 43 | 43 | 44 | 41 | 45 | 48 | 51 | 40 | 48 | 46 | 49 | 38 | 39 | 39 | — | — | — | — | — | — | — | |||||||
| Dell Technologies Inc. | 99 | 109 | 113 | 125 | 130 | 120 | 117 | 122 | 114 | 114 | 107 | 116 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Super Micro Computer Inc. | 44 | 37 | 57 | 54 | 72 | 70 | 63 | 74 | 59 | 53 | 44 | 54 | 61 | 52 | 43 | 44 | — | — | — | — | — | — | — | |||||||
Based on: 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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 Q3 2023 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ 13.34 = 27
2 Click competitor name to see calculations.
- Payables Turnover Ratio Trends
- The payables turnover ratio presents a fluctuating pattern over the observed period from March 2018 to September 2023. Initially starting at approximately 11.57 in March 2019, the ratio shows moderate variation through 2019 and 2020, moving between roughly 10.11 and 12.38. This suggests a generally stable but somewhat volatile frequency at which payables are settled. Notably, there is a decline observed during 2020, reaching a low near 9.2 in September 2021, indicating slower payment activity at that time. Following this trough, the ratio picks up substantially, rising to peak values above 13 by late 2021 and maintaining elevated levels through 2022 and into 2023, hovering mostly between 12.4 and 13.5. This increase in turnover ratio in recent periods signals a tendency towards quicker settlement of payables or improved management of payable accounts.
- Average Payables Payment Period
- Reflecting the inverse of the payables turnover ratio, the average payables payment period reveals complementary trends, measured in number of days. From March 2019 onward, the average days to settle payables oscillate, initially decreasing from 32 days through 2019 to a low of 28 days by December 2021, suggesting generally efficient payment timing. However, there is a notable increase peaking at 40 days around mid-2021, indicating a temporary slowdown in payments. This peak aligns with the dip in payables turnover ratio observed during the same timeframe. Post this peak, the payment period decreases again, stabilizing near 26 to 29 days through 2022 and 2023, consistent with the improved turnover ratio in those periods. This normalization suggests a return to more prompt payment behavior or enhanced accounts payable management.
- Overall Insights
- The data indicate a cyclical pattern in the company's management of payables, with periods of slower payment corresponding to lower turnover ratios and longer payment periods. The temporary deterioration observed around 2020-2021 could be attributed to operational challenges or external factors impacting cash flow management. The subsequent recovery and improvement in payables turnover and shorter payment periods demonstrate effective adjustments leading to more efficient payables processing. In summary, recent trends show a positive movement towards better liquidity management reflected by faster payment cycles.
Cash Conversion Cycle
Roper Technologies Inc., cash conversion cycle calculation (quarterly data)
No. days
| Sep 30, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | 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 | 25 | 25 | 25 | 25 | 22 | 19 | 41 | 35 | 33 | 40 | 39 | 36 | 40 | 41 | 38 | 37 | 39 | 38 | 39 | 36 | — | — | — | |||||||
| Average receivable collection period | 45 | 43 | 41 | 49 | 42 | 41 | 49 | 53 | 47 | 52 | 52 | 57 | 52 | 50 | 48 | 54 | 48 | 48 | 44 | 49 | — | — | — | |||||||
| Average payables payment period | 27 | 29 | 29 | 28 | 26 | 27 | 34 | 30 | 28 | 40 | 36 | 33 | 32 | 35 | 34 | 30 | 29 | 31 | 33 | 32 | — | — | — | |||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||
| Cash conversion cycle1 | 43 | 39 | 37 | 46 | 38 | 33 | 56 | 58 | 52 | 52 | 55 | 60 | 60 | 56 | 52 | 61 | 58 | 55 | 50 | 53 | — | — | — | |||||||
| Benchmarks | ||||||||||||||||||||||||||||||
| Cash Conversion Cycle, Competitors2 | ||||||||||||||||||||||||||||||
| Apple Inc. | -48 | -43 | -63 | -71 | -50 | -59 | -87 | -57 | -45 | -44 | -85 | -61 | -43 | -43 | -61 | -63 | — | — | — | — | — | — | — | |||||||
| Arista Networks Inc. | 324 | 318 | 321 | 303 | 261 | 223 | 231 | 217 | 213 | 204 | 197 | 212 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Cisco Systems Inc. | 52 | 51 | 44 | 53 | 40 | 42 | 29 | 26 | 15 | 23 | 10 | 22 | 9 | 20 | 21 | 26 | — | — | — | — | — | — | — | |||||||
| Dell Technologies Inc. | -32 | -38 | -44 | -51 | -51 | -49 | -54 | -53 | -49 | -47 | -43 | -48 | — | — | — | — | — | — | — | — | — | — | — | |||||||
| Super Micro Computer Inc. | 98 | 100 | 115 | 133 | 128 | 115 | 113 | 100 | 100 | 91 | 94 | 100 | 90 | 81 | 85 | 78 | — | — | — | — | — | — | — | |||||||
Based on: 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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 Q3 2023 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= 25 + 45 – 27 = 43
2 Click competitor name to see calculations.
Analysis of the quarterly financial data reveals several notable trends and patterns in the working capital management metrics over the observed periods.
- Average Inventory Processing Period
- This metric, representing the average number of days inventory remains before processing, shows relative stability with fluctuations typically between 33 and 41 days across most quarters. A pronounced decline is observed in the quarters of 2022, with values dropping significantly to approximately 19 to 25 days, indicating a more efficient inventory turnover during that period. Post-2022, the inventory days stabilize again around 25 days.
- Average Receivable Collection Period
- This ratio exhibits some variability but generally maintains a range roughly between 40 and 57 days. Notably, there is a peak around late 2020 and early 2021, where the collection period increases above 50 days, suggesting slower collections during that timeframe. A marked improvement occurs in 2022, with collection days dipping near 40 days, indicative of improved receivables management. In the most recent quarters, there is a slight increase but the period settles near the low to mid-40 day range.
- Average Payables Payment Period
- The average days taken to pay suppliers fluctuates between the high 20s and upper 30s throughout the periods. The data shows a peak in mid-2021 with payment periods reaching up to 40 days, reflecting potentially extended payment terms or delayed payables during that quarter. Subsequently, the payment period decreases and stabilizes around the high 20s, indicating a resumption of timely payments in the later periods.
- Cash Conversion Cycle
- The cash conversion cycle (CCC), which reflects the net time to convert resource inputs into cash flows, generally ranges from approximately 33 to 61 days. A clear peak occurs around 2019 and 2020, where the CCC exceeds 55 days in several quarters, suggesting less efficient working capital usage during that period. Notably, a substantial improvement is detected during 2022, where CCC decreases sharply to the low 30s and 40s, driven primarily by reduced inventory days and improved receivables performance. The CCC then experiences a slight increase but remains lower than earlier peak levels, indicating enhanced overall cash flow efficiency in the most recent quarters.
Overall, the data describes a working capital cycle experiencing inefficiencies around the 2019 to 2020 period, followed by marked improvements, particularly in 2022, characterized by reduced inventory and receivable periods alongside stable payables payment periods. The improvements in the cash conversion cycle suggest strengthened operational efficiency and potentially better liquidity management in recent years.