Stock Analysis on Net

Lam Research Corp. (NASDAQ:LRCX)

$24.99

Analysis of Short-term (Operating) Activity Ratios
Quarterly Data

Microsoft Excel

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Short-term Activity Ratios (Summary)

Lam Research Corp., short-term (operating) activity ratios (quarterly data)

Microsoft Excel
Sep 28, 2025 Jun 29, 2025 Mar 30, 2025 Dec 29, 2024 Sep 29, 2024 Jun 30, 2024 Mar 31, 2024 Dec 24, 2023 Sep 24, 2023 Jun 25, 2023 Mar 26, 2023 Dec 25, 2022 Sep 25, 2022 Jun 26, 2022 Mar 27, 2022 Dec 26, 2021 Sep 26, 2021 Jun 27, 2021 Mar 28, 2021 Dec 27, 2020 Sep 27, 2020
Turnover Ratios
Inventory turnover
Receivables turnover
Payables turnover
Working capital turnover
Average No. Days
Average inventory processing period
Add: Average receivable collection period
Operating cycle
Less: Average payables payment period
Cash conversion cycle

Based on: 10-Q (reporting date: 2025-09-28), 10-K (reporting date: 2025-06-29), 10-Q (reporting date: 2025-03-30), 10-Q (reporting date: 2024-12-29), 10-Q (reporting date: 2024-09-29), 10-K (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-Q (reporting date: 2023-12-24), 10-Q (reporting date: 2023-09-24), 10-K (reporting date: 2023-06-25), 10-Q (reporting date: 2023-03-26), 10-Q (reporting date: 2022-12-25), 10-Q (reporting date: 2022-09-25), 10-K (reporting date: 2022-06-26), 10-Q (reporting date: 2022-03-27), 10-Q (reporting date: 2021-12-26), 10-Q (reporting date: 2021-09-26), 10-K (reporting date: 2021-06-27), 10-Q (reporting date: 2021-03-28), 10-Q (reporting date: 2020-12-27), 10-Q (reporting date: 2020-09-27).


Inventory Turnover
The inventory turnover ratio demonstrates a declining trend from 2.77 in September 2020 to a low of 1.75 in March 2024, indicating a slower movement of inventory over this period. Subsequently, there is a recovery observed, with the ratio increasing to 2.43 by September 2025, suggesting improved inventory management or increased sales efficiency in the later periods.
Receivables Turnover
Receivables turnover exhibits moderate fluctuations, starting from 4.77 in September 2020, dipping below 4.0 around mid-2022, then rising to a peak of approximately 6.46 in March 2024, before stabilizing around 5.3-5.5 towards the latter part of 2025. This pattern indicates variability in collection efficiency, with notable improvement around early 2024 followed by stabilization.
Payables Turnover
Payables turnover remained relatively stable in the initial periods, near 9.0, but starting late 2022, there is a distinct upward spike reaching 20.5 in December 2022, followed by a gradual decline to around 11.5 by September 2025. This suggests a period of accelerated payment to suppliers followed by a normalization phase.
Working Capital Turnover
Working capital turnover rose steadily from 1.41 in late 2020 to a peak of 2.23 in mid-2022, indicating more efficient use of working capital. After this peak, a decline occurs through late 2023, dropping to around 1.63, then recovering gradually to 2.42 by late 2025. The overall trend reveals oscillations in working capital efficiency, with an improving outlook in the most recent quarters.
Average Inventory Processing Period
There is an increasing trend in the average number of days inventory is held, progressing from 132 days in September 2020 to a high of 208 days in March 2024. Afterwards, the period shortens to 151 days by September 2025, supporting the inventory turnover findings and reflecting initial inventory accumulation followed by better turnover rates during the final periods.
Average Receivable Collection Period
The average collection period fluctuates, starting at 77 days, with an increase up to 93 days around late 2022, followed by a general decline to approximately 56 days in March 2024. It then settles in the high 60s through 2025, indicating episodic challenges in collections but an overall improvement near early 2024 and subsequent stabilization.
Operating Cycle
The operating cycle, combining inventory and receivables periods, shows an upward trajectory from about 209 days to a peak near 275 days in late 2023. Thereafter, it declines steadily to 219 days by September 2025. This pattern highlights an elongation in the time required to convert inventory and receivables into cash until late 2023, followed by improvements.
Average Payables Payment Period
The payable payment period generally shortens from about 41 days to a low of 18 days by early 2023, indicating quicker supplier payments. After this point, it gradually extends again to about 32 days by 2025. These shifts illustrate changing cash flow strategies relating to payment terms with suppliers.
Cash Conversion Cycle
The cash conversion cycle enlarges from 168 days up to 252 days through the end of 2023, demonstrating increased time for converting inputs into cash, thus potentially tightening liquidity. Following this peak, it decreases to 187 days by September 2025, signifying enhanced cash flow management and operational efficiency in recent periods.

Turnover Ratios


Average No. Days


Inventory Turnover

Lam Research Corp., inventory turnover calculation (quarterly data)

Microsoft Excel
Sep 28, 2025 Jun 29, 2025 Mar 30, 2025 Dec 29, 2024 Sep 29, 2024 Jun 30, 2024 Mar 31, 2024 Dec 24, 2023 Sep 24, 2023 Jun 25, 2023 Mar 26, 2023 Dec 25, 2022 Sep 25, 2022 Jun 26, 2022 Mar 27, 2022 Dec 26, 2021 Sep 26, 2021 Jun 27, 2021 Mar 28, 2021 Dec 27, 2020 Sep 27, 2020
Selected Financial Data (US$ in thousands)
Cost of goods sold
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.
Micron Technology Inc.
NVIDIA Corp.
Qualcomm Inc.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-09-28), 10-K (reporting date: 2025-06-29), 10-Q (reporting date: 2025-03-30), 10-Q (reporting date: 2024-12-29), 10-Q (reporting date: 2024-09-29), 10-K (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-Q (reporting date: 2023-12-24), 10-Q (reporting date: 2023-09-24), 10-K (reporting date: 2023-06-25), 10-Q (reporting date: 2023-03-26), 10-Q (reporting date: 2022-12-25), 10-Q (reporting date: 2022-09-25), 10-K (reporting date: 2022-06-26), 10-Q (reporting date: 2022-03-27), 10-Q (reporting date: 2021-12-26), 10-Q (reporting date: 2021-09-26), 10-K (reporting date: 2021-06-27), 10-Q (reporting date: 2021-03-28), 10-Q (reporting date: 2020-12-27), 10-Q (reporting date: 2020-09-27).

1 Q1 2026 Calculation
Inventory turnover = (Cost of goods soldQ1 2026 + Cost of goods soldQ4 2025 + Cost of goods soldQ3 2025 + Cost of goods soldQ2 2025) ÷ Inventories
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


Cost of Goods Sold (COGS)
The cost of goods sold exhibited a general upward trend over the reported periods, rising from approximately $1.67 billion to nearly $2.64 billion. Notably, COGS increased steadily from September 2020 through September 2022, peaking around $2.9 billion, before experiencing a decline and then hovering around the $2.0 to $2.3 billion range in the more recent quarters. Towards the latest dates, COGS showed a resurgence, climbing again to levels above $2.6 billion by the end of the period.
Inventories
Inventories have shown a consistent increase overall during the timeline, starting at roughly $2.14 billion and reaching around $4.1 billion by the end of the last period. After steady growth in inventory levels through September 2022, inventories peaked near $4.9 billion in early 2023. Subsequently, there was a slight reduction and stabilization between $4.2 billion and $4.4 billion, with a minor downward adjustment seen at the very end. This trend suggests growing stockpiles that stabilized somewhat in the latter periods.
Inventory Turnover Ratio
The inventory turnover ratio declined notably over the course of the data series, moving from an initial rate of 2.77 down to around 2.0 in mid-2023 and reaching a low of approximately 1.75 by early 2024. However, it began to recover in recent quarters, climbing back to about 2.43 near the end of the timeline. This pattern suggests that inventory was turning over more slowly for an extended period, implying potential overstocking or slower sales, followed by improved efficiency or higher sales in later periods.
Summary Insights
The data indicates that while costs associated with goods sold generally increased, reflecting likely growth in production or sales volume, inventory levels rose at a steeper rate, especially until early 2023. This discrepancy contributed to a declining inventory turnover ratio, signaling a slowdown in inventory movement relative to cost of goods sold. The late-stage improvement in turnover alongside fluctuating COGS and inventory suggests operational adjustments potentially aimed at optimizing inventory management and aligning production more closely with demand.

Receivables Turnover

Lam Research Corp., receivables turnover calculation (quarterly data)

Microsoft Excel
Sep 28, 2025 Jun 29, 2025 Mar 30, 2025 Dec 29, 2024 Sep 29, 2024 Jun 30, 2024 Mar 31, 2024 Dec 24, 2023 Sep 24, 2023 Jun 25, 2023 Mar 26, 2023 Dec 25, 2022 Sep 25, 2022 Jun 26, 2022 Mar 27, 2022 Dec 26, 2021 Sep 26, 2021 Jun 27, 2021 Mar 28, 2021 Dec 27, 2020 Sep 27, 2020
Selected Financial Data (US$ in thousands)
Revenue
Accounts receivable, less allowance
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.
Micron Technology Inc.
NVIDIA Corp.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-09-28), 10-K (reporting date: 2025-06-29), 10-Q (reporting date: 2025-03-30), 10-Q (reporting date: 2024-12-29), 10-Q (reporting date: 2024-09-29), 10-K (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-Q (reporting date: 2023-12-24), 10-Q (reporting date: 2023-09-24), 10-K (reporting date: 2023-06-25), 10-Q (reporting date: 2023-03-26), 10-Q (reporting date: 2022-12-25), 10-Q (reporting date: 2022-09-25), 10-K (reporting date: 2022-06-26), 10-Q (reporting date: 2022-03-27), 10-Q (reporting date: 2021-12-26), 10-Q (reporting date: 2021-09-26), 10-K (reporting date: 2021-06-27), 10-Q (reporting date: 2021-03-28), 10-Q (reporting date: 2020-12-27), 10-Q (reporting date: 2020-09-27).

1 Q1 2026 Calculation
Receivables turnover = (RevenueQ1 2026 + RevenueQ4 2025 + RevenueQ3 2025 + RevenueQ2 2025) ÷ Accounts receivable, less allowance
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


Revenue Trends
The revenue exhibited an overall increasing trend from late 2020 through mid-2025, starting at approximately 3.18 billion USD in September 2020 and reaching over 5.32 billion USD by September 2025. There were some fluctuations, such as a decline in Q1 2023 back to around 3.87 billion USD after peaking near 5.28 billion USD in Q4 2022. However, after this dip, revenue resumed its upward trajectory and consistently increased through 2025.
Accounts Receivable Dynamics
The accounts receivable, net of allowances, also showed considerable variability. From about 2.32 billion USD in late 2020, it increased steadily, peaking near 4.57 billion USD in late 2022. Following this peak, balances declined sharply to below 2.21 billion USD by Q3 2023, then generally rose again to approximately 3.63 billion USD by Q3 2025. This pattern suggests significant changes in credit policies or collections over the periods.
Receivables Turnover Ratio
The receivables turnover ratio showed moderate fluctuations but overall indicated an improving collection efficiency over the timeframe. Starting at 4.77 in late 2020, the ratio dipped to a low of 3.94 by late 2022, corresponding with the highest accounts receivable balances and elevated revenue figures. Following the low, the ratio increased, peaking at 6.46 in early 2024, suggesting faster collection of receivables, before stabilizing between 5.3 and 5.5 during the latest periods.
Interrelationships and Insights
The observed trends point to a company experiencing growth in sales, though with periods of stress on working capital management, particularly reflected in the spike of receivables in late 2022. The subsequent recovery in turnover ratio and decline in accounts receivable balances imply more effective credit control and cash collection efforts after that period. The temporary decline in revenue during early 2023 suggests either market disruptions or other operational factors affecting sales, but the prompt recovery and continued growth afterward indicate resilience and ongoing demand expansion.

Payables Turnover

Lam Research Corp., payables turnover calculation (quarterly data)

Microsoft Excel
Sep 28, 2025 Jun 29, 2025 Mar 30, 2025 Dec 29, 2024 Sep 29, 2024 Jun 30, 2024 Mar 31, 2024 Dec 24, 2023 Sep 24, 2023 Jun 25, 2023 Mar 26, 2023 Dec 25, 2022 Sep 25, 2022 Jun 26, 2022 Mar 27, 2022 Dec 26, 2021 Sep 26, 2021 Jun 27, 2021 Mar 28, 2021 Dec 27, 2020 Sep 27, 2020
Selected Financial Data (US$ in thousands)
Cost of goods sold
Trade 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.
NVIDIA Corp.
Qualcomm Inc.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-09-28), 10-K (reporting date: 2025-06-29), 10-Q (reporting date: 2025-03-30), 10-Q (reporting date: 2024-12-29), 10-Q (reporting date: 2024-09-29), 10-K (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-Q (reporting date: 2023-12-24), 10-Q (reporting date: 2023-09-24), 10-K (reporting date: 2023-06-25), 10-Q (reporting date: 2023-03-26), 10-Q (reporting date: 2022-12-25), 10-Q (reporting date: 2022-09-25), 10-K (reporting date: 2022-06-26), 10-Q (reporting date: 2022-03-27), 10-Q (reporting date: 2021-12-26), 10-Q (reporting date: 2021-09-26), 10-K (reporting date: 2021-06-27), 10-Q (reporting date: 2021-03-28), 10-Q (reporting date: 2020-12-27), 10-Q (reporting date: 2020-09-27).

1 Q1 2026 Calculation
Payables turnover = (Cost of goods soldQ1 2026 + Cost of goods soldQ4 2025 + Cost of goods soldQ3 2025 + Cost of goods soldQ2 2025) ÷ Trade accounts payable
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The analysis of the quarterly financial data over the observed periods reveals notable trends in cost management and payables efficiency.

Cost of Goods Sold (COGS)
There is an overall upward trend in the cost of goods sold from September 2020 through June 2025. Initially, the COGS increased steadily from approximately $1.67 billion to a peak around $2.9 billion by December 2022. This was followed by a significant decline in the subsequent quarters of 2023, reaching a nadir near $1.75 billion in June 2023. After this dip, the COGS again exhibits a gradual increase, climbing back above $2.5 billion by mid-2025. This fluctuating pattern likely reflects variances in production volume, raw material costs, or operational efficiencies during the periods.
Trade Accounts Payable
Trade accounts payable showed a general upward trajectory throughout the timeline, starting from approximately $663 million in late 2020 and rising to around $1.16 billion by mid-2025. There is a notable dip in accounts payable during late 2022 to mid-2023, falling as low as approximately $470 million, which corresponds with the dip in COGS during the same timeframe. This suggests possible adjustments in payment terms or inventory management during the fluctuating economic environment.
Payables Turnover Ratio
The payables turnover ratio, which measures how quickly the company pays off its suppliers, displays considerable variability. Early periods show ratios around 9 to 10 times per year, indicating steady payments relative to purchases. Starting end of 2022 through mid-2023, the ratio increased sharply, peaking at over 20 times, suggesting the company was paying suppliers more frequently, possibly as a response to the drop in payables or as part of liquidity management. Following this peak, the ratio declines gradually but remains elevated relative to early years, stabilizing between 10 and 15 times payment cycles annually towards 2025.

In summary, the data indicate a cyclicality in costs and payables reflective of underlying operational or market conditions. COGS and payables moved in tandem with a lag period, and changes in payables turnover demonstrate responsiveness to the company's payment strategies over time. Monitoring these trends can provide insights into cash flow management and operational efficiency going forward.


Working Capital Turnover

Lam Research Corp., working capital turnover calculation (quarterly data)

Microsoft Excel
Sep 28, 2025 Jun 29, 2025 Mar 30, 2025 Dec 29, 2024 Sep 29, 2024 Jun 30, 2024 Mar 31, 2024 Dec 24, 2023 Sep 24, 2023 Jun 25, 2023 Mar 26, 2023 Dec 25, 2022 Sep 25, 2022 Jun 26, 2022 Mar 27, 2022 Dec 26, 2021 Sep 26, 2021 Jun 27, 2021 Mar 28, 2021 Dec 27, 2020 Sep 27, 2020
Selected Financial Data (US$ in thousands)
Current assets
Less: Current liabilities
Working capital
 
Revenue
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.
Micron Technology Inc.
NVIDIA Corp.
Qualcomm Inc.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-09-28), 10-K (reporting date: 2025-06-29), 10-Q (reporting date: 2025-03-30), 10-Q (reporting date: 2024-12-29), 10-Q (reporting date: 2024-09-29), 10-K (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-Q (reporting date: 2023-12-24), 10-Q (reporting date: 2023-09-24), 10-K (reporting date: 2023-06-25), 10-Q (reporting date: 2023-03-26), 10-Q (reporting date: 2022-12-25), 10-Q (reporting date: 2022-09-25), 10-K (reporting date: 2022-06-26), 10-Q (reporting date: 2022-03-27), 10-Q (reporting date: 2021-12-26), 10-Q (reporting date: 2021-09-26), 10-K (reporting date: 2021-06-27), 10-Q (reporting date: 2021-03-28), 10-Q (reporting date: 2020-12-27), 10-Q (reporting date: 2020-09-27).

1 Q1 2026 Calculation
Working capital turnover = (RevenueQ1 2026 + RevenueQ4 2025 + RevenueQ3 2025 + RevenueQ2 2025) ÷ Working capital
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


Working Capital
The working capital shows variability over the periods with a general upward trend in certain intervals. Starting at approximately $7.9 billion in late 2020, it experienced fluctuations with peaks near $9.2 billion in late 2022. Subsequent periods reveal a mild decline followed by stabilization around $8.0 to $8.3 billion in 2024 and 2025. This indicates periodic adjustments in current assets and liabilities without a consistent linear growth.
Revenue
Revenue demonstrates significant volatility throughout the periods analyzed. An initial growth phase is evident from about $3.18 billion in September 2020, rising to over $5 billion by late 2022. This was followed by a sharp decline in early 2023 to approximately $3.2 billion and a gradual recovery thereafter. From mid-2023 onward, revenue shows a steady upward trend, reaching over $5.3 billion by mid-2025. The fluctuations suggest exposure to cyclical market conditions or demand variability, with a recovery and growth phase in the later periods.
Working Capital Turnover
The working capital turnover ratio exhibits an increasing trend in the early periods, rising from 1.41 in September 2020 to a peak of 2.32 by late 2025. The ratio initially grows steadily, indicating improved efficiency in utilizing working capital to generate revenue. Notable dips occur around late 2022 to 2023, correlating with the revenue decline, before resuming an upward trajectory. The ratio consistently remains above 1.4 throughout, reflecting effective management of working capital relative to revenue.
Interrelation and Insights
The data suggests that, while working capital levels fluctuate, the company manages to enhance revenue generation efficiency as evidenced by the increasing working capital turnover ratio. The periods of declining revenue are accompanied by some decreases in turnover, signaling sensitivity to revenue changes. Overall, the post-2023 recovery in revenue combined with maintained working capital levels and improved turnover points to strengthened operational performance and potential optimization in asset-liability management.

Average Inventory Processing Period

Lam Research Corp., average inventory processing period calculation (quarterly data)

Microsoft Excel
Sep 28, 2025 Jun 29, 2025 Mar 30, 2025 Dec 29, 2024 Sep 29, 2024 Jun 30, 2024 Mar 31, 2024 Dec 24, 2023 Sep 24, 2023 Jun 25, 2023 Mar 26, 2023 Dec 25, 2022 Sep 25, 2022 Jun 26, 2022 Mar 27, 2022 Dec 26, 2021 Sep 26, 2021 Jun 27, 2021 Mar 28, 2021 Dec 27, 2020 Sep 27, 2020
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.
Micron Technology Inc.
NVIDIA Corp.
Qualcomm Inc.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-09-28), 10-K (reporting date: 2025-06-29), 10-Q (reporting date: 2025-03-30), 10-Q (reporting date: 2024-12-29), 10-Q (reporting date: 2024-09-29), 10-K (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-Q (reporting date: 2023-12-24), 10-Q (reporting date: 2023-09-24), 10-K (reporting date: 2023-06-25), 10-Q (reporting date: 2023-03-26), 10-Q (reporting date: 2022-12-25), 10-Q (reporting date: 2022-09-25), 10-K (reporting date: 2022-06-26), 10-Q (reporting date: 2022-03-27), 10-Q (reporting date: 2021-12-26), 10-Q (reporting date: 2021-09-26), 10-K (reporting date: 2021-06-27), 10-Q (reporting date: 2021-03-28), 10-Q (reporting date: 2020-12-27), 10-Q (reporting date: 2020-09-27).

1 Q1 2026 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =

2 Click competitor name to see calculations.


The analysis of inventory management metrics over the observed periods reveals important trends and shifts.

Inventory Turnover
The inventory turnover ratio demonstrates a fluctuating downward trend from September 2020 through approximately December 2023. It decreases from an initial value around 2.77 down to approximately 1.75 by March 2024. Following this decline, there is a gradual recovery in the turnover ratio, reaching up to 2.43 by September 2025. This pattern suggests that inventory was being sold and replenished less frequently during the middle intervals, potentially indicating either increased inventory levels, decreased sales, or operational challenges. The rebound in later periods may reflect improved inventory management or an increase in sales velocity.
Average Inventory Processing Period
The corresponding average inventory processing period, which represents the number of days inventory remains before being sold or utilized, corroborates the turnover data. There is a clear increasing trend from 132 days in September 2020 to a peak of 208 days around March 2024. This elongation of the processing period aligns with the decrease in inventory turnover ratio, indicating slower movement of inventory. Afterwards, the processing period gradually shortens to 151 days by September 2025, again matching the improvement seen in the turnover ratio.

Overall, the data indicates a period of weakening inventory efficiency up until early 2024, with inventories staying longer on hand and being turned over less frequently. Subsequently, operational improvements or market conditions likely contributed to enhanced inventory metrics in later periods, as evidenced by a higher turnover ratio and reduced inventory processing days.


Average Receivable Collection Period

Lam Research Corp., average receivable collection period calculation (quarterly data)

Microsoft Excel
Sep 28, 2025 Jun 29, 2025 Mar 30, 2025 Dec 29, 2024 Sep 29, 2024 Jun 30, 2024 Mar 31, 2024 Dec 24, 2023 Sep 24, 2023 Jun 25, 2023 Mar 26, 2023 Dec 25, 2022 Sep 25, 2022 Jun 26, 2022 Mar 27, 2022 Dec 26, 2021 Sep 26, 2021 Jun 27, 2021 Mar 28, 2021 Dec 27, 2020 Sep 27, 2020
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.
Micron Technology Inc.
NVIDIA Corp.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-09-28), 10-K (reporting date: 2025-06-29), 10-Q (reporting date: 2025-03-30), 10-Q (reporting date: 2024-12-29), 10-Q (reporting date: 2024-09-29), 10-K (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-Q (reporting date: 2023-12-24), 10-Q (reporting date: 2023-09-24), 10-K (reporting date: 2023-06-25), 10-Q (reporting date: 2023-03-26), 10-Q (reporting date: 2022-12-25), 10-Q (reporting date: 2022-09-25), 10-K (reporting date: 2022-06-26), 10-Q (reporting date: 2022-03-27), 10-Q (reporting date: 2021-12-26), 10-Q (reporting date: 2021-09-26), 10-K (reporting date: 2021-06-27), 10-Q (reporting date: 2021-03-28), 10-Q (reporting date: 2020-12-27), 10-Q (reporting date: 2020-09-27).

1 Q1 2026 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =

2 Click competitor name to see calculations.


Receivables Turnover
The receivables turnover ratio exhibits variability over the observed periods, starting at 4.77 and displaying fluctuations with a general pattern of increase and decrease. Initially, there is a decline from 4.77 to 4.11, followed by moderate recovery and peaks, notably reaching 6.46 during one of the later quarters. This suggests periods of improved efficiency in collecting receivables, particularly in recent quarters where values generally trend higher than some earlier lows. Towards the very end, the ratio stabilizes around the mid-5 range, indicating a relatively steady turnover rate.
Average Receivable Collection Period
The average collection period inversely mirrors the turnover ratio's trends, as expected. The days outstanding begin at 77 days, rise to a peak of 93 days, then decline to as low as 56 days in later periods, indicating improvements in collection efficiency at those times. However, fluctuations continue with values periodically increasing again, reaching around the high 60s or low 70s towards the end of the dataset. This pattern highlights variability in the payment behavior of customers or changes in credit terms but with a general tendency toward improved collections intermittently.
Overall Trends and Insights
The data reflect a cyclical nature in receivables management performance, with alternating phases of increased and decreased efficiency. The improved receivables turnover alongside reduced collection periods during certain quarters suggest effective credit and collections management at those times. The periodic reversions to lower turnover and higher days outstanding indicate potential external factors or seasonal effects impacting customer payments or company credit policies. The notable peaks and troughs emphasize the need for ongoing attention to credit control to maintain optimal liquidity.

Operating Cycle

Lam Research Corp., operating cycle calculation (quarterly data)

No. days

Microsoft Excel
Sep 28, 2025 Jun 29, 2025 Mar 30, 2025 Dec 29, 2024 Sep 29, 2024 Jun 30, 2024 Mar 31, 2024 Dec 24, 2023 Sep 24, 2023 Jun 25, 2023 Mar 26, 2023 Dec 25, 2022 Sep 25, 2022 Jun 26, 2022 Mar 27, 2022 Dec 26, 2021 Sep 26, 2021 Jun 27, 2021 Mar 28, 2021 Dec 27, 2020 Sep 27, 2020
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.
Micron Technology Inc.
NVIDIA Corp.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-09-28), 10-K (reporting date: 2025-06-29), 10-Q (reporting date: 2025-03-30), 10-Q (reporting date: 2024-12-29), 10-Q (reporting date: 2024-09-29), 10-K (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-Q (reporting date: 2023-12-24), 10-Q (reporting date: 2023-09-24), 10-K (reporting date: 2023-06-25), 10-Q (reporting date: 2023-03-26), 10-Q (reporting date: 2022-12-25), 10-Q (reporting date: 2022-09-25), 10-K (reporting date: 2022-06-26), 10-Q (reporting date: 2022-03-27), 10-Q (reporting date: 2021-12-26), 10-Q (reporting date: 2021-09-26), 10-K (reporting date: 2021-06-27), 10-Q (reporting date: 2021-03-28), 10-Q (reporting date: 2020-12-27), 10-Q (reporting date: 2020-09-27).

1 Q1 2026 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= + =

2 Click competitor name to see calculations.


The financial data reveals several key trends regarding the company's operational efficiency and working capital management over the observed periods.

Average Inventory Processing Period
The average inventory processing period shows a general upward trend from 132 days in late September 2020 to a peak of 208 days in March 2024. After this peak, the period declines to 151 days by late September 2025. This indicates that, initially, the company experienced a lengthening in the time inventory remained on hand, which could imply slower inventory turnover or challenges in managing inventory efficiently. The subsequent decrease after March 2024 suggests an improvement or strategic adjustment leading to faster inventory processing.
Average Receivable Collection Period
The average receivable collection period demonstrates moderate fluctuations around a range of approximately 56 to 93 days. Early periods show some variability, peaking at 93 days in September 2022, but the overall trend is towards stabilization, with collection periods generally staying under 70 days from March 2023 onward. This suggests improved credit control or collection efforts in the latter periods, contributing to more efficient receivables management.
Operating Cycle
The operating cycle, which combines inventory processing and receivable collection periods, follows a similar pattern to the inventory period. It extends from 209 days in late September 2020, increases to a peak of 275 days in December 2023, and then decreases steadily to 219 days by late September 2025. The initial elongation of the operating cycle indicates increased capital tied up in operational processes, potentially stressing liquidity. The subsequent contraction reflects enhanced operational efficiency and working capital turnover.

In summary, the data points to a period of deteriorating working capital efficiency until early 2024, marked by extended inventory and operating cycles. Afterward, the company appears to have executed measures leading to improvements, as shown by shortened inventory processing times and a reduction in the operating cycle. Receivable management remains relatively stable with slight improvements in collection speed over time. These dynamics suggest attention to optimizing operational processes and cash flow management in the more recent periods.


Average Payables Payment Period

Lam Research Corp., average payables payment period calculation (quarterly data)

Microsoft Excel
Sep 28, 2025 Jun 29, 2025 Mar 30, 2025 Dec 29, 2024 Sep 29, 2024 Jun 30, 2024 Mar 31, 2024 Dec 24, 2023 Sep 24, 2023 Jun 25, 2023 Mar 26, 2023 Dec 25, 2022 Sep 25, 2022 Jun 26, 2022 Mar 27, 2022 Dec 26, 2021 Sep 26, 2021 Jun 27, 2021 Mar 28, 2021 Dec 27, 2020 Sep 27, 2020
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.
NVIDIA Corp.
Qualcomm Inc.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-09-28), 10-K (reporting date: 2025-06-29), 10-Q (reporting date: 2025-03-30), 10-Q (reporting date: 2024-12-29), 10-Q (reporting date: 2024-09-29), 10-K (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-Q (reporting date: 2023-12-24), 10-Q (reporting date: 2023-09-24), 10-K (reporting date: 2023-06-25), 10-Q (reporting date: 2023-03-26), 10-Q (reporting date: 2022-12-25), 10-Q (reporting date: 2022-09-25), 10-K (reporting date: 2022-06-26), 10-Q (reporting date: 2022-03-27), 10-Q (reporting date: 2021-12-26), 10-Q (reporting date: 2021-09-26), 10-K (reporting date: 2021-06-27), 10-Q (reporting date: 2021-03-28), 10-Q (reporting date: 2020-12-27), 10-Q (reporting date: 2020-09-27).

1 Q1 2026 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ =

2 Click competitor name to see calculations.


Payables Turnover Ratio Trend
The payables turnover ratio demonstrates a fluctuating pattern over the observed periods. Initially, the ratio exhibits moderate values around 8.8 to 10.1 between late 2020 and late 2021. Subsequently, there is a significant increase reaching a peak of 20.5 in mid-2023, followed by a gradual decline towards values near 11.5 by late 2025. This suggests an increased rate of accounts payable settlement in the middle of the period, followed by a return to more normalized turnover levels in the latest quarters.
Average Payables Payment Period Trend
The average payables payment period measures an opposing trend in terms of days outstanding. The period starts at approximately 41 days in late 2020, decreasing gradually to a low point of 18 days by mid-2023, which corresponds to the peak in payables turnover ratio, indicating faster payments. After this trough, the payment period lengthens again, rising to around 33 days by the end of the data series in late 2025. This indicates a lengthening of the duration taken to settle payables after the aggressive payment period in mid-2023.
Relationship Between Metrics
There is a clear inverse relationship between the payables turnover ratio and the average payables payment period. When the payables turnover ratio peaks, the corresponding payment period shortens significantly, showing that the company accelerated its payments during that interval. Conversely, as the turnover ratio declines from its peak, the payment period increases, signaling a return to longer payment cycles.
Overall Observations
The company's payment behavior shows a cyclical adjustment in payables management over the years, with a pronounced shift toward faster payments in the middle of the period followed by a normalization. This could reflect changes in working capital management strategies, supplier negotiations, or cash flow considerations. The end values indicate a balancing act toward a moderate payment timeframe and turnover ratio, which may aim to optimize supplier relations and internal cash usage.

Cash Conversion Cycle

Lam Research Corp., cash conversion cycle calculation (quarterly data)

No. days

Microsoft Excel
Sep 28, 2025 Jun 29, 2025 Mar 30, 2025 Dec 29, 2024 Sep 29, 2024 Jun 30, 2024 Mar 31, 2024 Dec 24, 2023 Sep 24, 2023 Jun 25, 2023 Mar 26, 2023 Dec 25, 2022 Sep 25, 2022 Jun 26, 2022 Mar 27, 2022 Dec 26, 2021 Sep 26, 2021 Jun 27, 2021 Mar 28, 2021 Dec 27, 2020 Sep 27, 2020
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.
NVIDIA Corp.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-09-28), 10-K (reporting date: 2025-06-29), 10-Q (reporting date: 2025-03-30), 10-Q (reporting date: 2024-12-29), 10-Q (reporting date: 2024-09-29), 10-K (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-Q (reporting date: 2023-12-24), 10-Q (reporting date: 2023-09-24), 10-K (reporting date: 2023-06-25), 10-Q (reporting date: 2023-03-26), 10-Q (reporting date: 2022-12-25), 10-Q (reporting date: 2022-09-25), 10-K (reporting date: 2022-06-26), 10-Q (reporting date: 2022-03-27), 10-Q (reporting date: 2021-12-26), 10-Q (reporting date: 2021-09-26), 10-K (reporting date: 2021-06-27), 10-Q (reporting date: 2021-03-28), 10-Q (reporting date: 2020-12-27), 10-Q (reporting date: 2020-09-27).

1 Q1 2026 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= + =

2 Click competitor name to see calculations.


The financial data reflects several key trends over the analyzed periods related to inventory, receivables, payables, and the cash conversion cycle.

Average Inventory Processing Period
This metric exhibited an increasing trend over the timeline, starting at 132 days and rising steadily to a peak of 208 days before gradually declining to 151 days towards the end. This suggests that the company took progressively longer to process inventory up to a certain point but then improved its inventory turnover efficiency in the later periods.
Average Receivable Collection Period
The receivable collection period showed moderate fluctuations but generally remained within a range of approximately 56 to 93 days. It experienced a notable decrease from a high point above 90 days to lows near 56 days, indicative of improved effectiveness in collecting receivables in some periods, although there were intermittent increases again, pointing to some variability in collections efficiency.
Average Payables Payment Period
The payables payment period decreased initially from around 41 days to as low as 18 days, indicating faster payments to suppliers in the mid timeline. Subsequently, the period gradually increased again to near 35 days but did not return to the original higher levels. This pattern suggests changing strategies or constraints in managing payables, shifting from extended payment terms to quicker settlements and then moderate lengthening.
Cash Conversion Cycle
The cash conversion cycle reflected a trend paralleling the inventory processing period, increasing from 168 days to a peak above 250 days, followed by a decline to 187 days. The prolonged cash conversion cycle during the peak periods implies that working capital was tied up for longer durations, potentially indicating inefficiencies or strategic decisions to hold inventory and manage receivables and payables differently. The eventual reduction suggests some operational improvements in managing the cash conversion process.

Overall, the data indicates the company experienced increased operational cycle lengths in inventory and cash management during the middle of the period analyzed, followed by improvements toward the end. Efficiency in receivables collection showed variability but with some positive improvements, while payables management oscillated between faster and slower payment practices. These trends highlight shifts in working capital dynamics and liquidity management over time.