Stock Analysis on Net

Fortinet Inc. (NASDAQ:FTNT)

$22.49

This company has been moved to the archive! The financial data has not been updated since May 8, 2023.

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

Microsoft Excel

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Short-term Activity Ratios (Summary)

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

Microsoft Excel
Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
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: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).


The financial ratios and periods analyzed reveal fluctuating operational efficiency and cash management dynamics over time.

Inventory turnover
The ratio displays a moderate decline from 5.62 in September 2019 to 3.76 in March 2023, indicating slower inventory movement. Peaks occurred around mid-2019, followed by a gradual reduction, suggesting potential inventory accumulation or slower sales.
Receivables turnover
This ratio varies within a range with a high around 5.33 in December 2019 and lows near 3.5 in March 2023. The pattern reflects inconsistencies in collecting receivables, with some periods showing better efficiency and others indicating slower collections.
Payables turnover
The payables turnover ratio shows a peak around mid-2019 at approximately 6.74, followed by a decline to about 4.46 in September 2022, with slight recovery towards March 2023. This suggests a lengthening in the time taken to pay suppliers over the period.
Working capital turnover
The working capital turnover ratio exhibits significant volatility, with a notable jump beginning in mid-2021, reaching a maximum of 20.23 in December 2022, before declining. This sharp increase implies improved efficiency in using working capital temporarily, followed by a reversion.
Average inventory processing period
The duration has generally increased over the observed quarters, rising from about 65 days in September 2018 to peaks close to 97 days by March 2023. This corresponds with the lower inventory turnover ratio and suggests longer holding times of inventory.
Average receivable collection period
The number of days to collect receivables fluctuates, with values ranging roughly between 68 and 104 days. A notable increase occurs in early 2020 and again in late 2022, indicating occasional delays in collections.
Operating cycle
The operating cycle duration generally increased from about 140 days in late 2018 to over 190 days in late 2020, then slightly declined but remained elevated around 180 days by early 2023. The extended cycle points to longer time spans between inventory acquisition and cash collection.
Average payables payment period
There is a gradual increase in the days payable, rising from approximately 54 days in mid-2018 to over 80 days by late 2022. The trend indicates an increased period for settling obligations, likely used as a cash management strategy.
Cash conversion cycle
The cash conversion cycle shows variability with an overall trend toward lengthening, moving from about 78 days in late 2018 to peaks above 110 days in late 2022 and early 2023. This suggests a longer time to convert resources to cash, which could impact liquidity.

Overall, the data indicates a trend of longer inventory holding and receivables collection periods, coupled with extended payable payment terms. While working capital turnover showed temporary improvements, the widening cash conversion cycle highlights potential challenges in operational cash flow efficiency toward the most recent quarters analyzed.


Turnover Ratios


Average No. Days


Inventory Turnover

Fortinet Inc., inventory turnover calculation (quarterly data)

Microsoft Excel
Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
Selected Financial Data (US$ in thousands)
Cost of revenue
Inventory
Short-term Activity Ratio
Inventory turnover1
Benchmarks
Inventory Turnover, Competitors2
Cadence Design Systems Inc.
International Business Machines Corp.
Microsoft Corp.
Synopsys Inc.

Based on: 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).

1 Q1 2023 Calculation
Inventory turnover = (Cost of revenueQ1 2023 + Cost of revenueQ4 2022 + Cost of revenueQ3 2022 + Cost of revenueQ2 2022) ÷ Inventory
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


Cost of Revenue
The cost of revenue shows a general upward trend over the reviewed periods. Starting from 97,200 thousand USD in March 2018, it experienced incremental increases with some seasonal fluctuations, reaching 307,800 thousand USD by March 2023. Notable rises occurred in the quarters ending December 2020, September 2021, and from March 2022 onward, indicating an expansion in operational scale or higher production costs over time.
Inventory Levels
Inventory levels demonstrate a consistent growth trend. Beginning at 80,000 thousand USD in March 2018, the figures rose steadily, surpassing 300,000 thousand USD by March 2023. This more than threefold increase reflects an accumulation of stock, which may be correlated with increased sales demands, expansion strategies, or cautious supply chain management. The period between 2021 and 2023 especially marks significant inventory buildup, suggesting preparation for higher sales volume or potential supply constraints.
Inventory Turnover Ratio
Inventory turnover ratio data is available from March 2019 onward, showing values predominantly in the range of approximately 3.76 to 5.62 times. The ratio peaked at 5.62 in September 2019, indicating more efficient inventory movement at that time. Subsequently, it experienced a general declining trend, dropping to 3.76 by March 2023. This decline suggests slower inventory turnover relative to past periods, which may imply increased inventory holding periods, potentially reflecting changes in demand, supply chain challenges, or shifts in product mix.
Summary of Relationships and Trends
There is a consistent increase in both cost of revenue and inventory levels over the analyzed timeframe. Meanwhile, the decreasing inventory turnover ratio over recent periods suggests that inventory is being held longer relative to sales. The combination points to the possibility of increasing challenges in managing inventory efficiently or a strategic decision to maintain higher stock levels in anticipation of market conditions. The rising cost of revenue aligns with growing business scale but could also indicate margin pressures if inventory turnover is slowing.

Receivables Turnover

Fortinet Inc., receivables turnover calculation (quarterly data)

Microsoft Excel
Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
Selected Financial Data (US$ in thousands)
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.
Synopsys Inc.
Workday Inc.

Based on: 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).

1 Q1 2023 Calculation
Receivables turnover = (RevenueQ1 2023 + RevenueQ4 2022 + RevenueQ3 2022 + RevenueQ2 2022) ÷ Accounts receivable, net
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


Revenue Trends
Revenue demonstrates a consistent upward trajectory over the analyzed quarters, growing from $399,000 thousand in March 2018 to a peak of $1,283,000 thousand in March 2023. This reflects a significant expansion in sales or service income over the five-year period. Notably, the revenue growth accelerated after 2020, suggesting an enhanced market presence or increased demand. Seasonal variations are evident but overshadowed by the overall positive growth trend.
Accounts Receivable Trends
Accounts receivable, net, also increased markedly, rising from $313,100 thousand in March 2018 to $1,087,200 thousand by March 2023. This increase suggests an expansion in credit sales or a higher volume of customer payments pending collection. The substantial jump around late 2020 and early 2021 indicates either more aggressive sales on credit terms or potential delays in collection. The growth in receivables aligns with the revenue increase but appears more volatile with sharper increases and fluctuations.
Receivables Turnover Ratio Analysis
The receivables turnover ratio fluctuates within a range of approximately 3.5 to 5.33 during the observed periods. Higher turnover values, such as those around late 2018 and 2021, indicate more efficient collection processes or shorter credit periods, while lower values, especially near early 2023, point to a slowdown in collections or extended payment terms. The ratio trends downward in the final quarters, which could imply potential challenges in receivables management or changes in customer payment behavior.
Overall Observations
The data reflects robust revenue growth accompanied by increasing accounts receivable. However, the decline in the receivables turnover ratio toward the end of the period suggests that the company's efficiency in collection may have diminished. This disparity between rising receivables and decreasing turnover ratio may warrant further management attention to optimize working capital and cash flow.

Payables Turnover

Fortinet Inc., payables turnover calculation (quarterly data)

Microsoft Excel
Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
Selected Financial Data (US$ in thousands)
Cost of revenue
Accounts payable
Short-term Activity Ratio
Payables turnover1
Benchmarks
Payables Turnover, Competitors2
Accenture PLC
Adobe 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.
ServiceNow Inc.
Workday Inc.

Based on: 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).

1 Q1 2023 Calculation
Payables turnover = (Cost of revenueQ1 2023 + Cost of revenueQ4 2022 + Cost of revenueQ3 2022 + Cost of revenueQ2 2022) ÷ Accounts payable
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The cost of revenue for the company exhibits a consistent upward trend over the analyzed periods, increasing from approximately $97.2 million in the first quarter of 2018 to around $307.8 million by the first quarter of 2023. This reflects a general growth in the company's expenditure related to generating revenue, with noticeable accelerations particularly evident starting from mid-2020 onward. The increase in cost appears steady without significant volatility, suggesting expanding operations or rising costs in line with revenue growth.

Accounts payable shows a similar overall upward trajectory, rising from $55.7 million in Q1 2018 to a peak of $243.4 million in Q4 2022, before slightly decreasing to $238.4 million in Q1 2023. The increases indicate growing short-term obligations, possibly due to higher purchases on credit parallel to the growth in cost of revenue. The minor decline at the end could suggest improved payables management or timing differences in payments.

The payables turnover ratio, available from the third quarter of 2018 onward, fluctuates within the range of approximately 4.03 to 6.74 but displays a general declining trend over the periods. The ratio peaked at 6.74 in Q2 2019 but declined to around 4.46 by Q4 2022, with a slight uptick to 4.78 in Q1 2023. This decreasing trend indicates that the company is taking longer to pay its suppliers on average, reflecting possibly extended payment terms or liquidity management strategies.

Cost of Revenue
Steady and substantial increase over 5 years, with an acceleration starting mid-2020.
Consistent rise reflects growing scale of operations or increasing input costs.
Accounts Payable
Marked upward movement, nearly quadrupling from 2018 to late 2022.
Slight reduction in early 2023 may indicate improved payment cycle management.
Payables Turnover Ratio
Initial fluctuations stabilize into a downward trend from mid-2019 onward.
The decline suggests lengthening payment periods, possibly reflecting strategic cash flow management or vendor negotiations.

Overall, the data illustrates a growing company with increasing operational scale, as evidenced by rising costs and payables. Concurrently, the moderation in payables turnover highlights extended payment terms or liquidity preservation tactics. These patterns suggest a focus on balancing growth with cash flow optimization.


Working Capital Turnover

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

Microsoft Excel
Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
Selected Financial Data (US$ in thousands)
Current assets
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.
Synopsys Inc.
Workday Inc.

Based on: 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).

1 Q1 2023 Calculation
Working capital turnover = (RevenueQ1 2023 + RevenueQ4 2022 + RevenueQ3 2022 + RevenueQ2 2022) ÷ Working capital
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


Working Capital
The working capital demonstrates significant fluctuations over the analyzed period. Initially, it shows a steady upward trend from 706,100 thousand US$ in March 2018 to a peak of approximately 1,295,400 thousand US$ at the end of 2019. A sharp decline occurs in early 2020, reaching a low point around mid-2022 at 202,600 thousand US$. Following this trough, there is a moderate recovery, with working capital increasing to approximately 1,096,900 thousand US$ by the first quarter of 2023.
Revenue
Revenue presents a general upward trend throughout the period. Starting from 399,000 thousand US$ in the first quarter of 2018, it rises steadily with some minor quarter-to-quarter variations, peaking near 1,283,000 thousand US$ by the end of 2022. Despite a small downturn in early 2023, revenue remains significantly higher than at the beginning of the period, indicating sustained growth over the five-year span.
Working Capital Turnover Ratio
The working capital turnover ratio exhibits considerable volatility and an overall increasing trend. Early measurements (starting from March 2019) show ratios generally between 1.43 and 1.87. There is a notable spike starting in late 2020, reaching values as high as 20.23 in late 2022, indicating more efficient use of working capital during this period. However, the final recorded quarter in early 2023 shows a decline to 4.31, suggesting a partial normalization or reduced efficiency relative to the peak.
Observations and Insights
The initial growth in working capital through 2019 coincides with a steady increase in revenue, suggesting expansion. The sharp working capital decline in 2020 may be indicative of operational adjustments or strategic changes, possibly in response to external economic factors. Concurrently, revenue continues to grow, implying resilience or successful adaptation. The rising working capital turnover ratio from 2020 to 2022, peaking in late 2022, points to improved utilization of working capital to generate sales, though the subsequent fall in early 2023 suggests this efficiency may be reverting to more typical levels. The overall data signifies a period of growth with some volatility in working capital management, but a consistent upward trend in revenue generation.

Average Inventory Processing Period

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

Microsoft Excel
Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
Selected Financial Data
Inventory turnover
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.
Synopsys Inc.

Based on: 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).

1 Q1 2023 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =

2 Click competitor name to see calculations.


Inventory Turnover Ratio
The inventory turnover ratio demonstrates variability throughout the observed periods. Starting from a value of 5 in the quarter ending March 31, 2019, it generally shows a declining trend over time. There is a peak at 5.62 in September 2019, followed by a decrease to around 4.04 to 4.08 during the end of 2020 and early 2021. From mid-2021 onward, the ratio oscillates in a range between approximately 4 and 4.8 but declines to its lowest point of 3.76 by the quarter ending March 31, 2023. This declining trend indicates a slower movement of inventory over the periods analyzed.
Average Inventory Processing Period
Conversely, the average inventory processing period, measured in days, exhibits an overall increasing trend during the same timeframe. Beginning at 73 days in March 2019, the number of days decreases to a low near 65 days by September 2019 but then rises notably, reaching 90 days by the end of 2020 and maintaining around the 90-day mark for the early part of 2021. The period fluctuates somewhat but remains elevated, culminating in a peak of 97 days at the end of the series, in March 2023. This increase reflects a longer duration to process or turn over inventory, aligning with the observed reduction in inventory turnover ratio.
Insights
The inverse relationship between the inventory turnover ratio and the average inventory processing period is evident, as expected, with the former declining while the latter extends. This suggests that inventory is moving more slowly through the company’s operations over the quarters, potentially indicating changes in demand, supply chain efficiency, inventory management practices, or product mix. The extended processing period towards the end of the data set may warrant further examination to identify underlying causes and assess potential impacts on working capital and operational efficiency.

Average Receivable Collection Period

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

Microsoft Excel
Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
Selected Financial Data
Receivables turnover
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.
Synopsys Inc.
Workday Inc.

Based on: 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).

1 Q1 2023 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =

2 Click competitor name to see calculations.


Receivables Turnover Ratio
The receivables turnover ratio shows fluctuations across the observed period, starting from 4.05 and peaking around 5.33 at the end of 2018. It then declines to 3.6 by the end of the first quarter of 2021, followed by a recovery to a high of 5.17 in the third quarter of 2021. Subsequently, it gradually decreases again, reaching a low of 3.5 in the first quarter of 2023 before rising slightly to 4.35.
Average Receivable Collection Period
The average receivable collection period exhibits an inverse pattern to the receivables turnover, starting around 90 days and improving to as low as 68 days at the end of 2018. After this improvement, it deteriorates, increasing to 101 days by March 2021. A recovery follows, with the period decreasing to as few as 71 days in the fourth quarter of 2021. Then, it again trends upward, peaking at 104 days in the first quarter of 2023, before a slight improvement to 84 days.
Overall Trend and Interpretation
Overall, the data indicates periods of improvement in the efficiency of receivables collection, especially noticeable in late 2018 and late 2021, as reflected by higher receivables turnover ratios and shorter collection periods. However, these improvements were followed by deteriorations, suggesting volatile management of receivables over the timeframe. The recent trend towards longer collection periods and lower turnover ratios in early 2023 may signal challenges in receivables management or changes in credit policies that could impact cash flow efficiency.

Operating Cycle

Fortinet Inc., operating cycle calculation (quarterly data)

No. days

Microsoft Excel
Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
Selected Financial Data
Average inventory processing period
Average receivable collection period
Short-term Activity Ratio
Operating cycle1
Benchmarks
Operating Cycle, Competitors2
Cadence Design Systems Inc.
International Business Machines Corp.
Microsoft Corp.
Synopsys Inc.

Based on: 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).

1 Q1 2023 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= + =

2 Click competitor name to see calculations.


The financial data reveals evolving trends in the company's efficiency metrics, specifically focusing on inventory management, receivables collection, and the overall operating cycle over a series of quarterly periods.

Average Inventory Processing Period
The average inventory processing period displays fluctuations with no clear linear trend but generally maintains a range between approximately 65 to 97 days. Starting from 73 days in early 2019, the period dips to 65 days by late 2019 before rising and stabilizing around the 85 to 90-day mark in 2020 and 2021. A modest decline occurs thereafter, reaching 75 days in late 2022. However, it again increases towards 97 days by the first quarter of 2023, suggesting occasional inefficiency in inventory turnover or potential changes in inventory strategy.
Average Receivable Collection Period
The average receivable collection period shows more variability, ranging mainly between 68 to 104 days. Initially, a reduction is observed from 90 days to 68 days during 2018 and 2019, indicating improved collection efficiency. This improvement, however, is not sustained as the period lengthens again in 2020, peaking at 101 days. The data reflects some recovery with periods generally falling back to the 70s and 80s between 2021 and 2022. Notably, the collection period peaks again at 104 days near the end of 2022 before slightly decreasing to 84 days in early 2023, indicating inconsistent receivables management.
Operating Cycle
The operating cycle, which combines inventory processing and receivables collection periods, shows a fluctuating upward trend over the analyzed timeframe. Beginning near 140 days in late 2018, it rises to a high of approximately 193 days by the end of 2022 before a marginal decrease to 181 days in the first quarter of 2023. The general increase in the operating cycle signals a lengthening time between cash outflows for inventory and cash inflows from receivables, potentially impacting liquidity and working capital efficiency adversely.

In summary, the data highlights a general trend of increased durations in all three analyzed efficiency measures over time, with notable volatility. The periods where inventory processing or receivables collection extend suggest operational challenges that may affect cash flow and overall financial agility. The increasing operating cycle reflects this growing lag in operational turnover, which could warrant closer monitoring and targeted management interventions to optimize working capital.


Average Payables Payment Period

Fortinet Inc., average payables payment period calculation (quarterly data)

Microsoft Excel
Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
Selected Financial Data
Payables turnover
Short-term Activity Ratio (no. days)
Average payables payment period1
Benchmarks (no. days)
Average Payables Payment Period, Competitors2
Accenture PLC
Adobe 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.
ServiceNow Inc.
Workday Inc.

Based on: 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).

1 Q1 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 a fluctuating trend over the reported periods. Starting from a ratio of 5.21 in March 2019, it peaked at 6.74 in June 2019, signaling a faster rate of payment to suppliers during that quarter. Thereafter, the ratio declined with some volatility, experiencing lows around 4.03 in March 2021. Through the subsequent quarters, the ratio showed moderate recovery and some stability, ranging mostly between 4.46 and 5.28, ending at 4.78 in March 2023. The overall pattern indicates a general slowing in payables turnover, suggesting the company may be taking longer to settle its obligations in more recent periods compared to the mid-2019 peak.
Average payables payment period (number of days)
The average payables payment period is inversely related to the payables turnover ratio, showing corresponding fluctuations. It began at 70 days in March 2019, shortened significantly to 54 days by June 2019, aligning with the increased turnover ratio in the same period. Following this low point, the payment period extended again, reaching a high of 91 days in March 2021, indicating a slower payment cycle. After this peak, the payment period decreased to around 69-72 days for several subsequent quarters before extending again, ultimately recording 76 days in March 2023. The general trend signals that the company temporarily accelerated payment to suppliers mid-2019 but has since experienced lengthening payment cycles, potentially as a cash flow management measure or reflecting changing supplier terms.

Cash Conversion Cycle

Fortinet Inc., cash conversion cycle calculation (quarterly data)

No. days

Microsoft Excel
Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
Selected Financial Data
Average inventory processing period
Average receivable collection period
Average payables payment period
Short-term Activity Ratio
Cash conversion cycle1
Benchmarks
Cash Conversion Cycle, Competitors2
International Business Machines Corp.
Microsoft Corp.

Based on: 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31).

1 Q1 2023 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= + =

2 Click competitor name to see calculations.


Average Inventory Processing Period
The average inventory processing period shows variability over the observed quarters. Starting from 73 days in March 2019, it declined steadily to 65 days by September 2019, indicating improved inventory management. However, from the end of 2019 through 2020 and into early 2021, the period generally increased, peaking at 91 days in March 2021. This suggests slowing inventory turnover during this time. Following the peak, a moderate decline occurred throughout 2021 and 2022, with the period reducing to 75 days by September 2022. Nonetheless, the last two quarters of the dataset show an upward trend again, reaching 97 days by March 2023, indicating a recent lengthening in inventory holding times.
Average Receivable Collection Period
The average receivable collection period experienced fluctuations but remained generally stable in the mid-range from 2019 to 2020, varying between 68 and 92 days. A notable increase occurred in December 2020, reaching 101 days, which points to slower collection of receivables. Subsequently, the period decreased during 2021, improving to 71 days by September 2021. However, in 2022, collection days lengthened again with values ranging from 80 to 88 days, culminating in a significant increase to 104 days in March 2023. This last value indicates a deterioration in collection efficiency compared to earlier periods.
Average Payables Payment Period
The payables payment period demonstrates a relatively steady upward trend from mid-2019 through 2022. Initially at 54 days in June 2019, the period increased to 70 days by March 2020 and generally continued to extend, reaching 91 days in December 2020. In 2021, a decrease followed, with payment days declining to around 69-74 days. Nonetheless, in 2022, the period rose again, moving above 75 days consistently, with a slight decline to 76 days in March 2023. The overall trend indicates a tendency toward longer payment cycles, implying more extended creditor financing.
Cash Conversion Cycle
The cash conversion cycle, which integrates inventory, receivables, and payables dynamics, showcases considerable fluctuation across the analyzed periods. Beginning at 93 days in March 2019, it decreased to 78 days by December 2019, reflecting improved working capital efficiency. Yet, from 2020 onward, the cycle extended notably, reaching peaks of 107 days in both March and December 2020. The next year saw some improvement, with values dropping below 90 days during mid-2021. However, in 2022 and early 2023, the cycle lengthened again, rising above 100 days in March 2023, the highest in the dataset. This pattern indicates a challenging environment for working capital management, with longer durations to convert resources into cash.