Stock Analysis on Net

Synopsys Inc. (NASDAQ:SNPS)

$24.99

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

Microsoft Excel

Paying user area


We accept:

Visa Mastercard American Express Maestro Discover JCB PayPal Google Pay
Visa Secure Mastercard Identity Check American Express SafeKey

Short-term Activity Ratios (Summary)

Synopsys Inc., short-term (operating) activity ratios (quarterly data)

Microsoft Excel
Jul 31, 2025 Apr 30, 2025 Jan 31, 2025 Oct 31, 2024 Jul 31, 2024 Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Turnover Ratios
Inventory turnover
Receivables turnover
Working capital turnover
Average No. Days
Average inventory processing period
Add: Average receivable collection period
Operating cycle

Based on: 10-Q (reporting date: 2025-07-31), 10-Q (reporting date: 2025-04-30), 10-Q (reporting date: 2025-01-31), 10-K (reporting date: 2024-10-31), 10-Q (reporting date: 2024-07-31), 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).


The analyzed financial ratios and periods reveal several trends and fluctuations over the quarters. The analysis covers four key metrics: inventory turnover, receivables turnover, working capital turnover, and associated timing periods for inventory processing, receivable collection, and overall operating cycle.

Inventory Turnover
This ratio exhibits a general declining trend from early values above 5.0 in 2019 to under 3.5 by the end of 2025. Starting near 5.32 in early 2019, it experienced fluctuations but mainly decreased, indicating that inventory was turning over less frequently over time. Periodic minor recoveries occurred, such as in early 2022, but the overall direction is downward, suggesting potentially slower inventory movement or buildup.
Receivables Turnover
The receivables turnover ratio displays considerable variability, with no consistent long-term direction. Initial values around 6.07 later fluctuated significantly, peaking multiple times above 7.0 and dipping below 5.0 in several quarters. The highest turnover was seen around mid-2023 (8.29), indicating rapid collection of receivables then, while later periods saw declines toward around 4.62 by late 2025, suggesting slower collections at those later points.
Working Capital Turnover
Working capital turnover ratios were very volatile, showing sharp drops after a peak of 27.06 around late 2019. Subsequent quarters see rapid reductions, often below 10 and dipping as low as 0.43 in mid-2025. This suggests decreasing efficiency or reduced sales relative to working capital, especially toward the most recent quarters, indicative of possibly increased working capital or decreased sales activity.
Average Inventory Processing Period
The days inventory outstanding increased initially from 69 days to above 100 days between 2019 and 2020, indicating longer holding periods. Subsequently, it oscillated between roughly 70 and 120 days, trending higher toward 2024 and mid-2025, reaching as high as 123 days. This aligns with the declining inventory turnover ratio, implying slower inventory movement and longer storage times.
Average Receivable Collection Period
The average days to collect receivables show considerable fluctuations, ranging from under 50 days to over 80 days. Periods of quicker collection (around 44-50 days) were interspersed with times of longer collection periods (reaching 84 and up to 79 days). Overall, the collection period rounds between moderate and extended durations, without a clear sustained trend toward speedier collections.
Operating Cycle
The operating cycle, summing inventory and receivables periods, generally remains high, fluctuating between approximately 130 and 180 days. Peaks above 170 days occur sporadically, often corresponding with increased inventory processing or receivable collection times. This sustained extended operating cycle indicates that the company's cash conversion process experienced lengthening periods, which may affect liquidity management.

In summary, trends indicate a slowing turnover in inventory and working capital, with longer inventory processing and steady to slightly extended receivable collection times. The operating cycle's lengthening corroborates these findings, signaling challenges in asset utilization efficiency and potential impacts on working capital management over the observed periods.


Turnover Ratios


Average No. Days


Inventory Turnover

Synopsys Inc., inventory turnover calculation (quarterly data)

Microsoft Excel
Jul 31, 2025 Apr 30, 2025 Jan 31, 2025 Oct 31, 2024 Jul 31, 2024 Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data (US$ in thousands)
Cost of revenue
Inventories
Short-term Activity Ratio
Inventory turnover1
Benchmarks
Inventory Turnover, Competitors2
Cadence Design Systems Inc.
International Business Machines Corp.
Microsoft Corp.

Based on: 10-Q (reporting date: 2025-07-31), 10-Q (reporting date: 2025-04-30), 10-Q (reporting date: 2025-01-31), 10-K (reporting date: 2024-10-31), 10-Q (reporting date: 2024-07-31), 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q3 2025 Calculation
Inventory turnover = (Cost of revenueQ3 2025 + Cost of revenueQ2 2025 + Cost of revenueQ1 2025 + Cost of revenueQ4 2024) ÷ Inventories
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The financial data reveals notable fluctuations in both the cost of revenue and inventories across the quarters from January 2019 to July 2025. A detailed examination of these key items and the derived inventory turnover ratio provides insights into operational and business trends over this extended period.

Cost of Revenue
The cost of revenue displays a generally upward trend over the observed periods, starting at approximately 193 million US dollars in the first quarter of 2019 and reaching over 380 million by mid-2025. There are fluctuations within this growth: for instance, a marked increase is evident in late 2020, where the cost rose significantly from around 193 million to over 224 million US dollars. This elevated level is mostly sustained, with periodic increases thereafter, culminating in a peak exceeding 380 million by the third quarter of 2025. Some quarters show decreases compared to prior periods, but the overall trajectory is upward.
Inventories
Inventories exhibit a consistent increase from roughly 138 thousand US dollars in early 2019 to a peak of over 415 thousand US dollars in the first quarter of 2025. This rise is not strictly linear; smaller declines and plateaus occur, such as a noticeable reduction in inventories between late 2020 and early 2021, followed by a subsequent rise. Post-2020, the inventory level shows more volatility but maintains an upward trend overall. Inventory values remain relatively high through mid-2025, suggesting accumulation or slower turnover in the later periods.
Inventory Turnover Ratio
The inventory turnover ratio, derived from the available data starting in the first quarter of 2020, shows a declining trend until around early 2023, dropping from a high of approximately 5.32 to lows near 2.98 to 3.18 by 2024. This decline indicates that inventory was turning over more slowly over this timeframe, potentially pointing to slower sales or increased inventory holdings relative to cost of revenue. After reaching this low point, the ratio sees a mild recovery towards mid-2025, rising back to levels around 3.5. This pattern suggests a possible improvement in inventory management or sales velocity in recent quarters.

In summary, the data portrays an expanding scale of business activity as evidenced by rising cost of revenue and inventory balances. However, the inventory turnover ratio trend implies inventory has been held longer relative to sales through most of the period, with some signs of operational improvements more recently. These dynamics may reflect changes in demand patterns, supply chain considerations, or strategic inventory management decisions over time.


Receivables Turnover

Synopsys Inc., receivables turnover calculation (quarterly data)

Microsoft Excel
Jul 31, 2025 Apr 30, 2025 Jan 31, 2025 Oct 31, 2024 Jul 31, 2024 Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data (US$ in thousands)
Revenue
Accounts receivable, net
Short-term Activity Ratio
Receivables turnover1
Benchmarks
Receivables Turnover, Competitors2
Adobe Inc.
Cadence Design Systems Inc.
CrowdStrike Holdings Inc.
Datadog Inc.
Fair Isaac Corp.
International Business Machines Corp.
Intuit Inc.
Microsoft Corp.
Oracle Corp.
Palantir Technologies Inc.
Palo Alto Networks Inc.
Salesforce Inc.
ServiceNow Inc.
Workday Inc.

Based on: 10-Q (reporting date: 2025-07-31), 10-Q (reporting date: 2025-04-30), 10-Q (reporting date: 2025-01-31), 10-K (reporting date: 2024-10-31), 10-Q (reporting date: 2024-07-31), 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q3 2025 Calculation
Receivables turnover = (RevenueQ3 2025 + RevenueQ2 2025 + RevenueQ1 2025 + RevenueQ4 2024) ÷ Accounts receivable, net
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The revenue exhibits a generally upward trend from January 2019 through July 2025, with some fluctuations across quarters. Initial growth is modest, with revenue increasing from $820,401 thousand in January 2019 to $1,162,419 thousand in October 2021. Following this, revenue maintains a strong growth trajectory, peaking intermittently around $1,599,128 thousand in October 2023 before experiencing some periods of decline and recovery. The most recent data show a fluctuating pattern with revenue hitting $1,739,737 thousand in July 2025, indicating overall expansion with quarterly variations.

Accounts receivable demonstrate considerable volatility over the same period. Beginning at $762,292 thousand in January 2019, the figures decrease significantly through mid-2019, then surge and fluctuate throughout the subsequent years. The accounts receivable reached a prominent peak in January 2022 ($1,038,749 thousand), sharply declined afterward, and again climbed to a high of $1,392,373 thousand by July 2025. This pattern points to inconsistent collection cycles or changes in sales credit terms, impacting the outstanding balances.

The receivables turnover ratio, available from July 2019 onward, fluctuates between 4.22 and 8.29 across quarters. Higher turnover values suggest improved efficiency in collecting receivables, observed notably in quarters like January 2021 (7.40) and October 2023 (8.29). Lower ratios, such as in April 2020 (4.22) and July 2025 (4.62), reflect slower collection periods or higher outstanding receivables relative to sales. The variation in this ratio is consistent with the observed volatility in accounts receivable balances, underlining periodic changes in credit management or customer payment behavior.

In summary, revenue growth is positive but marked by quarterly fluctuations, while accounts receivable values show significant instability, likely affecting cash flow dynamics. The receivables turnover oscillates, reflecting shifts in collection efficiency and credit policies. These patterns suggest the need for ongoing monitoring of credit risk and working capital management to support sustained revenue growth.


Working Capital Turnover

Synopsys Inc., working capital turnover calculation (quarterly data)

Microsoft Excel
Jul 31, 2025 Apr 30, 2025 Jan 31, 2025 Oct 31, 2024 Jul 31, 2024 Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
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
Accenture PLC
Adobe Inc.
Cadence Design Systems Inc.
CrowdStrike Holdings Inc.
Datadog Inc.
Fair Isaac Corp.
International Business Machines Corp.
Intuit Inc.
Microsoft Corp.
Oracle Corp.
Palantir Technologies Inc.
Palo Alto Networks Inc.
Salesforce Inc.
ServiceNow Inc.
Workday Inc.

Based on: 10-Q (reporting date: 2025-07-31), 10-Q (reporting date: 2025-04-30), 10-Q (reporting date: 2025-01-31), 10-K (reporting date: 2024-10-31), 10-Q (reporting date: 2024-07-31), 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q3 2025 Calculation
Working capital turnover = (RevenueQ3 2025 + RevenueQ2 2025 + RevenueQ1 2025 + RevenueQ4 2024) ÷ Working capital
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The financial data reveals several notable trends over the periods presented.

Working Capital
The working capital shows considerable volatility over the timeline. Initially, working capital was negative, with large deficits at the start of 2019 and through early 2020, reflecting short-term liabilities exceeding current assets. However, beginning in mid-2020, there is a significant positive shift, with working capital turning favorable and increasing substantially, peaking in early 2025. Despite this upward trend, there is a marked fluctuation in the last few periods, including a substantial increase in Jan 2025 followed by a sharp decline in Apr and Jul 2025.
Revenue
Revenue generally trends upward across the periods, reflecting consistent growth. From early 2019 through early 2025, revenue increased steadily with few exceptions. Some minor fluctuations occur, notably around mid-2022 and early 2025, but the overall trend is positive. The growth accelerated more prominently starting from 2020, likely indicating expanding business operations or market demand.
Working Capital Turnover
The working capital turnover ratio starts data availability in the latter part of 2020. Initially, it recorded a very high ratio (27.06), which fell into single-digit values and fluctuated thereafter. This suggests varying efficiency in utilizing working capital to generate revenue. After an initial period of volatility, turnover ratios generally decline progressing towards 2025, reaching very low levels below 1. This decreasing trend indicates that the company is either holding higher working capital relative to its revenue or experiencing less efficient asset utilization in its short-term operations over time.

In summary, the data indicates that while revenue demonstrates steady growth, the company's working capital position improved notably after 2020 but with increased volatility in later years. The efficiency in using working capital to generate revenue, as reflected by the turnover ratio, appears to be declining, which might warrant further examination of working capital management and operational effectiveness.


Average Inventory Processing Period

Synopsys Inc., average inventory processing period calculation (quarterly data)

Microsoft Excel
Jul 31, 2025 Apr 30, 2025 Jan 31, 2025 Oct 31, 2024 Jul 31, 2024 Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data
Inventory turnover
Short-term Activity Ratio (no. days)
Average inventory processing period1
Benchmarks (no. days)
Average Inventory Processing Period, Competitors2
Cadence Design Systems Inc.
International Business Machines Corp.
Microsoft Corp.

Based on: 10-Q (reporting date: 2025-07-31), 10-Q (reporting date: 2025-04-30), 10-Q (reporting date: 2025-01-31), 10-K (reporting date: 2024-10-31), 10-Q (reporting date: 2024-07-31), 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q3 2025 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =

2 Click competitor name to see calculations.


The inventory turnover ratio exhibits a clear downward trend from early 2020 through mid-2024, indicating a gradual decline in the frequency with which inventory is sold and replaced over this period. Starting at 5.32 in January 2020, the ratio decreases steadily to a low near 3.12 by October 2024, with minor fluctuations along the way. This decline suggests a slowing in inventory movement, potentially implying increased inventory levels relative to sales or reduced sales velocity over the analyzed time span. Toward the last observed quarters, there is a slight uptick, though the ratio remains below earlier values from 2020.

Correspondingly, the average inventory processing period, measured in days, reflects an inverse pattern to the inventory turnover ratio. Beginning at 69 days in January 2020, this metric increases progressively, peaking around 123 days in April 2025. The upward trend in inventory processing duration suggests that inventory is held longer before being sold, which aligns with the decreasing turnover ratio noted above. The increase in holding periods points to potential challenges in inventory management efficiency or shifts in demand patterns requiring longer inventory retention.

The inverse relationship between the inventory turnover ratio and the average inventory processing period is consistent throughout the intervals reported. As turnover decreases, the processing period lengthens, indicating slower movement through inventory. These patterns may reflect broader operational or market conditions affecting inventory dynamics, such as supply chain disruptions, changes in product demand, or strategic shifts in inventory policies.

Inventory Turnover Ratio
Decreased from 5.32 in early 2020 to approximately 3.12 by late 2024, indicating a slowdown in inventory cycling.
Average Inventory Processing Period
Increased from 69 days to a peak near 123 days, demonstrating longer inventory holding periods.
Overall Insight
The inverse movement of these metrics points to less efficient inventory management or altered market conditions resulting in slower sales and extended inventory retention over the periods analyzed.

Average Receivable Collection Period

Synopsys Inc., average receivable collection period calculation (quarterly data)

Microsoft Excel
Jul 31, 2025 Apr 30, 2025 Jan 31, 2025 Oct 31, 2024 Jul 31, 2024 Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data
Receivables turnover
Short-term Activity Ratio (no. days)
Average receivable collection period1
Benchmarks (no. days)
Average Receivable Collection Period, Competitors2
Adobe Inc.
Cadence Design Systems Inc.
CrowdStrike Holdings Inc.
Datadog Inc.
Fair Isaac Corp.
International Business Machines Corp.
Intuit Inc.
Microsoft Corp.
Oracle Corp.
Palantir Technologies Inc.
Palo Alto Networks Inc.
Salesforce Inc.
ServiceNow Inc.
Workday Inc.

Based on: 10-Q (reporting date: 2025-07-31), 10-Q (reporting date: 2025-04-30), 10-Q (reporting date: 2025-01-31), 10-K (reporting date: 2024-10-31), 10-Q (reporting date: 2024-07-31), 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q3 2025 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =

2 Click competitor name to see calculations.


The receivables turnover ratio demonstrates notable fluctuations over the observed quarterly periods. Initially, the data from early 2019 is unavailable, but starting from January 2020, the ratio shows a decline from 6.07 to a low of 4.22 in April 2020, suggesting a slowdown in collections or credit sales management during that period. Subsequently, the ratio improves steadily, reaching a peak of 7.40 in January 2022, indicating more effective collections and possibly stronger cash flow management.

Following the peak, there is a sharp decrease in April 2022 to 4.34, reflecting potentially worsening collection efficiency. However, after this trough, the turnover ratio again rises and fluctuates around the 6.0 to 8.0 range from mid-2022 through early 2024, signaling periods of improved receivables management interspersed with moderate declines. The latest available data from October 2024 and January 2025 indicate a downward trend, dropping to 4.62 by July 2025, which might reflect recent challenges in receivables collection.

Regarding the average receivable collection period, this metric inversely mirrors the turnover ratio trends. Beginning in January 2020, the collection period extends notably from 60 days to a peak of 86 days in April 2020, consistent with the drop in turnover ratio and implying delayed collections. This period shortens significantly by January 2022, reaching a low of 49 days, aligning with the peak in turnover ratio and enhanced collection efficiency.

Subsequent quarters see the collection period increase once again, peaking at 84 days in April 2022, indicative of slower receivables turnover. After that, although there are fluctuations, the collection period generally decreases and stabilizes mostly in the 44 to 65 days range through early 2024, correlating with a generally higher turnover ratio. Toward the latest periods, a slight increase is observed, concluding with a rise to 79 days by July 2025, suggesting some emerging delays in receivables collection.

Overall, the analysis reveals a cyclical pattern in receivables management, with periods of efficiency followed by intervals of delayed collections. The fluctuations in both metrics demonstrate the company's varying effectiveness in converting receivables to cash over time. Attention should be given to recent downward trends in turnover and upward trends in collection days that could affect liquidity if sustained.


Operating Cycle

Synopsys Inc., operating cycle calculation (quarterly data)

No. days

Microsoft Excel
Jul 31, 2025 Apr 30, 2025 Jan 31, 2025 Oct 31, 2024 Jul 31, 2024 Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data
Average inventory processing period
Average receivable collection period
Short-term Activity Ratio
Operating cycle1
Benchmarks
Operating Cycle, Competitors2
Cadence Design Systems Inc.
International Business Machines Corp.
Microsoft Corp.

Based on: 10-Q (reporting date: 2025-07-31), 10-Q (reporting date: 2025-04-30), 10-Q (reporting date: 2025-01-31), 10-K (reporting date: 2024-10-31), 10-Q (reporting date: 2024-07-31), 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q3 2025 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= + =

2 Click competitor name to see calculations.


The data reveals distinct patterns across the three analyzed financial periods, measured in number of days, highlighting several operational and working capital management aspects.

Average Inventory Processing Period
The average inventory processing period shows a general upward trend from early 2020 through subsequent years. Starting at 69 days in January 2020, the figure increased steadily to peak at 115 days in July 2024. There is some variability thereafter, with shorter durations observed at times, such as 73 days in January 2023, but the overall tendency is toward longer processing intervals. This suggests an increasing time to convert inventory into sales, potentially impacting liquidity and inventory turnover efficiency.
Average Receivable Collection Period
The average receivable collection period exhibits greater fluctuation across the timeframe. Initially holding around 60 days in early 2020, it experienced spikes and troughs, reaching a notable peak of 86 days in April 2020, followed by periods as low as 44 days in July 2023. These oscillations reflect varying credit collection effectiveness or changing customer payment behaviors. The pattern indicates inconsistencies in receivables management, which may affect cash flow stability.
Operating Cycle
The operating cycle combines the intervals of inventory processing and receivables collection, providing a comprehensive view of working capital efficiency. It shows a marked increase from 129 days in January 2020, rising to a high of 180 days in July 2024. While the data includes fluctuations, the general trend toward lengthening operating cycles could signal extended capital tie-up periods, reducing operational agility and potentially increasing financing costs.

Overall, the trends point to lengthening durations in inventory handling and overall operating cycles, coupled with irregular receivables collection times. These factors highlight areas where operational and financial management might focus efforts to enhance turnover rates and improve cash conversion timings.