Activity ratios measure how efficiently a company performs day-to-day tasks, such us the collection of receivables and management of inventory.
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- Statement of Comprehensive Income
- Common-Size Balance Sheet: Liabilities and Stockholders’ Equity
- Analysis of Profitability Ratios
- Analysis of Liquidity Ratios
- Analysis of Solvency Ratios
- Analysis of Long-term (Investment) Activity Ratios
- Common Stock Valuation Ratios
- Net Profit Margin since 2005
- Return on Equity (ROE) since 2005
- Total Asset Turnover since 2005
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Short-term Activity Ratios (Summary)
Based on: 10-Q (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-K (reporting date: 2022-03-31), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-K (reporting date: 2021-03-31), 10-Q (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-K (reporting date: 2020-03-31), 10-Q (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-K (reporting date: 2019-03-31), 10-Q (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-K (reporting date: 2018-03-31), 10-Q (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30).
The financial data reveals multiple trends in key operational efficiency ratios and cycle periods over the observed quarters.
- Inventory Turnover
- The inventory turnover ratio demonstrates an initial decline from 3.72 to 1.58 between mid-2017 and mid-2018, indicating slower inventory movement. Following this trough, the ratio recovered somewhat to around 3.1 during 2020 and early 2021, before steadily declining again to 2.27 by late 2022. This pattern suggests fluctuating inventory management effectiveness with a general trend towards slower stock turnover in recent periods.
- Receivables Turnover
- This ratio fluctuates moderately, generally ranging between 5.35 and 9.22. A peak occurs at 9.22 in late 2017, indicating faster collection of receivables at that time. Subsequently, it settles mostly around 5.5 to 7, showing relatively stable but somewhat slower collections in recent quarters compared to the late 2017 peak.
- Payables Turnover
- The payables turnover ratio shows volatility with a low point of 5.48 in mid-2018 and peaks near 10.83 in early 2018. From 2019 onward, the ratio generally trends downward from around 9.69 to the 6–8 range, suggesting the company is taking longer to pay its suppliers in recent periods.
- Working Capital Turnover
- Data availability is limited and irregular for this ratio, with notable spikes at 52.68 and 55.51 in two quarters (mid-2018 and late 2022). These extreme values may indicate significant temporary efficiency changes or data anomalies. Outside of these spikes, the ratio fluctuates between 2.18 and 9.1 with no clear sustained trend, implying variable efficiency in using working capital to generate sales.
- Average Inventory Processing Period
- The number of days inventory is held exhibits a significant increase from around 98 days in mid-2017 to a peak of 231 days in mid-2018, confirming slower inventory turnover during that period. After this peak, the period declines and stabilizes around 110–130 days through 2019 and 2020. However, in the latest periods through 2022, it shows a rising trend up to 160 days, indicating increasing inventory holding time again.
- Average Receivable Collection Period
- The collection period remains relatively stable, mostly between 52 and 68 days. It shows a slight increase around mid-2018, consistent with the decrease in receivables turnover, but overall the variation is moderate, reflecting consistent credit management practices.
- Operating Cycle
- The operating cycle, defined as the sum of inventory and receivables periods, expands markedly to a high of 299 days in mid-2018, reflecting the earlier observed spikes in inventory and receivables periods. After this surge, it contracts back to around the 150–180 day range during 2019–2021. Toward late 2022, there is a gradual increase to over 210 days, suggesting prolongation of the full operating cycle.
- Average Payables Payment Period
- This period rises sharply from about 34–40 days in 2017 to peaks above 50 days in parts of 2021 and late 2022. A prolonged payment period implies the company is extending payment terms with suppliers.
- Cash Conversion Cycle
- The cash conversion cycle reflects the net effect of the above components and increases significantly from approximately 112–129 days in 2017 to over 230 days in mid-2018. It declines to a range near 130–140 days throughout 2019 and early 2020 but trends upward again in late 2021 through 2022, reaching 164 days. This indicates that the company's cash is tied up longer in operational processes, especially recently.
In summary, the company experienced a period of operational inefficiency around mid-2018, with slower inventory turnover, longer receivables collection, extended payables periods, and an elongation of the cash conversion cycle. After this, some improvement occurred with partial reversals of these trends. However, the recent data from 2021 and 2022 show a renewed trend of slower inventory movement, longer payment and collection cycles, and thus a lengthening cash conversion cycle, implying working capital management challenges impacting liquidity efficiency.
Turnover Ratios
Average No. Days
Inventory Turnover
| 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 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in thousands) | ||||||||||||||||||||||||||||||
| Cost of sales | ||||||||||||||||||||||||||||||
| Inventories | ||||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||
| Inventory turnover1 | ||||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||||
| Inventory Turnover, Competitors2 | ||||||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | ||||||||||||||||||||||||||||||
| Analog Devices Inc. | ||||||||||||||||||||||||||||||
| Applied Materials Inc. | ||||||||||||||||||||||||||||||
| Broadcom Inc. | ||||||||||||||||||||||||||||||
| Intel Corp. | ||||||||||||||||||||||||||||||
| KLA Corp. | ||||||||||||||||||||||||||||||
| Lam Research Corp. | ||||||||||||||||||||||||||||||
| Micron Technology Inc. | ||||||||||||||||||||||||||||||
| NVIDIA Corp. | ||||||||||||||||||||||||||||||
| Qualcomm Inc. | ||||||||||||||||||||||||||||||
| Texas Instruments Inc. | ||||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-K (reporting date: 2022-03-31), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-K (reporting date: 2021-03-31), 10-Q (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-K (reporting date: 2020-03-31), 10-Q (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-K (reporting date: 2019-03-31), 10-Q (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-K (reporting date: 2018-03-31), 10-Q (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30).
1 Q3 2023 Calculation
Inventory turnover
= (Cost of salesQ3 2023
+ Cost of salesQ2 2023
+ Cost of salesQ1 2023
+ Cost of salesQ4 2022)
÷ Inventories
= ( + + + )
÷ =
2 Click competitor name to see calculations.
- Cost of sales
- The cost of sales exhibited a generally increasing trend over the observed periods. Initially, the values fluctuated moderately around the 380,000 to 400,000 US$ thousand range until early 2018. Beginning mid-2018, there was a significant jump, with the cost surpassing 570,000 US$ thousand, peaking at 743,200 US$ thousand in September 2018. After this peak, the cost of sales temporarily declined and then stabilized somewhat between 500,000 and 580,000 US$ thousand through 2019 and early 2020. From mid-2020 onward, the cost of sales demonstrated a steady upward trajectory, increasing consistently from approximately 506,300 US$ thousand in late 2020 to 698,400 US$ thousand by the end of 2022.
- Inventories
- Inventories started at 426,843 US$ thousand in mid-2017 and showed a rising trend with notable variability. A substantial spike was observed in mid-2018, where inventories soared past 1,100,000 US$ thousand, followed by a decrease to lower levels in the subsequent quarters. Into 2019 and early 2020, inventories fluctuated moderately around 660,000 to 730,000 US$ thousand. From mid-2020 forward, inventories again trended upward, with a pronounced increase accelerating through 2021 and 2022, culminating in inventory levels exceeding 1,165,400 US$ thousand by the end of 2022. This suggests a considerable buildup in stock over recent periods.
- Inventory turnover
- The inventory turnover ratio showed a declining trend over the timeframe. Beginning at a relatively high level of 3.72 in mid-2017, it declined sharply to 1.58 by mid-2018, coinciding with the inventory spike and increased cost of sales in that period. Following this low, the ratio recovered somewhat to above 3.0 in 2018 and early 2019, indicating improved efficiency. However, from mid-2019 onward, the turnover ratio steadily declined, falling below 3.0 and continuing down to 2.27 by the end of 2022. This persistent decrease reflects a lengthening of the inventory holding period, potentially indicating slower inventory movement or overstocking relative to sales.
- Overall insights
- The data reflects a company managing increasing costs of sales in combination with growing inventory levels, particularly pronounced after mid-2018 and again accelerating in recent periods. The simultaneous decline in inventory turnover ratio suggests that inventory is not being converted to sales as rapidly as before, which may point to evolving operational challenges such as demand fluctuations, supply chain issues, or strategic stockpiling. The trends warrant attention to optimize inventory management and control cost growth relative to revenue generation.
Receivables Turnover
| 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 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in thousands) | ||||||||||||||||||||||||||||||
| Net sales | ||||||||||||||||||||||||||||||
| Accounts receivable, net | ||||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||
| Receivables turnover1 | ||||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||||
| Receivables Turnover, Competitors2 | ||||||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | ||||||||||||||||||||||||||||||
| Analog Devices Inc. | ||||||||||||||||||||||||||||||
| Applied Materials Inc. | ||||||||||||||||||||||||||||||
| Broadcom Inc. | ||||||||||||||||||||||||||||||
| Intel Corp. | ||||||||||||||||||||||||||||||
| KLA Corp. | ||||||||||||||||||||||||||||||
| Lam Research Corp. | ||||||||||||||||||||||||||||||
| Micron Technology Inc. | ||||||||||||||||||||||||||||||
| NVIDIA Corp. | ||||||||||||||||||||||||||||||
| Texas Instruments Inc. | ||||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-K (reporting date: 2022-03-31), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-K (reporting date: 2021-03-31), 10-Q (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-K (reporting date: 2020-03-31), 10-Q (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-K (reporting date: 2019-03-31), 10-Q (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-K (reporting date: 2018-03-31), 10-Q (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30).
1 Q3 2023 Calculation
Receivables turnover
= (Net salesQ3 2023
+ Net salesQ2 2023
+ Net salesQ1 2023
+ Net salesQ4 2022)
÷ Accounts receivable, net
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The financial data indicates a general upward trend in net sales over the observed quarters, with occasional fluctuations. Starting from approximately 972 million USD in mid-2017, net sales experienced growth with notable increases reaching over 2.16 billion USD by the end of 2022. Despite some minor quarterly declines, the overall trajectory suggests a steady expansion in revenue generation.
Accounts receivable exhibit variability that does not consistently mirror the net sales pattern. Initial values around 529 million USD increased significantly to near 789 million USD by mid-2018, then experienced declines and rises across subsequent quarters. Notably, accounts receivable showed occasional sharp increases, such as in early 2019, peaking at over 1.17 billion USD towards the end of 2022. The fluctuations might imply changes in credit policy, payment collection efficiency, or customer purchasing behaviors.
The receivables turnover ratio fluctuates between approximately 5.3 and 9.2 times per year. The ratio peaked notably at 9.22 in late 2018 but generally oscillated in the mid-5 to mid-6 range in most quarters. This pattern suggests variability in how efficiently the company collects receivables relative to sales. The periods of lower turnover correspond roughly with higher accounts receivable balances, indicating potentially longer collection periods during those times.
- Summary
- Net sales demonstrate consistent growth, indicative of robust business expansion.
- Accounts receivable balances show significant volatility, with periods of both increase and reduction that may reflect changes in credit management or customer payment cycles.
- Receivables turnover ratio varies correspondingly, suggesting fluctuations in collection efficiency over time.
- The interplay of these metrics points to a need for ongoing monitoring of receivable management to sustain healthy cash flows amid growing sales volumes.
Payables Turnover
| 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 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in thousands) | ||||||||||||||||||||||||||||||
| Cost of sales | ||||||||||||||||||||||||||||||
| Accounts payable | ||||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||
| Payables turnover1 | ||||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||||
| Payables Turnover, Competitors2 | ||||||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | ||||||||||||||||||||||||||||||
| Analog Devices Inc. | ||||||||||||||||||||||||||||||
| Broadcom Inc. | ||||||||||||||||||||||||||||||
| Intel Corp. | ||||||||||||||||||||||||||||||
| KLA Corp. | ||||||||||||||||||||||||||||||
| Lam Research Corp. | ||||||||||||||||||||||||||||||
| NVIDIA Corp. | ||||||||||||||||||||||||||||||
| Qualcomm Inc. | ||||||||||||||||||||||||||||||
| Texas Instruments Inc. | ||||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-K (reporting date: 2022-03-31), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-K (reporting date: 2021-03-31), 10-Q (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-K (reporting date: 2020-03-31), 10-Q (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-K (reporting date: 2019-03-31), 10-Q (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-K (reporting date: 2018-03-31), 10-Q (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30).
1 Q3 2023 Calculation
Payables turnover
= (Cost of salesQ3 2023
+ Cost of salesQ2 2023
+ Cost of salesQ1 2023
+ Cost of salesQ4 2022)
÷ Accounts payable
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The analysis of the financial data reveals several notable trends and fluctuations in key operational metrics over the observed periods.
- Cost of Sales
- The cost of sales demonstrated a generally increasing trend with some variability. From mid-2017 to early 2018, costs were relatively stable, fluctuating around the 387 million US dollars mark. However, in the second quarter of 2018, there was a sharp increase, peaking at approximately 743 million in the third quarter of 2018. Subsequently, costs declined somewhat and stabilized around the 500-600 million range through 2019 and early 2020. Starting mid-2020, a gradual upward trend is evident, culminating in close to 698 million by the end of 2022. This pattern suggests increased production or procurement activity over time, with some episodic surges in expenses.
- Accounts Payable
- Accounts payable showed significant variation over the course of the periods measured. Initial figures ranged between 144 million and 182 million US dollars in 2017, followed by a substantial increase to over 318 million in mid-2018. After a decline toward the end of 2018, payables rose again gradually, peaking at nearly 380 million in the third quarter of 2022 before slightly decreasing at year's end. This upward trajectory in payables generally aligns with the broader increase observed in cost of sales, indicating higher outstanding supplier obligations.
- Payables Turnover Ratio
- The payables turnover ratio exhibited considerable fluctuation. The ratio was relatively high in early periods (around 9.2 to 10.8 in 2017 and early 2018), indicating faster payment cycles initially. This dropped sharply in mid-2018 to a low of 5.48, coinciding with the surge in accounts payable and cost of sales, suggesting slower payment to suppliers during this period. Subsequently, the ratio rose again, fluctuating mostly between 6.7 and 9.7 for the remainder of the timeframe. The downturn in turnover ratio in later periods could indicate more extended payment terms or slower payments, reflecting changes in working capital management or supplier negotiations.
In summary, the company experienced increased operational costs and payables over the reviewed periods with notable peaks in mid-2018. The payables turnover ratio trends suggest an adjustment in payment behavior, with slower payment periods especially during times of elevated costs and payables. These patterns may reflect strategic decisions in procurement financing or responses to market conditions impacting cash flow management.
Working Capital Turnover
| 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 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in thousands) | ||||||||||||||||||||||||||||||
| Current assets | ||||||||||||||||||||||||||||||
| Less: Current liabilities | ||||||||||||||||||||||||||||||
| Working capital | ||||||||||||||||||||||||||||||
| Net sales | ||||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||
| Working capital turnover1 | ||||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||||
| Working Capital Turnover, Competitors2 | ||||||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | ||||||||||||||||||||||||||||||
| Analog Devices Inc. | ||||||||||||||||||||||||||||||
| Applied Materials Inc. | ||||||||||||||||||||||||||||||
| Broadcom Inc. | ||||||||||||||||||||||||||||||
| Intel Corp. | ||||||||||||||||||||||||||||||
| KLA Corp. | ||||||||||||||||||||||||||||||
| Lam Research Corp. | ||||||||||||||||||||||||||||||
| Micron Technology Inc. | ||||||||||||||||||||||||||||||
| NVIDIA Corp. | ||||||||||||||||||||||||||||||
| Qualcomm Inc. | ||||||||||||||||||||||||||||||
| Texas Instruments Inc. | ||||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-K (reporting date: 2022-03-31), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-K (reporting date: 2021-03-31), 10-Q (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-K (reporting date: 2020-03-31), 10-Q (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-K (reporting date: 2019-03-31), 10-Q (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-K (reporting date: 2018-03-31), 10-Q (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30).
1 Q3 2023 Calculation
Working capital turnover
= (Net salesQ3 2023
+ Net salesQ2 2023
+ Net salesQ1 2023
+ Net salesQ4 2022)
÷ Working capital
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The financial data reveals notable trends in working capital, net sales, and working capital turnover over the analyzed quarterly periods.
- Working Capital
- Working capital values exhibit significant volatility across the reviewed periods. Initially, values ranged between approximately 1.3 billion to 1.7 billion US dollars until early 2018, followed by a sharp decline to lower levels mid-2018, with some quarters even reporting negative working capital. This negative phase persisted notably around late 2018 through mid-2019. Subsequently, from mid-2019 onward, working capital shows a recovery trend with fluctuations but generally improves back into positive territory, reaching over 1.3 billion US dollars by late 2022. Such fluctuations imply varying liquidity conditions and potential challenges in managing current assets and liabilities consistently.
- Net Sales
- Net sales display a steady upward trend throughout the period. Starting near 972 million US dollars in mid-2017, sales gradually increase quarter over quarter with no significant declines. Reaching approximately 2.17 billion US dollars by the last quarter of 2022, the consistent growth in net sales indicates expanding revenue generation and possibly successful market penetration or product performance during the timeframe.
- Working Capital Turnover
- The working capital turnover ratio demonstrates considerable variation, reflecting the changes in both working capital and sales levels. Early periods show ratios mostly between 2.18 to 2.97, rising sharply in mid-2018 to anomalously high values such as 52.68 and 35.62 at certain points. There are gaps with missing data in some quarters, but overall, the ratio tends to fluctuate widely, indicating variability in the efficiency of using working capital to generate sales. The periods of extremely high turnover ratios coincide with quarters of very low or negative working capital, which mechanically inflates the ratio due to the denominator effect.
In summary, while revenue growth appears strong and consistent, the working capital figures and corresponding turnover ratios suggest periods of operational challenges related to liquidity management. The fluctuations and occasional negative values in working capital signal potential issues in balancing current assets and liabilities. Despite this, the improving trend in working capital from 2019 onwards, alongside rising sales, may indicate efforts toward stabilizing financial operations and enhancing working capital efficiency over time.
Average Inventory Processing Period
| 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 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||||
| Inventory turnover | ||||||||||||||||||||||||||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||||
| Average inventory processing period1 | ||||||||||||||||||||||||||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||||
| Average Inventory Processing Period, Competitors2 | ||||||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | ||||||||||||||||||||||||||||||
| Analog Devices Inc. | ||||||||||||||||||||||||||||||
| Applied Materials Inc. | ||||||||||||||||||||||||||||||
| Broadcom Inc. | ||||||||||||||||||||||||||||||
| Intel Corp. | ||||||||||||||||||||||||||||||
| KLA Corp. | ||||||||||||||||||||||||||||||
| Lam Research Corp. | ||||||||||||||||||||||||||||||
| Micron Technology Inc. | ||||||||||||||||||||||||||||||
| NVIDIA Corp. | ||||||||||||||||||||||||||||||
| Qualcomm Inc. | ||||||||||||||||||||||||||||||
| Texas Instruments Inc. | ||||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-K (reporting date: 2022-03-31), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-K (reporting date: 2021-03-31), 10-Q (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-K (reporting date: 2020-03-31), 10-Q (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-K (reporting date: 2019-03-31), 10-Q (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-K (reporting date: 2018-03-31), 10-Q (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30).
1 Q3 2023 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =
2 Click competitor name to see calculations.
The analyzed data presents inventory management efficiency over multiple quarters, reflected through the inventory turnover ratio and the average inventory processing period measured in days.
- Inventory Turnover Ratio
- This ratio demonstrates a generally declining trend from mid-2017 through the end of 2022. Starting at a relatively high level of 3.72 in June 2017, the ratio experiences fluctuations with a marked dip around June 2018 to 1.58, followed by a recovery phase through early 2019. Subsequently, the ratio stabilizes in a range near 3.0 until early 2021. From that point onward, it shows a gradual decrease, ending at 2.27 in December 2022.
- Average Inventory Processing Period
- The average number of days to process inventory inversely mirrors the inventory turnover ratio, starting at 98 days in June 2017 and increasing significantly to 231 days by June 2018. This peak corresponds with the period of the lowest inventory turnover. Afterwards, the processing period decreases and stabilizes around 110 to 120 days from late 2018 to early 2021. A renewed upward trend is seen from early 2021 onward, reaching 160 days by the end of 2022.
The inverse relationship between these two metrics is consistent with inventory management theory, where a higher turnover ratio typically correlates with a shorter processing period. The significant variations observed around mid-2018 suggest operational challenges or strategic shifts impacting inventory efficiency during that time. Though some recovery occurred, the latter periods show a trend toward slower inventory turnover and longer processing times, which may indicate increasing inventory holding or slower sales cycles.
Average Receivable Collection Period
| 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 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||||
| Receivables turnover | ||||||||||||||||||||||||||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||||
| Average receivable collection period1 | ||||||||||||||||||||||||||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||||
| Average Receivable Collection Period, Competitors2 | ||||||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | ||||||||||||||||||||||||||||||
| Analog Devices Inc. | ||||||||||||||||||||||||||||||
| Applied Materials Inc. | ||||||||||||||||||||||||||||||
| Broadcom Inc. | ||||||||||||||||||||||||||||||
| Intel Corp. | ||||||||||||||||||||||||||||||
| KLA Corp. | ||||||||||||||||||||||||||||||
| Lam Research Corp. | ||||||||||||||||||||||||||||||
| Micron Technology Inc. | ||||||||||||||||||||||||||||||
| NVIDIA Corp. | ||||||||||||||||||||||||||||||
| Texas Instruments Inc. | ||||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-K (reporting date: 2022-03-31), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-K (reporting date: 2021-03-31), 10-Q (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-K (reporting date: 2020-03-31), 10-Q (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-K (reporting date: 2019-03-31), 10-Q (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-K (reporting date: 2018-03-31), 10-Q (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30).
1 Q3 2023 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =
2 Click competitor name to see calculations.
The receivables turnover ratio and average receivable collection period provide insight into the efficiency of the company’s credit and collection policies over the analyzed quarters.
- Receivables Turnover Ratio
- The receivables turnover ratio exhibits moderate fluctuations throughout the observed period. Initially, the ratio was around 6.77 to 7.06 in mid to late 2017, indicating a relatively stable collection performance. A noticeable dip occurred in June 2018 when the ratio dropped to 5.35, followed by a significant peak reaching 9.22 in December 2018, representing a period of improved collection efficiency. After this peak, the ratio decreased again, fluctuating between approximately 5.45 and 6.93 over subsequent quarters. Toward the end of the timeline, in 2022, the ratio trends slightly upward, reaching 6.85 in the last quarter, suggesting a gradual recovery or improvement in receivables turnover.
- Average Receivable Collection Period
- The average collection period moves inversely relative to the receivables turnover ratio, as expected. It began close to 52-54 days in mid-2017, indicating a typical collection duration. An increase to 68 days occurred in June 2018, aligned with the lowered turnover ratio, indicating slower collection during that quarter. A sharp improvement to just 40 days was recorded in December 2017, maintaining relative strength thereafter. The period then fluctuated between approximately 53 and 67 days from 2019 through 2021, showing some volatility but generally remaining within a moderate range. By the end of 2022, the collection period stabilized around 53-54 days, correlating with the slight increase in turnover ratio.
Overall, the data reflect periods of variability in collection efficiency, with some quarters showing strong performance and others less so. The company appears to have maintained a reasonable average collection period, primarily ranging from 50 to 65 days, except for outliers in mid-2018. The gradual improvement in turnover ratio and the corresponding reduction of days in receivable collection toward the end of the analyzed timeline suggest enhancements in credit management practices or customer payment behavior.
Operating Cycle
| 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 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||||
| Average inventory processing period | ||||||||||||||||||||||||||||||
| Average receivable collection period | ||||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||
| Operating cycle1 | ||||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||||
| Operating Cycle, Competitors2 | ||||||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | ||||||||||||||||||||||||||||||
| Analog Devices Inc. | ||||||||||||||||||||||||||||||
| Applied Materials Inc. | ||||||||||||||||||||||||||||||
| Broadcom Inc. | ||||||||||||||||||||||||||||||
| Intel Corp. | ||||||||||||||||||||||||||||||
| KLA Corp. | ||||||||||||||||||||||||||||||
| Lam Research Corp. | ||||||||||||||||||||||||||||||
| Micron Technology Inc. | ||||||||||||||||||||||||||||||
| NVIDIA Corp. | ||||||||||||||||||||||||||||||
| Texas Instruments Inc. | ||||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-K (reporting date: 2022-03-31), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-K (reporting date: 2021-03-31), 10-Q (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-K (reporting date: 2020-03-31), 10-Q (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-K (reporting date: 2019-03-31), 10-Q (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-K (reporting date: 2018-03-31), 10-Q (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30).
1 Q3 2023 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= + =
2 Click competitor name to see calculations.
The analysis of the quarterly financial data reveals notable variations in inventory processing, receivable collection, and overall operating cycle over the observed periods.
- Average inventory processing period
- This metric shows a generally increasing trend, starting from 98 days at mid-2017 and rising sharply to 231 days by mid-2018, indicating a significant slowdown in inventory turnover during that period. Subsequently, there is a reduction to around 112-120 days from late 2018 through early 2021, suggesting a recovery in inventory management efficiency. However, from 2021 onward, the processing period begins to gradually increase again, reaching 160 days by the end of 2022, implying a gradual lengthening of the inventory turnover period.
- Average receivable collection period
- The receivable collection period remains relatively stable with moderate fluctuations between approximately 40 and 68 days. Notable spikes are observed in mid-2018 (68 days) and early 2020 (65 days), indicating periods of slower cash inflow from receivables. Between these spikes, the collection period generally hovers around the mid-50-day range, with slight decreases toward the end of 2022, returning to approximately 53 days.
- Operating cycle
- The operating cycle follows a pattern predominantly influenced by the inventory processing period and receivables collection. It rises markedly from 152 days at mid-2017 to a pronounced peak of 299 days by mid-2018, signaling a significant extension of the cash conversion cycle at that time. Following the peak, the cycle shortens substantially to the range of 150-185 days through early 2021, reflecting improvements in working capital management. However, from 2021 onward, the operating cycle trends upward again, reaching 213 days by the end of 2022, indicating a lengthened duration for converting inventory and receivables into cash.
Overall, the data suggests cyclical variations in both inventory management and receivables collections, with a particularly challenging period around mid-2018 reflected in all three metrics. Improvements were achieved in the subsequent years but signs of reverting toward slower working capital turnover emerge in late 2021 through 2022. These patterns point to areas where operational efficiencies should be carefully monitored and potentially optimized to maintain healthier liquidity and asset utilization.
Average Payables Payment Period
| 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 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||||
| Payables turnover | ||||||||||||||||||||||||||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||||
| Average payables payment period1 | ||||||||||||||||||||||||||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||||
| Average Payables Payment Period, Competitors2 | ||||||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | ||||||||||||||||||||||||||||||
| Analog Devices Inc. | ||||||||||||||||||||||||||||||
| Broadcom Inc. | ||||||||||||||||||||||||||||||
| Intel Corp. | ||||||||||||||||||||||||||||||
| KLA Corp. | ||||||||||||||||||||||||||||||
| Lam Research Corp. | ||||||||||||||||||||||||||||||
| NVIDIA Corp. | ||||||||||||||||||||||||||||||
| Qualcomm Inc. | ||||||||||||||||||||||||||||||
| Texas Instruments Inc. | ||||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-K (reporting date: 2022-03-31), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-K (reporting date: 2021-03-31), 10-Q (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-K (reporting date: 2020-03-31), 10-Q (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-K (reporting date: 2019-03-31), 10-Q (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-K (reporting date: 2018-03-31), 10-Q (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30).
1 Q3 2023 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ =
2 Click competitor name to see calculations.
- Payables Turnover Ratio
- The payables turnover ratio exhibits considerable fluctuation over the observed period. Initially, it ranged between approximately 8.35 and 10.83 from mid-2017 through early 2019, showing moderate variability but generally maintaining a relatively stable level. Around mid-2018, a noticeable dip occurred, where the ratio fell to a low of 5.48, indicating a slower turnover of payables during that quarter. Subsequently, the ratio rebounded and stabilized closer to previous levels, fluctuating mostly between 7 and 10 through 2019 and 2020.
- From 2021 onwards, there is a gradual declining trend in the payables turnover ratio, settling mostly in the 6.7 to 8.1 range by late 2022. This decline suggests a moderate deceleration in payables turnover, potentially indicating extended payment periods or slower supplier settlements compared to earlier years.
- Average Payables Payment Period (Days)
- The average payables payment period inversely reflects the trend observed in the payables turnover ratio, as expected. Early in the timeline, payment periods were relatively short, hovering around 34 to 44 days. A significant spike is evident in mid-2018, where the payment period increased sharply to 67 days, coinciding with the drop in payables turnover ratio during the same period. This points to lengthened payment cycles during that quarter.
- Following this spike, the payment period shortened again to a range around 34 to 44 days through 2019 and early 2020. However, from 2021 onwards there is a steady increase in the average payment period, with values generally ranging from 45 to 54 days by late 2022. This gradual extension in payment days aligns with the downward trend in the payables turnover ratio, supporting the view that the company has been taking longer on average to pay its suppliers over recent quarters.
- Overall Trends and Insights
- The data reveals that payables management has experienced periods of both acceleration and deceleration. The sharp mid-2018 changes suggest a one-time disruption or strategic shift in payment practices, possibly reflecting operational adjustments or external factors affecting liquidity or supplier relationships.
- From 2021 through the end of 2022, the observed trends suggest that the company has increasingly extended its average payment periods, which could be indicative of tighter cash management or renegotiated payment terms with suppliers. The moderately declining payables turnover and lengthening payment period warrant monitoring to assess potential impacts on supplier relations and working capital efficiency.
Cash Conversion Cycle
| 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 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||||
| Average inventory processing period | ||||||||||||||||||||||||||||||
| Average receivable collection period | ||||||||||||||||||||||||||||||
| Average payables payment period | ||||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||
| Cash conversion cycle1 | ||||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||||
| Cash Conversion Cycle, Competitors2 | ||||||||||||||||||||||||||||||
| Advanced Micro Devices Inc. | ||||||||||||||||||||||||||||||
| Analog Devices Inc. | ||||||||||||||||||||||||||||||
| Broadcom Inc. | ||||||||||||||||||||||||||||||
| Intel Corp. | ||||||||||||||||||||||||||||||
| KLA Corp. | ||||||||||||||||||||||||||||||
| Lam Research Corp. | ||||||||||||||||||||||||||||||
| NVIDIA Corp. | ||||||||||||||||||||||||||||||
| Texas Instruments Inc. | ||||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-K (reporting date: 2022-03-31), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-K (reporting date: 2021-03-31), 10-Q (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-K (reporting date: 2020-03-31), 10-Q (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-K (reporting date: 2019-03-31), 10-Q (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-K (reporting date: 2018-03-31), 10-Q (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30).
1 Q3 2023 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= + – =
2 Click competitor name to see calculations.
- Inventory Processing Period
-
The average inventory processing period exhibited considerable variability over the analyzed quarters, beginning at 98 days and rising to a peak of 231 days in June 2018. Following this peak, the period decreased steadily to approximately 107-112 days by March 2019. Subsequently, a gradual upward trend occurred, reaching 160 days by the end of 2022. This pattern indicates fluctuations in inventory turnover efficiency, with the highest delay in mid-2018 and a general increase in processing time toward the later periods.
- Receivable Collection Period
-
The average receivable collection period showed moderate fluctuations, primarily ranging between 40 and 68 days. It started near the mid-50s, peaked at 68 days in June 2018, then dropped to around 40 days by December 2018. Afterward, the period fluctuated mostly in the low 50s to mid-60s, without a clear upward or downward long-term trend. This suggests some variability in the speed of receivables turnover but generally stable collection performance over time.
- Payables Payment Period
-
The average payables payment period varied from 34 to 67 days, with notable peaks around June 2018 (67 days) and increases toward the later quarters, peaking at 54 days in September 2022 before slightly declining. Initially, the period was around 34-40 days, indicating quicker payment to suppliers, but trends towards longer payables duration suggest a strategic extension in payment terms or cash flow management to preserve liquidity.
- Cash Conversion Cycle
-
The cash conversion cycle mirrored trends observed in inventory and receivables with a high degree of fluctuation. Initially measured at 112 days, it peaked sharply at 232 days in June 2018, reflecting delayed cash conversion predominantly driven by a spike in inventory processing. Subsequently, it decreased to near 128-133 days in 2019 and early 2020 but trended upward again from mid-2021 onward, reaching 164 days by the end of 2022. This indicates growing challenges in converting investments in inventory and receivables into cash, potentially impacting working capital efficiency.