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)
SolarEdge Technologies Inc., short-term (operating) activity ratios (quarterly data)
Based on: 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).
- Inventory Turnover
- The inventory turnover ratio shows a general decline from 6.37 in December 2018 to 3.11 by December 2022. Early in the period, turnover peaked at 6.37 but then decreased steadily, indicating a slower movement of inventory over time. This suggests potential challenges in inventory management or slowing sales affecting the frequency of inventory replacement.
- Receivables Turnover
- Receivables turnover exhibited volatility with an initial decline from 5.4 in March 2019 to a low of 3.27 in June 2022. Notably, there was a peak around September 2020 reaching 8.76, followed by a downward trend. The overall decrease in turnover ratio points to longer collection periods and potentially weakened efficiency in receivables collection over the analyzed quarters.
- Payables Turnover
- The payables turnover ratio fluctuated but generally maintained a range between approximately 5 and 8. Peaks at 8.4 in December 2020 and 8.65 in December 2021 suggest periods of more rapid payment to suppliers, which later slowed down, reflected in a drop to 4.93 by December 2022. This variability may reflect changes in payment policies or operational cash management strategies over time.
- Working Capital Turnover
- Working capital turnover ratio declined significantly from a high of 2.87 in March 2020 to around 1.12 in December 2020. Post this low point, some recovery is evident reaching 1.66 in December 2021, but the ratio stabilized at relatively lower levels (around 1.5) thereafter. This trend suggests a weakening in the efficiency of using working capital to generate sales.
- Average Inventory Processing Period
- The average number of days to process inventory increased markedly from 57 days in December 2018 to a peak of 128 days in March 2021, followed by modest fluctuations around 100 days towards the end of the period. This indicates an elongation of inventory holding periods and slower inventory turnover, which may imply excess inventory or slower sales.
- Average Receivable Collection Period
- The average receivable collection period lengthened from 68 days in March 2019 to over 100 days by the end of 2022. After some improvement mid-period, the trend reversed, indicating increasing delays in collecting payments from customers, which could impact cash flows.
- Operating Cycle
- The operating cycle showed a general upward trend, increasing from approximately 141 days in December 2018 to 223 days by December 2022. This lengthening operating cycle reflects longer times to convert inventory and receivables into cash, suggesting decreased operational efficiency over time.
- Average Payables Payment Period
- The average payables payment period varied widely, with a notable decline from 63 days in March 2019 to a low around 42 days in December 2021, followed by a rebound to 74 days by December 2022. These fluctuations indicate varying strategies in managing payment terms, with a trend towards longer payment periods in the most recent quarters, which could be used to conserve cash.
- Cash Conversion Cycle
- The cash conversion cycle lengthened considerably from 85 days in December 2018 to about 149 days at the end of 2022. This increase is driven by slower inventory turnover and longer receivable collection periods, partially offset by some management of payables. A longer cash conversion cycle suggests increased capital tied up in the operating cycle, potentially impacting liquidity.
Turnover Ratios
Average No. Days
Inventory Turnover
SolarEdge Technologies Inc., inventory turnover calculation (quarterly data)
| 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 revenues | 629,655) | 614,722) | 545,132) | 476,122) | 391,424) | 353,843) | 323,865) | 265,415) | 247,782) | 230,032) | 228,888) | 291,210) | 274,974) | 271,247) | 214,340) | 185,761) | 183,959) | 158,596) | 145,172) | 130,274) | ||||||
| Inventories, net | 729,201) | 561,352) | 470,272) | 432,504) | 380,143) | 304,713) | 321,915) | 340,038) | 331,696) | 297,027) | 264,460) | 198,557) | 170,798) | 134,283) | 148,892) | 150,798) | 141,519) | 107,179) | 102,014) | 98,363) | ||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||
| Inventory turnover1 | 3.11 | 3.61 | 3.76 | 3.57 | 3.51 | 3.91 | 3.31 | 2.86 | 3.01 | 3.45 | 4.03 | 5.30 | 5.54 | 6.37 | 4.99 | 4.47 | 4.37 | — | — | — | ||||||
| Benchmarks | ||||||||||||||||||||||||||
| Inventory Turnover, Competitors2 | ||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | 3.45 | 3.62 | 4.24 | 4.00 | 4.35 | 4.15 | 4.10 | 3.81 | 3.87 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Analog Devices Inc. | 3.20 | 3.82 | 3.78 | 3.66 | 2.33 | 3.16 | 3.16 | 3.18 | 3.14 | 3.12 | 3.23 | 3.28 | 3.24 | — | — | — | — | — | — | — | ||||||
| Applied Materials Inc. | 2.33 | 2.42 | 2.60 | 2.79 | 2.82 | 2.80 | 2.65 | 2.55 | 2.44 | 2.30 | 2.32 | 2.43 | 2.37 | — | — | — | — | — | — | — | ||||||
| Broadcom Inc. | 5.77 | 5.92 | 6.40 | 6.95 | 8.18 | 9.10 | 10.44 | 11.01 | 10.34 | 9.51 | 10.76 | 10.73 | 11.57 | — | — | — | — | — | — | — | ||||||
| Intel Corp. | 2.74 | 2.90 | 3.02 | 2.97 | 3.27 | 3.50 | 3.91 | 4.15 | 4.06 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| KLA Corp. | 1.67 | 1.71 | 1.75 | 1.73 | 1.76 | 1.81 | 1.76 | 1.77 | 1.87 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Lam Research Corp. | 2.36 | 2.60 | 2.89 | 2.95 | 2.91 | 2.78 | 2.71 | 2.77 | 2.86 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Micron Technology Inc. | 2.53 | 3.06 | 3.14 | 3.60 | 3.85 | 3.73 | 3.43 | 2.74 | 2.65 | 2.66 | 2.62 | 2.67 | 2.48 | — | — | — | — | — | — | — | ||||||
| NVIDIA Corp. | 3.62 | 3.87 | 3.75 | 3.63 | 3.44 | 3.69 | 3.47 | 3.81 | 4.24 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Qualcomm Inc. | 2.94 | 3.27 | 3.58 | 3.90 | 4.42 | 4.18 | 4.41 | 4.17 | 3.56 | 3.67 | 5.08 | 6.00 | 6.14 | — | — | — | — | — | — | — | ||||||
| Texas Instruments Inc. | 2.27 | 2.56 | 2.74 | 2.88 | 3.12 | 3.18 | 3.12 | 2.88 | 2.66 | — | — | — | — | — | — | — | — | — | — | — | ||||||
Based on: 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 Q4 2022 Calculation
Inventory turnover
= (Cost of revenuesQ4 2022
+ Cost of revenuesQ3 2022
+ Cost of revenuesQ2 2022
+ Cost of revenuesQ1 2022)
÷ Inventories, net
= (629,655 + 614,722 + 545,132 + 476,122)
÷ 729,201 = 3.11
2 Click competitor name to see calculations.
The analysis of the quarterly financial data reveals several notable trends in cost of revenues, inventories, and inventory turnover over the examined time frame.
- Cost of Revenues
-
There is a clear upward trajectory in the cost of revenues from March 2018 through December 2022. Starting at approximately $130 million, the figure rose steadily, reaching nearly $630 million by the end of 2022. Notwithstanding some quarter-to-quarter fluctuations, this increase reflects a consistent growth in production or sales volume, or potentially rising input costs. The most pronounced increments appear from early 2021 onwards, indicating either accelerated sales growth or increased operational expenses during that period.
- Inventories, Net
-
Net inventories exhibited a similar ascending pattern over the period. From approximately $98 million in the first quarter of 2018, inventories increased sharply to just over $729 million by the final quarter of 2022. This rise in inventory levels outpaced the cost of revenues growth, especially during 2021 and 2022, which may suggest stockpiling or delays in sales. Quarterly data also show periods of pronounced increases, particularly in early 2021 and throughout 2022, demonstrating a possible strategic buildup of inventory or supply chain adjustments.
- Inventory Turnover
-
Inventory turnover ratios, calculated for portions of the timeline starting in late 2018, indicate a variable but generally declining trend over the subsequent quarters. Initially, turnover ratios ranged between roughly 4.4 to 6.4 times per year, peaking at 6.37 in December 2018. Post that peak, turnover ratios declined steadily and stabilized between approximately 3 and 4 times per year from 2020 onwards, with a slight recovery in late 2021 followed by a gradual decrease again through 2022. This declining turnover implies that inventory is being sold less frequently relative to its level, which aligns with the substantial inventory accumulation observed and could imply slower sales or increased stocking periods.
In summary, the data suggests robust growth in the scale of operations as reflected by rising cost of revenues and inventory levels. However, the declining inventory turnover ratios may signal inefficiencies in inventory management, potential overstocking, or slower demand absorption in recent periods. Attention may be warranted to optimize inventory levels and turnover to support operational efficiency and liquidity.
Receivables Turnover
SolarEdge Technologies Inc., receivables turnover calculation (quarterly data)
| 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) | ||||||||||||||||||||||||||
| Revenues | 890,702) | 836,723) | 727,774) | 655,080) | 551,915) | 526,404) | 480,057) | 405,489) | 358,107) | 338,095) | 331,851) | 431,218) | 418,223) | 410,556) | 325,010) | 271,871) | 263,670) | 236,578) | 227,118) | 209,871) | ||||||
| Trade receivables, net of allowances | 905,146) | 785,325) | 669,100) | 676,820) | 456,339) | 416,244) | 343,652) | 271,713) | 218,706) | 183,141) | 181,700) | 235,673) | 298,383) | 292,232) | 237,804) | 187,496) | 173,579) | 151,088) | 118,103) | 127,479) | ||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||
| Receivables turnover1 | 3.44 | 3.53 | 3.68 | 3.27 | 4.30 | 4.25 | 4.60 | 5.28 | 6.67 | 8.30 | 8.76 | 6.73 | 4.78 | 4.35 | 4.61 | 5.33 | 5.40 | — | — | — | ||||||
| Benchmarks | ||||||||||||||||||||||||||
| Receivables Turnover, Competitors2 | ||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | 5.72 | 5.26 | 5.33 | 5.13 | 6.07 | 6.68 | 6.60 | 5.24 | 4.73 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Analog Devices Inc. | 6.67 | 6.37 | 6.07 | 5.16 | 5.02 | 7.90 | 7.62 | 7.08 | 7.60 | 8.10 | 9.42 | 9.85 | 9.43 | — | — | — | — | — | — | — | ||||||
| Applied Materials Inc. | 4.25 | 5.08 | 5.09 | 5.49 | 4.66 | 5.66 | 5.87 | 5.98 | 5.81 | 5.80 | 5.88 | 5.61 | 5.77 | — | — | — | — | — | — | — | ||||||
| Broadcom Inc. | 11.22 | 11.70 | 9.73 | 11.23 | 13.25 | 11.87 | 10.54 | 9.78 | 10.40 | 8.64 | 7.13 | 6.21 | 6.93 | — | — | — | — | — | — | — | ||||||
| Intel Corp. | 15.26 | 9.31 | 12.11 | 10.98 | 8.36 | 9.34 | 10.40 | 10.78 | 11.48 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| KLA Corp. | 5.08 | 5.34 | 4.72 | 5.10 | 5.30 | 5.37 | 4.98 | 5.77 | 5.24 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Lam Research Corp. | 3.99 | 4.52 | 4.86 | 4.64 | 4.83 | 4.72 | 4.11 | 4.77 | 4.79 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Micron Technology Inc. | 6.00 | 5.20 | 5.79 | 5.64 | 5.22 | 6.02 | 7.01 | 5.98 | 5.48 | 5.62 | 6.43 | 6.04 | 7.33 | — | — | — | — | — | — | — | ||||||
| NVIDIA Corp. | 5.79 | 6.14 | 6.11 | 6.37 | 6.86 | 5.80 | 6.27 | 6.18 | 6.59 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Texas Instruments Inc. | 10.57 | 9.90 | 8.95 | 10.56 | 10.78 | 10.64 | 10.54 | 9.74 | 10.23 | — | — | — | — | — | — | — | — | — | — | — | ||||||
Based on: 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 Q4 2022 Calculation
Receivables turnover
= (RevenuesQ4 2022
+ RevenuesQ3 2022
+ RevenuesQ2 2022
+ RevenuesQ1 2022)
÷ Trade receivables, net of allowances
= (890,702 + 836,723 + 727,774 + 655,080)
÷ 905,146 = 3.44
2 Click competitor name to see calculations.
The quarterly financial data reveals several key trends in the company's revenue, trade receivables, and receivables turnover over the observed periods.
- Revenues
-
Revenue figures demonstrate a consistent and substantial upward trajectory from March 2018 through December 2022. Starting at approximately $210 million in the first quarter of 2018, revenues increased steadily each quarter, reaching nearly $891 million by the fourth quarter of 2022. This growth reflects a more than fourfold increase over the period, indicating robust expansion. Notably, there was a minor dip in the second quarter of 2020, likely reflecting external challenges during that period, followed by a strong recovery and accelerated growth thereafter.
- Trade Receivables, Net of Allowances
-
Trade receivables also followed a generally increasing pattern, rising from around $127 million in March 2018 to over $905 million by December 2022. This significant increase parallels the revenue growth but also suggests an expanding amount of outstanding customer balances. A temporary decline in mid-2020 corresponds with a revenue dip then, but since that time, trade receivables resumed growth, accelerating particularly from early 2021 onwards. The sharp rise in trade receivables in the final quarters suggests a lengthening in the collection cycle or increased credit sales.
- Receivables Turnover Ratio
-
The receivables turnover ratio, which measures how efficiently the company collects its receivables, shows a downward trend from early 2018 through the end of 2022. Initial values in the 5.4 to 4.3 range during 2018 and 2019 increased temporarily to a peak of 8.76 in the third quarter of 2020, indicating rapid collection of receivables during that period. However, post-2020, this ratio steadily declined to approximately 3.44 by the end of 2022. The decreasing turnover ratio over the recent quarters indicates that receivables are being collected more slowly, which may point to extended payment terms offered to customers or difficulties in collection efficiency despite rising revenues.
In summary, while the company has demonstrated strong revenue growth through the period, the corresponding increase in trade receivables and decreasing receivables turnover ratio suggest a trend toward slower collection practices or increased credit risk. This combination warrants closer monitoring of working capital management and credit policies to sustain financial health amidst rapid sales expansion.
Payables Turnover
SolarEdge Technologies Inc., payables turnover calculation (quarterly data)
| 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 revenues | 629,655) | 614,722) | 545,132) | 476,122) | 391,424) | 353,843) | 323,865) | 265,415) | 247,782) | 230,032) | 228,888) | 291,210) | 274,974) | 271,247) | 214,340) | 185,761) | 183,959) | 158,596) | 145,172) | 130,274) | ||||||
| Trade payables, net | 459,831) | 311,565) | 253,399) | 241,630) | 252,068) | 137,621) | 141,174) | 122,063) | 162,051) | 122,106) | 158,264) | 139,138) | 157,148) | 132,230) | 116,795) | 90,190) | 107,079) | 83,459) | 81,610) | 83,091) | ||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||
| Payables turnover1 | 4.93 | 6.51 | 6.97 | 6.40 | 5.29 | 8.65 | 7.56 | 7.96 | 6.16 | 8.40 | 6.74 | 7.56 | 6.02 | 6.47 | 6.36 | 7.47 | 5.77 | — | — | — | ||||||
| Benchmarks | ||||||||||||||||||||||||||
| Payables Turnover, Competitors2 | ||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | 4.40 | 4.46 | 5.97 | 5.78 | 6.05 | 7.29 | 8.31 | 6.38 | 9.92 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Analog Devices Inc. | 7.70 | 8.43 | 9.01 | 8.17 | 6.30 | 7.82 | 7.25 | 8.66 | 8.42 | 8.85 | 9.83 | 9.12 | 8.78 | — | — | — | — | — | — | — | ||||||
| Broadcom Inc. | 11.13 | 15.27 | 9.98 | 9.80 | 9.77 | 10.91 | 12.63 | 11.67 | 12.41 | 9.41 | 8.33 | 10.28 | 11.83 | — | — | — | — | — | — | — | ||||||
| Intel Corp. | 3.77 | 5.21 | 4.63 | 4.92 | 6.13 | 5.05 | 5.82 | 6.49 | 6.14 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| KLA Corp. | 8.10 | 7.98 | 8.43 | 7.79 | 8.10 | 8.88 | 9.53 | 9.69 | 9.27 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Lam Research Corp. | 9.25 | 8.99 | 9.31 | 10.12 | 9.43 | 9.33 | 8.82 | 8.94 | 9.18 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| NVIDIA Corp. | 5.29 | 5.19 | 5.38 | 5.94 | 5.23 | 5.03 | 5.44 | 5.65 | 6.04 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Qualcomm Inc. | 4.91 | 4.72 | 4.37 | 4.28 | 5.19 | 4.83 | 4.62 | 4.38 | 4.12 | 4.21 | 4.19 | 4.96 | 6.29 | — | — | — | — | — | — | — | ||||||
| Texas Instruments Inc. | 7.35 | 7.89 | 8.46 | 9.27 | 9.14 | 9.93 | 9.86 | 9.60 | 12.51 | — | — | — | — | — | — | — | — | — | — | — | ||||||
Based on: 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 Q4 2022 Calculation
Payables turnover
= (Cost of revenuesQ4 2022
+ Cost of revenuesQ3 2022
+ Cost of revenuesQ2 2022
+ Cost of revenuesQ1 2022)
÷ Trade payables, net
= (629,655 + 614,722 + 545,132 + 476,122)
÷ 459,831 = 4.93
2 Click competitor name to see calculations.
- Cost of Revenues
- The cost of revenues demonstrated a consistent upward trend throughout the observed quarters. Starting at approximately 130 million USD in the first quarter of 2018, the cost rose progressively to reach over 629 million USD by the end of 2022. Notable periods of accelerated growth occurred between mid-2019 and 2020, and again from early 2021 through 2022, reflecting a significant expansion in cost base over time.
- Trade Payables, Net
- Trade payables showed more variability but followed an overall increasing pattern. Initial levels around 83 million USD in early 2018 fluctuated moderately until late 2019, after which a sharp increase was observed. By the end of 2022, trade payables surged to approximately 460 million USD, indicating intensified short-term liabilities or increased procurement activities. Peaks and troughs occurred intermittently, suggesting fluctuating payment cycles or working capital management changes during the periods.
- Payables Turnover Ratio
- The payables turnover ratio, which measures how frequently the company pays off its suppliers, exhibited considerable variation across quarters. The ratio ranged roughly between 4.93 and 8.65, with no clear linear trend. Noteworthy observations include a peak turnover ratio above 8.4 in late 2020 and late 2021, contrasting with lower turnover around 5.29 and 4.93 in early 2022 and late 2022, respectively. This variability may reflect changing payment policies, negotiation terms with suppliers, or cash flow management strategies over time.
- Overall Insights
- The combined data reveals that while both cost of revenues and trade payables escalated significantly over the five-year period, the payables turnover ratio fluctuated without a clear directional trend. The steady rise in costs and payables suggests business growth or expanded operational scale, whereas the inconsistent payables turnover ratio points to varying efficiency or strategies in managing supplier payments. The large increase in trade payables relative to cost of revenues toward the end of the period may merit further investigation to assess potential impacts on liquidity and supplier relations.
Working Capital Turnover
SolarEdge Technologies Inc., working capital turnover calculation (quarterly data)
| 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 | 2,899,658) | 2,451,773) | 2,283,808) | 2,462,317) | 1,711,291) | 1,552,554) | 1,488,911) | 1,585,107) | 1,719,341) | 1,744,981) | 1,072,998) | 955,919) | 932,763) | 834,803) | 730,544) | 717,532) | 678,113) | 655,653) | 616,047) | 571,212) | ||||||
| Less: Current liabilities | 889,717) | 694,480) | 612,174) | 568,741) | 525,181) | 405,507) | 399,585) | 397,726) | 436,099) | 382,537) | 405,065) | 389,681) | 436,714) | 335,407) | 293,778) | 248,072) | 225,718) | 166,150) | 153,971) | 158,609) | ||||||
| Working capital | 2,009,941) | 1,757,293) | 1,671,634) | 1,893,576) | 1,186,110) | 1,147,047) | 1,089,326) | 1,187,381) | 1,283,242) | 1,362,444) | 667,933) | 566,238) | 496,049) | 499,396) | 436,766) | 469,460) | 452,395) | 489,503) | 462,076) | 412,603) | ||||||
| Revenues | 890,702) | 836,723) | 727,774) | 655,080) | 551,915) | 526,404) | 480,057) | 405,489) | 358,107) | 338,095) | 331,851) | 431,218) | 418,223) | 410,556) | 325,010) | 271,871) | 263,670) | 236,578) | 227,118) | 209,871) | ||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||
| Working capital turnover1 | 1.55 | 1.58 | 1.47 | 1.17 | 1.66 | 1.54 | 1.45 | 1.21 | 1.14 | 1.12 | 2.38 | 2.80 | 2.87 | 2.55 | 2.51 | 2.13 | 2.07 | — | — | — | ||||||
| Benchmarks | ||||||||||||||||||||||||||
| Working Capital Turnover, Competitors2 | ||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | 2.73 | 2.95 | 2.72 | 2.42 | 3.78 | 3.36 | 2.71 | 2.64 | 2.62 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Analog Devices Inc. | 4.81 | 4.94 | 4.23 | 3.50 | 2.81 | 21.89 | 49.24 | 6.18 | 4.86 | 6.92 | 11.81 | 40.91 | 12.57 | — | — | — | — | — | — | — | ||||||
| Applied Materials Inc. | 3.02 | 2.93 | 2.89 | 2.56 | 2.36 | 2.14 | 1.95 | 1.86 | 1.93 | 2.04 | 1.94 | 2.42 | 2.54 | — | — | — | — | — | — | — | ||||||
| Broadcom Inc. | 2.90 | 3.58 | 3.80 | 3.15 | 2.66 | 2.90 | 3.27 | 3.25 | 4.32 | 3.32 | 3.00 | 5.19 | 7.49 | — | — | — | — | — | — | — | ||||||
| Intel Corp. | 3.45 | 3.24 | 3.14 | 2.34 | 2.61 | 2.47 | 3.16 | 3.59 | 3.46 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| KLA Corp. | 2.14 | 2.30 | 2.08 | 2.06 | 1.93 | 1.91 | 1.90 | 1.97 | 1.92 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Lam Research Corp. | 2.23 | 2.18 | 2.01 | 2.04 | 1.80 | 1.72 | 1.51 | 1.41 | 1.31 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Micron Technology Inc. | 2.16 | 2.06 | 2.14 | 2.17 | 2.05 | 1.95 | 1.98 | 2.04 | 1.89 | 1.73 | 1.93 | 2.10 | 2.31 | — | — | — | — | — | — | — | ||||||
| NVIDIA Corp. | 1.10 | 1.09 | 1.03 | 1.36 | 1.37 | 1.38 | 1.06 | 0.67 | 0.92 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Qualcomm Inc. | 4.99 | 5.88 | 4.80 | 4.53 | 4.13 | 3.96 | 3.19 | 2.53 | 2.39 | 2.62 | 4.47 | 3.50 | 3.10 | — | — | — | — | — | — | — | ||||||
| Texas Instruments Inc. | 1.81 | 1.84 | 1.87 | 1.65 | 1.65 | 1.57 | 1.87 | 1.77 | 1.84 | — | — | — | — | — | — | — | — | — | — | — | ||||||
Based on: 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 Q4 2022 Calculation
Working capital turnover
= (RevenuesQ4 2022
+ RevenuesQ3 2022
+ RevenuesQ2 2022
+ RevenuesQ1 2022)
÷ Working capital
= (890,702 + 836,723 + 727,774 + 655,080)
÷ 2,009,941 = 1.55
2 Click competitor name to see calculations.
- Working Capital
- The working capital has exhibited a generally upward trend from March 2018 to December 2022. Starting at approximately 412 million USD in early 2018, it increased steadily, with a notable acceleration in growth from mid-2020 onward. By December 2022, working capital reached over 2 billion USD, indicating improved short-term financial health and liquidity over these periods. Some fluctuations are observed, such as a slight dip in late 2019, but the overall direction is strongly positive.
- Revenues
- Revenues followed a generally increasing trajectory across the analyzed quarters. Starting from about 210 million USD in March 2018, revenues experienced significant growth, with occasional modest drops such as in the second quarter of 2020. The trend post-2020 recovered strongly and accelerated, reaching close to 891 million USD by December 2022. This indicates effective sales performance and possibly expanding market penetration or product adoption during the period.
- Working Capital Turnover Ratio
- The working capital turnover ratio shows more variability and a generally declining trend compared to working capital and revenues. The ratio began above 2.0 in early 2019, peaked close to 2.9 in early 2020, then dropped sharply to below 1.2 by the end of 2020. Subsequently, it stabilized in the range of approximately 1.1 to 1.7 through 2021 and 2022, with no clear upward movement. This declining and volatile pattern suggests that while working capital and revenues increased, the efficiency of generating revenue from working capital investments diminished over time.
- Summary Insights
- The company demonstrated strong growth in both working capital and revenues between 2018 and 2022, reflecting an expanding operational scale and market success. However, the decreasing and fluctuating working capital turnover ratio indicates a reduced efficiency in using working capital to generate sales, particularly after early 2020. This might point to increasing investments in current assets or a strategic shift affecting operational efficiency. Management may need to investigate the operational factors driving this trend to optimize asset utilization and sustain revenue growth while managing working capital effectively.
Average Inventory Processing Period
SolarEdge Technologies Inc., average inventory processing period calculation (quarterly data)
| 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 | 3.11 | 3.61 | 3.76 | 3.57 | 3.51 | 3.91 | 3.31 | 2.86 | 3.01 | 3.45 | 4.03 | 5.30 | 5.54 | 6.37 | 4.99 | 4.47 | 4.37 | — | — | — | ||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||
| Average inventory processing period1 | 117 | 101 | 97 | 102 | 104 | 93 | 110 | 128 | 121 | 106 | 91 | 69 | 66 | 57 | 73 | 82 | 84 | — | — | — | ||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||
| Average Inventory Processing Period, Competitors2 | ||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | 106 | 101 | 86 | 91 | 84 | 88 | 89 | 96 | 94 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Analog Devices Inc. | 114 | 96 | 97 | 100 | 157 | 115 | 116 | 115 | 116 | 117 | 113 | 111 | 113 | — | — | — | — | — | — | — | ||||||
| Applied Materials Inc. | 157 | 151 | 140 | 131 | 129 | 130 | 138 | 143 | 150 | 159 | 157 | 150 | 154 | — | — | — | — | — | — | — | ||||||
| Broadcom Inc. | 63 | 62 | 57 | 53 | 45 | 40 | 35 | 33 | 35 | 38 | 34 | 34 | 32 | — | — | — | — | — | — | — | ||||||
| Intel Corp. | 133 | 126 | 121 | 123 | 112 | 104 | 93 | 88 | 90 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| KLA Corp. | 218 | 214 | 208 | 211 | 207 | 202 | 207 | 206 | 195 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Lam Research Corp. | 155 | 140 | 126 | 124 | 126 | 131 | 135 | 132 | 128 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Micron Technology Inc. | 144 | 119 | 116 | 101 | 95 | 98 | 106 | 133 | 138 | 137 | 139 | 137 | 147 | — | — | — | — | — | — | — | ||||||
| NVIDIA Corp. | 101 | 94 | 97 | 100 | 106 | 99 | 105 | 96 | 86 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Qualcomm Inc. | 124 | 112 | 102 | 93 | 83 | 87 | 83 | 88 | 102 | 99 | 72 | 61 | 59 | — | — | — | — | — | — | — | ||||||
| Texas Instruments Inc. | 161 | 143 | 133 | 127 | 117 | 115 | 117 | 127 | 137 | — | — | — | — | — | — | — | — | — | — | — | ||||||
Based on: 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 Q4 2022 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ 3.11 = 117
2 Click competitor name to see calculations.
The analysis of the inventory turnover ratio and average inventory processing period reveals notable trends over the observed quarters.
- Inventory Turnover Ratio
- The inventory turnover ratio showed an initial upward trend beginning in the first quarter of 2019, reaching a peak at 6.37 by the last quarter of 2019. This indicates an improvement in the rate at which inventory was sold and replaced during this period. However, starting in 2020, the turnover ratio declined substantially, dropping to 3.01 by the first quarter of 2021. A slight recovery is observed in subsequent quarters, with the ratio fluctuating between approximately 3.1 and 3.9 from mid-2021 through to the end of 2022, though it did not return to the peak levels seen in 2019.
- Average Inventory Processing Period
- Corresponding with the changes in inventory turnover, the average inventory processing period exhibited an inverse trend. From early 2019 through 2019, the days decreased from 84 to a minimum of 57, consistent with more efficient inventory management. However, beginning in 2020, the processing period lengthened significantly, increasing from 66 days at the start to a peak of 128 days in the second quarter of 2021. Following this peak, there was some improvement, with the period reducing to 93 days by the fourth quarter of 2021, but it then stabilized around 100 days through 2022, indicating a sustained lengthening compared to the 2019 levels.
Overall, the data suggest that the company experienced more efficient inventory turnover and faster processing periods in 2019. Beginning in 2020, there was a notable decline in inventory turnover efficiency, accompanied by longer inventory holding times which persisted through 2022. This shift may reflect changes in operations, market conditions, or supply chain dynamics impacting inventory management effectiveness during this later period.
Average Receivable Collection Period
SolarEdge Technologies Inc., average receivable collection period calculation (quarterly data)
| 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 | 3.44 | 3.53 | 3.68 | 3.27 | 4.30 | 4.25 | 4.60 | 5.28 | 6.67 | 8.30 | 8.76 | 6.73 | 4.78 | 4.35 | 4.61 | 5.33 | 5.40 | — | — | — | ||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||
| Average receivable collection period1 | 106 | 103 | 99 | 112 | 85 | 86 | 79 | 69 | 55 | 44 | 42 | 54 | 76 | 84 | 79 | 68 | 68 | — | — | — | ||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||
| Average Receivable Collection Period, Competitors2 | ||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | 64 | 69 | 69 | 71 | 60 | 55 | 55 | 70 | 77 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Analog Devices Inc. | 55 | 57 | 60 | 71 | 73 | 46 | 48 | 52 | 48 | 45 | 39 | 37 | 39 | — | — | — | — | — | — | — | ||||||
| Applied Materials Inc. | 86 | 72 | 72 | 67 | 78 | 65 | 62 | 61 | 63 | 63 | 62 | 65 | 63 | — | — | — | — | — | — | — | ||||||
| Broadcom Inc. | 33 | 31 | 38 | 33 | 28 | 31 | 35 | 37 | 35 | 42 | 51 | 59 | 53 | — | — | — | — | — | — | — | ||||||
| Intel Corp. | 24 | 39 | 30 | 33 | 44 | 39 | 35 | 34 | 32 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| KLA Corp. | 72 | 68 | 77 | 72 | 69 | 68 | 73 | 63 | 70 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Lam Research Corp. | 91 | 81 | 75 | 79 | 76 | 77 | 89 | 77 | 76 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Micron Technology Inc. | 61 | 70 | 63 | 65 | 70 | 61 | 52 | 61 | 67 | 65 | 57 | 60 | 50 | — | — | — | — | — | — | — | ||||||
| NVIDIA Corp. | 63 | 59 | 60 | 57 | 53 | 63 | 58 | 59 | 55 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Texas Instruments Inc. | 35 | 37 | 41 | 35 | 34 | 34 | 35 | 37 | 36 | — | — | — | — | — | — | — | — | — | — | — | ||||||
Based on: 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 Q4 2022 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ 3.44 = 106
2 Click competitor name to see calculations.
The receivables turnover ratio exhibits a generally declining trend over the observed quarters, starting at 5.4 and decreasing to approximately 3.44 by the end of the period. Notably, the ratio peaked around mid-2020, reaching values above 8, before entering a steady downward trajectory through 2021 and 2022.
Correspondingly, the average receivable collection period shows an inverse pattern, reflecting longer collection times over the same timeframe. Initially near 68 days, the period increased significantly, surpassing 100 days in the last quarters assessed. This indicates a lengthening in the time it takes to collect receivables toward the end of the analysis period.
- Receivables Turnover Ratio
- Started strong in early data points post-2018, with values around 5.4, peaked significantly during mid-2020 reaching highs near 8.76, then declined consistently through 2021 and 2022 toward the mid-3 range.
- Average Receivable Collection Period
- Initially stable near 68 days, the collection period dropped temporarily to as low as 42 days in late 2020, then increased steadily to over 100 days by late 2022, indicating slower collections.
The inverse relationship between these two metrics suggests a deterioration in receivables management or collection efficiency over the observed periods, with collections becoming slower and turnover decreasing. This trend may warrant further investigation to identify underlying causes, such as changes in credit policy, customer payment behavior, or economic conditions impacting receivables.
Operating Cycle
SolarEdge Technologies Inc., operating cycle calculation (quarterly data)
No. days
| 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 | 117 | 101 | 97 | 102 | 104 | 93 | 110 | 128 | 121 | 106 | 91 | 69 | 66 | 57 | 73 | 82 | 84 | — | — | — | ||||||
| Average receivable collection period | 106 | 103 | 99 | 112 | 85 | 86 | 79 | 69 | 55 | 44 | 42 | 54 | 76 | 84 | 79 | 68 | 68 | — | — | — | ||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||
| Operating cycle1 | 223 | 204 | 196 | 214 | 189 | 179 | 189 | 197 | 176 | 150 | 133 | 123 | 142 | 141 | 152 | 150 | 152 | — | — | — | ||||||
| Benchmarks | ||||||||||||||||||||||||||
| Operating Cycle, Competitors2 | ||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | 170 | 170 | 155 | 162 | 144 | 143 | 144 | 166 | 171 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Analog Devices Inc. | 169 | 153 | 157 | 171 | 230 | 161 | 164 | 167 | 164 | 162 | 152 | 148 | 152 | — | — | — | — | — | — | — | ||||||
| Applied Materials Inc. | 243 | 223 | 212 | 198 | 207 | 195 | 200 | 204 | 213 | 222 | 219 | 215 | 217 | — | — | — | — | — | — | — | ||||||
| Broadcom Inc. | 96 | 93 | 95 | 86 | 73 | 71 | 70 | 70 | 70 | 80 | 85 | 93 | 85 | — | — | — | — | — | — | — | ||||||
| Intel Corp. | 157 | 165 | 151 | 156 | 156 | 143 | 128 | 122 | 122 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| KLA Corp. | 290 | 282 | 285 | 283 | 276 | 270 | 280 | 269 | 265 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Lam Research Corp. | 246 | 221 | 201 | 203 | 202 | 208 | 224 | 209 | 204 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Micron Technology Inc. | 205 | 189 | 179 | 166 | 165 | 159 | 158 | 194 | 205 | 202 | 196 | 197 | 197 | — | — | — | — | — | — | — | ||||||
| NVIDIA Corp. | 164 | 153 | 157 | 157 | 159 | 162 | 163 | 155 | 141 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Texas Instruments Inc. | 196 | 180 | 174 | 162 | 151 | 149 | 152 | 164 | 173 | — | — | — | — | — | — | — | — | — | — | — | ||||||
Based on: 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 Q4 2022 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= 117 + 106 = 223
2 Click competitor name to see calculations.
The financial data reveals observable trends in key operational metrics over multiple quarterly periods.
- Average Inventory Processing Period
-
Initially starting from 84 days in March 2019, the inventory processing period exhibits a general upward trend with some fluctuations. It decreased to a low of 57 days by December 2019, suggesting improved inventory turnover efficiency during that period. However, beginning in early 2020, the period extended significantly, reaching a peak of 128 days by March 2021. Although it slightly improved afterward, inventory days remained elevated, fluctuating between 93 and 117 days through the end of 2022. This suggests that inventory was held longer on average in recent years, which may indicate challenges in inventory management or changes in demand patterns.
- Average Receivable Collection Period
-
The receivable collection period remained relatively stable at approximately 68 days during early 2019, followed by an increase to 79 and 84 days mid-2019 reflecting slower collections. A notable decrease occurred through 2020, reaching the lowest levels of 42 to 44 days in mid and late 2020, indicating improved collection efficiency. Subsequently, there was a gradual and consistent increase starting late 2020 through 2022, peaking at 112 days by mid-2022. This rise denotes a lengthening of the time customers take to settle payments, potentially impacting cash flow negatively.
- Operating Cycle
-
The operating cycle, representing the sum of inventory processing and receivable collection periods, demonstrates considerable variability. It hovered around 150 days through 2019, decreased somewhat in early 2020 but then surged considerably, reaching a peak of 223 days by the end of 2022. This trend indicates that the overall cash conversion process has become significantly longer over time, which could constrain liquidity and operational flexibility.
In summary, while there was improvement in both inventory and receivables turnover in certain periods, particularly in late 2019 for inventory and mid-2020 for receivables, both indicators generally deteriorated afterwards. The prolonged operating cycle in recent periods suggests increased working capital requirements and potential inefficiencies in inventory management and collections processes. Monitoring and managing these durations will be critical for sustaining operational efficiency and financial health.
Average Payables Payment Period
SolarEdge Technologies Inc., average payables payment period calculation (quarterly data)
| 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 | 4.93 | 6.51 | 6.97 | 6.40 | 5.29 | 8.65 | 7.56 | 7.96 | 6.16 | 8.40 | 6.74 | 7.56 | 6.02 | 6.47 | 6.36 | 7.47 | 5.77 | — | — | — | ||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||
| Average payables payment period1 | 74 | 56 | 52 | 57 | 69 | 42 | 48 | 46 | 59 | 43 | 54 | 48 | 61 | 56 | 57 | 49 | 63 | — | — | — | ||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||
| Average Payables Payment Period, Competitors2 | ||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | 83 | 82 | 61 | 63 | 60 | 50 | 44 | 57 | 37 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Analog Devices Inc. | 47 | 43 | 41 | 45 | 58 | 47 | 50 | 42 | 43 | 41 | 37 | 40 | 42 | — | — | — | — | — | — | — | ||||||
| Broadcom Inc. | 33 | 24 | 37 | 37 | 37 | 33 | 29 | 31 | 29 | 39 | 44 | 36 | 31 | — | — | — | — | — | — | — | ||||||
| Intel Corp. | 97 | 70 | 79 | 74 | 60 | 72 | 63 | 56 | 59 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| KLA Corp. | 45 | 46 | 43 | 47 | 45 | 41 | 38 | 38 | 39 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Lam Research Corp. | 39 | 41 | 39 | 36 | 39 | 39 | 41 | 41 | 40 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| NVIDIA Corp. | 69 | 70 | 68 | 61 | 70 | 72 | 67 | 65 | 60 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Qualcomm Inc. | 74 | 77 | 83 | 85 | 70 | 76 | 79 | 83 | 89 | 87 | 87 | 74 | 58 | — | — | — | — | — | — | — | ||||||
| Texas Instruments Inc. | 50 | 46 | 43 | 39 | 40 | 37 | 37 | 38 | 29 | — | — | — | — | — | — | — | — | — | — | — | ||||||
Based on: 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 Q4 2022 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ 4.93 = 74
2 Click competitor name to see calculations.
- Payables Turnover
- The payables turnover ratio exhibits variability over the reported period from March 31, 2019, through December 31, 2022. Initially, the ratio shows an increase from 5.77 to a peak of 8.65 by December 31, 2021, indicating a generally faster rate of paying suppliers during this timeframe. However, following this peak, the ratio experiences a decline to 4.93 by December 31, 2022, suggesting a slowdown in payable turnover at the end of the observed period.
- Average Payables Payment Period
- The average payables payment period tends to move inversely to the payables turnover ratio, as expected. It starts at 63 days in March 31, 2019, decreases to a low of 42 days in December 31, 2021, indicating quicker payments to suppliers during this time. After this, the payment period extends again, reaching 74 days by December 31, 2022, signifying a longer time taken to settle payables towards the end of the analyzed timeframe.
- Overall Trends and Insights
- The data points to a trend of improving supplier payment efficiency through to late 2021, with payables turnover increasing and payment period decreasing, reflecting potentially favorable liquidity conditions or strategic supplier management. However, in 2022, this trend reverses, with slower payables turnover and lengthening payment periods, which could indicate changes in operational cash flow management, supply chain conditions, or strategic cash conservation measures.
Cash Conversion Cycle
SolarEdge Technologies Inc., cash conversion cycle calculation (quarterly data)
No. days
| 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 | 117 | 101 | 97 | 102 | 104 | 93 | 110 | 128 | 121 | 106 | 91 | 69 | 66 | 57 | 73 | 82 | 84 | — | — | — | ||||||
| Average receivable collection period | 106 | 103 | 99 | 112 | 85 | 86 | 79 | 69 | 55 | 44 | 42 | 54 | 76 | 84 | 79 | 68 | 68 | — | — | — | ||||||
| Average payables payment period | 74 | 56 | 52 | 57 | 69 | 42 | 48 | 46 | 59 | 43 | 54 | 48 | 61 | 56 | 57 | 49 | 63 | — | — | — | ||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||
| Cash conversion cycle1 | 149 | 148 | 144 | 157 | 120 | 137 | 141 | 151 | 117 | 107 | 79 | 75 | 81 | 85 | 95 | 101 | 89 | — | — | — | ||||||
| Benchmarks | ||||||||||||||||||||||||||
| Cash Conversion Cycle, Competitors2 | ||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | 87 | 88 | 94 | 99 | 84 | 93 | 100 | 109 | 134 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Analog Devices Inc. | 122 | 110 | 116 | 126 | 172 | 114 | 114 | 125 | 121 | 121 | 115 | 108 | 110 | — | — | — | — | — | — | — | ||||||
| Broadcom Inc. | 63 | 69 | 58 | 49 | 36 | 38 | 41 | 39 | 41 | 41 | 41 | 57 | 54 | — | — | — | — | — | — | — | ||||||
| Intel Corp. | 60 | 95 | 72 | 82 | 96 | 71 | 65 | 66 | 63 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| KLA Corp. | 245 | 236 | 242 | 236 | 231 | 229 | 242 | 231 | 226 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Lam Research Corp. | 207 | 180 | 162 | 167 | 163 | 169 | 183 | 168 | 164 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| NVIDIA Corp. | 95 | 83 | 89 | 96 | 89 | 90 | 96 | 90 | 81 | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Texas Instruments Inc. | 146 | 134 | 131 | 123 | 111 | 112 | 115 | 126 | 144 | — | — | — | — | — | — | — | — | — | — | — | ||||||
Based on: 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 Q4 2022 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= 117 + 106 – 74 = 149
2 Click competitor name to see calculations.
- Average Inventory Processing Period
- The average inventory processing period shows a generally increasing trend from early 2019 through the end of 2020, rising from 84 days in March 2019 to a peak of 128 days in June 2021. Following this peak, the period declines to 93 days by March 2022 but then rises again towards 117 days by December 2022. This pattern suggests fluctuations in inventory turnover efficiency, with a tendency towards longer holding periods in more recent quarters.
- Average Receivable Collection Period
- The average receivable collection period exhibits volatility across the observed periods. Starting at 68 days in March 2019, it peaks at 86 days in September 2021. After a slight decline during late 2021, it increases again in 2022, reaching 106 days by December. This indicates variability in the collection process, with a general tendency toward lengthening payment terms or slower customer payments over time.
- Average Payables Payment Period
- The average payables payment period fluctuates but remains generally below 70 days throughout the observed periods. Initial values in 2019 range between 49 and 63 days, with a decline to mid-40s in 2020 followed by variation in 2021 and 2022. The period rises to 74 days by December 2022, indicating some extension in payment terms granted by suppliers toward the end of the period analyzed.
- Cash Conversion Cycle
- The cash conversion cycle mirrors the combined effect of the other three periods, showing an increasing trend from 89 days in March 2019 to a peak of 151 days in June 2021. While it slightly declines to 120 days by March 2022, it subsequently increases again to 149 days by December 2022. The prolonged cash conversion cycle suggests a lengthening gap between cash outflow and cash inflow, implying potential stress on liquidity or working capital management during this interval.