Analysis of Short-term (Operating) Activity Ratios
Quarterly Data
Activity ratios measure how efficiently a company performs day-to-day tasks, such us the collection of receivables and management of inventory.
Short-term Activity Ratios (Summary)
Fortinet Inc., short-term (operating) activity ratios (quarterly data)
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).
- Inventory Turnover
- The inventory turnover ratio exhibited a downward trend over the observed period. Starting at 5.27 in early 2019, it declined moderately with fluctuations, reaching a low of 3.76 by March 2023. This suggests an elongation in the time inventory remains on hand before being sold, indicating potential challenges in inventory management or shifts in sales velocity.
- Receivables Turnover
- The receivables turnover ratio showed variability but generally remained within a range close to 4 to 5.5. Initial values oscillated around 4.9 to 5.3, saw some declines and recoveries, and ended around 4.35 in early 2023. This pattern reflects changes in the company's ability to collect receivables, with some periods of slower collection impacting liquidity.
- Payables Turnover
- Payables turnover demonstrated a declining trend from approximately 6.7 in early 2019 to values fluctuating around 4.5 to 5 in recent periods. The reduction indicates a lengthening of the time taken to pay suppliers, which could be a tactic to preserve cash but may affect supplier relationships.
- Working Capital Turnover
- Working capital turnover saw pronounced fluctuations throughout the timeline. It initially hovered around 1.7 to 1.8 in 2019, surged markedly to peak at over 20 in late 2022, before declining again to 4.31 by March 2023. This volatility suggests significant changes in the efficiency of utilizing working capital to generate sales, possibly reflecting operational adjustments or external factors influencing capital management.
- Average Inventory Processing Period
- The average time to process inventory gradually increased from 69 days in early 2019 to a peak of 97 days by early 2023, with some oscillations in between. The lengthening period aligns with the downward trend in inventory turnover, indicating slower inventory movement.
- Average Receivable Collection Period
- This metric experienced variability, starting at 74 days, peaking above 100 days in some quarters, and settling around 84 days in early 2023. The expansions and contractions in collection time emphasize inconsistent cash inflows from customers, with some periods of delayed payments.
- Operating Cycle
- The operating cycle showed a general increasing trend from approximately 143 days in early 2019 to around 181 days by March 2023, with occasional dips. This indicates a lengthier process from inventory acquisition to cash collection, reflecting combined effects of slower inventory turnover and extended receivables collection.
- Average Payables Payment Period
- The payment period to suppliers increased from about 54 days to peaks exceeding 80 days during the period, then slightly decreased to 76 days in early 2023. This extension suggests greater reliance on supplier credit or strategic cash management to defer outflows.
- Cash Conversion Cycle
- The cash conversion cycle fluctuated between 78 and 111 days, starting near 89 days, peaking in late 2022, and remaining above 100 days toward the end. This indicates the duration for converting resource inputs into cash increased over time, signaling potential liquidity pressures or changes in operational efficiency.
Turnover Ratios
Average No. Days
Inventory Turnover
Fortinet Inc., inventory turnover calculation (quarterly data)
| 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 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in thousands) | |||||||||||||||||||||||
| Cost of revenue | 307,800) | 297,300) | 283,000) | 250,800) | 253,800) | 228,300) | 211,200) | 186,900) | 156,600) | 167,000) | 139,200) | 135,100) | 128,700) | 140,500) | 124,100) | 128,300) | 113,000) | ||||||
| Inventory | 302,700) | 264,600) | 215,800) | 195,200) | 184,600) | 175,800) | 177,900) | 149,800) | 149,600) | 139,800) | 134,500) | 126,000) | 105,000) | 117,900) | 99,200) | 85,700) | 88,400) | ||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Inventory turnover1 | 3.76 | 4.10 | 4.71 | 4.84 | 4.77 | 4.45 | 4.06 | 4.34 | 4.00 | 4.08 | 4.04 | 4.19 | 4.97 | 4.29 | 4.98 | 5.62 | 5.27 | ||||||
| Benchmarks | |||||||||||||||||||||||
| Inventory Turnover, Competitors2 | |||||||||||||||||||||||
| Cadence Design Systems Inc. | 3.12 | 2.90 | 3.04 | 3.17 | 2.91 | 2.65 | 3.06 | 3.50 | 4.11 | — | — | — | — | — | — | — | — | ||||||
| International Business Machines Corp. | 17.30 | 17.94 | 15.59 | 16.30 | 14.96 | 15.68 | 15.08 | 17.43 | 18.90 | — | — | — | — | — | — | — | — | ||||||
| Microsoft Corp. | 15.10 | 16.74 | 18.27 | 19.09 | 16.09 | 19.81 | 22.53 | 25.21 | 17.25 | — | — | — | — | — | — | — | — | ||||||
| Synopsys Inc. | 4.94 | 5.02 | 4.62 | 4.45 | 4.28 | 3.76 | 3.53 | 3.65 | 3.51 | 4.13 | 4.71 | 4.49 | 5.09 | — | — | — | — | ||||||
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).
1 Q1 2023 Calculation
Inventory turnover
= (Cost of revenueQ1 2023
+ Cost of revenueQ4 2022
+ Cost of revenueQ3 2022
+ Cost of revenueQ2 2022)
÷ Inventory
= (307,800 + 297,300 + 283,000 + 250,800)
÷ 302,700 = 3.76
2 Click competitor name to see calculations.
The company’s cost of revenue has demonstrated a general upward trend over the observed periods. Starting from approximately $113 million in early 2019, the cost rose steadily, showing more pronounced increases from mid-2020 onward, peaking above $300 million in early 2023. This increase reflects higher expenses related to producing goods or services over time.
Inventory levels have also shown a significant upward trajectory during the same timeframe. Beginning at around $88 million in early 2019, inventory increased consistently, reaching over $300 million by the first quarter of 2023. The growth was particularly notable from 2021 onwards, indicating a continual accumulation of stock.
The inventory turnover ratio presents a decreasing trend overall, suggesting a reduction in the rate at which inventory is sold and replenished. Initially, the ratio was above 5.2 in early 2019, declining gradually with some fluctuations to below 4 by early 2023. This decline implies the inventory is moving more slowly, possibly reflecting changes in sales velocity, stock management efficiency, or increased inventory holding relative to sales.
- Cost of Revenue
- Consistent growth from $113 million to approximately $308 million over four years, highlighting increasing operational costs.
- Inventory
- Steady increase from $88 million to $303 million, indicating accumulation of stock and possibly anticipation of higher sales or production needs.
- Inventory Turnover Ratio
- Decline from 5.27 to 3.76 ratio points over the period, suggesting slower inventory movement and potentially longer holding times or changes in demand dynamics.
In conclusion, the financial indicators emphasize rising cost structures and inventory levels, alongside a slowdown in inventory turnover. These patterns may warrant further investigation into inventory management practices and sales trends to optimize operational efficiency and capital usage.
Receivables Turnover
Fortinet Inc., receivables turnover calculation (quarterly data)
| Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in thousands) | |||||||||||||||||||||||
| Revenue | 1,262,300) | 1,283,000) | 1,149,500) | 1,030,100) | 954,800) | 963,600) | 867,200) | 801,100) | 710,300) | 748,000) | 651,100) | 617,600) | 577,700) | 614,400) | 547,500) | 521,700) | 472,600) | ||||||
| Accounts receivable, net | 1,087,200) | 1,261,700) | 963,200) | 919,500) | 790,400) | 807,700) | 604,900) | 584,600) | 637,300) | 720,000) | 546,600) | 498,700) | 474,700) | 544,300) | 384,100) | 403,100) | 381,000) | ||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Receivables turnover1 | 4.35 | 3.50 | 4.25 | 4.15 | 4.54 | 4.14 | 5.17 | 4.98 | 4.28 | 3.60 | 4.50 | 4.73 | 4.76 | 3.96 | 5.33 | 4.85 | 4.92 | ||||||
| Benchmarks | |||||||||||||||||||||||
| Receivables Turnover, Competitors2 | |||||||||||||||||||||||
| Adobe Inc. | 9.99 | 8.53 | 9.98 | 10.51 | 9.58 | 8.41 | 9.77 | 9.74 | 9.00 | 9.20 | 9.44 | 8.82 | 8.40 | — | — | — | — | ||||||
| AppLovin Corp. | 4.56 | 4.01 | 4.37 | 4.23 | 4.11 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Cadence Design Systems Inc. | 7.54 | 7.32 | 8.78 | 8.38 | 8.72 | 8.85 | 9.09 | 7.41 | 7.21 | — | — | — | — | — | — | — | — | ||||||
| CrowdStrike Holdings Inc. | 4.43 | 3.94 | 4.54 | 4.27 | 4.73 | 3.66 | 4.41 | 4.38 | 3.91 | — | — | — | — | — | — | — | — | ||||||
| Datadog Inc. | 4.89 | 4.19 | 4.39 | 4.47 | 4.33 | 3.83 | 3.92 | 4.06 | 4.35 | — | — | — | — | — | — | — | — | ||||||
| International Business Machines Corp. | 10.52 | 9.25 | 10.95 | 10.17 | 9.79 | 8.49 | 9.23 | 9.57 | 10.72 | — | — | — | — | — | — | — | — | ||||||
| Intuit Inc. | 34.68 | 28.53 | 17.44 | 12.84 | 25.10 | 24.64 | 16.04 | 16.60 | 79.16 | — | — | — | — | — | — | — | — | ||||||
| Microsoft Corp. | 6.49 | 4.48 | 5.90 | 5.52 | 6.44 | 4.42 | 6.08 | 5.61 | 6.44 | — | — | — | — | — | — | — | — | ||||||
| Oracle Corp. | 7.44 | 7.13 | 9.12 | 9.28 | 9.11 | 7.48 | 8.56 | 8.91 | 8.57 | — | — | — | — | — | — | — | — | ||||||
| Palantir Technologies Inc. | 7.81 | 7.38 | 5.33 | 6.56 | 6.42 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Palo Alto Networks Inc. | 4.70 | 2.57 | 4.17 | 5.10 | 5.61 | 3.43 | 5.20 | 5.65 | 5.30 | — | — | — | — | — | — | — | — | ||||||
| Salesforce Inc. | 7.07 | 2.72 | 6.22 | 5.78 | 7.04 | 2.73 | 6.12 | 5.63 | 5.93 | — | — | — | — | — | — | — | — | ||||||
| ServiceNow Inc. | 6.87 | 4.20 | 7.71 | 7.74 | 7.59 | 4.24 | 7.13 | 6.62 | 7.49 | — | — | — | — | — | — | — | — | ||||||
| Synopsys Inc. | 5.00 | 6.38 | 7.25 | 6.58 | 4.34 | 7.40 | 7.06 | 6.51 | 4.84 | 4.72 | 5.50 | 5.36 | 4.22 | — | — | — | — | ||||||
| Workday Inc. | 6.94 | 4.14 | 5.66 | 5.35 | 6.91 | 4.18 | 5.60 | 5.75 | 6.54 | — | — | — | — | — | — | — | — | ||||||
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).
1 Q1 2023 Calculation
Receivables turnover
= (RevenueQ1 2023
+ RevenueQ4 2022
+ RevenueQ3 2022
+ RevenueQ2 2022)
÷ Accounts receivable, net
= (1,262,300 + 1,283,000 + 1,149,500 + 1,030,100)
÷ 1,087,200 = 4.35
2 Click competitor name to see calculations.
The financial data demonstrates several key trends over the quarterly periods reviewed.
- Revenue
- Revenue shows a general upward trend from March 2019 through March 2023. Starting at approximately $472.6 million in March 2019, it increased steadily with minor fluctuations, peaking at $1.283 billion in December 2022. Although there was a slight decrease in the final quarter to around $1.262 billion, the overall growth across the timeframe indicates strong sales performance and expansion.
- Accounts Receivable, Net
- Accounts receivable exhibit a rising pattern with some notable volatility. Beginning near $381 million in March 2019, the figure grew significantly, reaching $1.261 billion in December 2022 before a moderate decline to $1.087 billion in March 2023. Several quarters show steep increases, such as between September and December 2019 and again in late 2021 and 2022, suggesting more credit sales or longer collection periods in those intervals.
- Receivables Turnover Ratio
- The receivables turnover ratio fluctuates between roughly 3.5 and 5.3 times per year during the period. Initially near 4.92 in March 2019, it experienced periodic drops, particularly in December of 2019 and 2020, indicating slower collection cycles during those quarters. The ratio peaks again in some quarters like September 2019 and September 2021, signaling more efficient collection. Toward the end of the period, the ratio settles around 4.35 but shows a notable decline in December 2022 at 3.5, implying a slower rate of converting receivables into cash despite higher revenue and receivable balances.
Overall, the data indicates robust revenue growth accompanied by increasing accounts receivable, which may require monitoring due to periodic drops in receivables turnover efficiency. The fluctuations in turnover ratio suggest variability in credit management or customer payment patterns over time. Maintaining or improving turnover in the context of rising sales might be critical for sustaining healthy cash flow.
Payables Turnover
Fortinet Inc., payables turnover calculation (quarterly data)
| Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in thousands) | |||||||||||||||||||||||
| Cost of revenue | 307,800) | 297,300) | 283,000) | 250,800) | 253,800) | 228,300) | 211,200) | 186,900) | 156,600) | 167,000) | 139,200) | 135,100) | 128,700) | 140,500) | 124,100) | 128,300) | 113,000) | ||||||
| Accounts payable | 238,400) | 243,400) | 215,100) | 193,100) | 174,700) | 148,400) | 142,300) | 132,000) | 129,500) | 141,600) | 95,900) | 107,200) | 87,800) | 96,400) | 85,900) | 72,400) | 69,200) | ||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Payables turnover1 | 4.78 | 4.46 | 4.72 | 4.89 | 5.04 | 5.28 | 5.07 | 4.92 | 4.62 | 4.03 | 5.67 | 4.93 | 5.94 | 5.25 | 5.75 | 6.65 | 6.74 | ||||||
| Benchmarks | |||||||||||||||||||||||
| Payables Turnover, Competitors2 | |||||||||||||||||||||||
| Accenture PLC | 17.54 | 16.37 | 16.93 | 17.22 | 16.45 | 15.03 | 16.92 | 17.94 | 20.16 | — | — | — | — | — | — | — | — | ||||||
| Adobe Inc. | 7.21 | 5.71 | 6.66 | 5.53 | 6.54 | 5.98 | 5.40 | 5.60 | 6.76 | 5.63 | 7.62 | 6.00 | 6.52 | — | — | — | — | ||||||
| AppLovin Corp. | 4.37 | 4.60 | 4.40 | 3.90 | 2.83 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| CrowdStrike Holdings Inc. | 39.15 | 8.05 | 47.07 | 15.13 | 75.30 | 19.03 | 27.52 | 17.99 | 24.39 | — | — | — | — | — | — | — | — | ||||||
| Datadog Inc. | 8.95 | 14.77 | 11.48 | 6.02 | 14.07 | 9.27 | 6.00 | 6.10 | 12.46 | — | — | — | — | — | — | — | — | ||||||
| International Business Machines Corp. | 7.44 | 6.87 | 7.35 | 7.40 | 7.69 | 6.54 | 6.71 | 7.47 | 8.35 | — | — | — | — | — | — | — | — | ||||||
| Intuit Inc. | 3.98 | 3.26 | 2.52 | 2.31 | 3.47 | 2.70 | 2.56 | 2.82 | 5.25 | — | — | — | — | — | — | — | — | ||||||
| Microsoft Corp. | 3.88 | 3.30 | 3.74 | 3.76 | 3.70 | 3.44 | 3.77 | 3.80 | 3.73 | — | — | — | — | — | — | — | — | ||||||
| Oracle Corp. | 6.72 | 6.74 | 7.65 | 8.03 | 10.79 | 10.54 | 9.49 | 10.71 | 14.72 | — | — | — | — | — | — | — | — | ||||||
| Palantir Technologies Inc. | 93.11 | 9.12 | 6.58 | 6.53 | 13.10 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Palo Alto Networks Inc. | 14.30 | 13.43 | 14.68 | 12.25 | 14.46 | 22.41 | 16.80 | 25.37 | 21.85 | — | — | — | — | — | — | — | — | ||||||
| ServiceNow Inc. | 7.20 | 5.74 | 7.86 | 5.60 | 8.57 | 15.20 | 19.64 | 11.82 | 9.75 | — | — | — | — | — | — | — | — | ||||||
| Workday Inc. | 12.14 | 25.74 | 28.20 | 24.24 | 25.48 | 15.85 | 21.29 | 19.83 | 31.83 | — | — | — | — | — | — | — | — | ||||||
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).
1 Q1 2023 Calculation
Payables turnover
= (Cost of revenueQ1 2023
+ Cost of revenueQ4 2022
+ Cost of revenueQ3 2022
+ Cost of revenueQ2 2022)
÷ Accounts payable
= (307,800 + 297,300 + 283,000 + 250,800)
÷ 238,400 = 4.78
2 Click competitor name to see calculations.
- Cost of Revenue
- The cost of revenue has exhibited a consistent upward trend over the examined periods. Starting at $113,000 thousand in March 2019, it increased gradually to $140,500 thousand by December 2019. Despite a minor dip in the first quarter of 2020, the overall trajectory remained upward through to March 2023, reaching $307,800 thousand. This growth reflects an expansion in the scale of operations or rising expenses associated with revenue generation.
- Accounts Payable
- Accounts payable also increased significantly during the timeframe. From $69,200 thousand in March 2019, it rose steadily with some fluctuations to a peak of $243,400 thousand in December 2022. By March 2023, the balance slightly declined to $238,400 thousand. The substantial increase indicates extended credit terms or higher procurement levels, aligning with the rising cost of revenue.
- Payables Turnover Ratio
- The payables turnover ratio showed a general declining trend from 6.74 in March 2019 to values fluctuating around 4.5 to 5.3 in recent quarters. Initially, the ratio fell notably from early 2019 through 2020, reflecting slower payment cycles or increasing accounts payable relative to cost of revenue. Although some recovery is observed in certain quarters, the recent ratios remain lower than the earliest period, suggesting a lengthening of the payment period to suppliers or increased reliance on payables financing.
- Overall Analysis
- The rising cost of revenue accompanied by increased accounts payable indicates expanding business operations with higher expense volumes. The declining payables turnover ratio supports the interpretation of extended payment terms or greater usage of credit from suppliers over time. These trends combined suggest the company is managing higher operational costs possibly through supplier credit, which may have impacts on liquidity and working capital management. Continuous monitoring of these metrics is advised to maintain financial health and supplier relationships.
Working Capital Turnover
Fortinet Inc., working capital turnover calculation (quarterly data)
| Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in thousands) | |||||||||||||||||||||||
| Current assets | 4,358,700) | 3,810,400) | 2,982,200) | 2,952,900) | 3,208,300) | 3,600,600) | 3,963,500) | 3,908,200) | 3,781,200) | 2,740,400) | 2,384,600) | 2,208,700) | 2,035,300) | 2,769,000) | 2,466,200) | 2,360,700) | 2,313,300) | ||||||
| Less: Current liabilities | 3,261,800) | 3,078,400) | 2,779,600) | 2,634,900) | 2,510,500) | 2,318,100) | 2,198,000) | 1,998,500) | 1,879,700) | 1,829,500) | 1,645,600) | 1,611,900) | 1,543,000) | 1,473,600) | 1,341,900) | 1,293,700) | 1,254,300) | ||||||
| Working capital | 1,096,900) | 732,000) | 202,600) | 318,000) | 697,800) | 1,282,500) | 1,765,500) | 1,909,700) | 1,901,500) | 910,900) | 739,000) | 596,800) | 492,300) | 1,295,400) | 1,124,300) | 1,067,000) | 1,059,000) | ||||||
| Revenue | 1,262,300) | 1,283,000) | 1,149,500) | 1,030,100) | 954,800) | 963,600) | 867,200) | 801,100) | 710,300) | 748,000) | 651,100) | 617,600) | 577,700) | 614,400) | 547,500) | 521,700) | 472,600) | ||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Working capital turnover1 | 4.31 | 6.03 | 20.23 | 12.00 | 5.14 | 2.61 | 1.77 | 1.52 | 1.43 | 2.85 | 3.33 | 3.95 | 4.59 | 1.66 | 1.82 | 1.83 | 1.77 | ||||||
| Benchmarks | |||||||||||||||||||||||
| Working Capital Turnover, Competitors2 | |||||||||||||||||||||||
| Accenture PLC | 14.81 | 15.07 | 13.41 | 15.55 | 15.85 | 12.77 | 7.71 | 8.35 | 7.70 | — | — | — | — | — | — | — | — | ||||||
| Adobe Inc. | 19.89 | 20.28 | 16.36 | 31.92 | 57.86 | 9.09 | 6.22 | 7.44 | 8.67 | 4.89 | 5.51 | 8.11 | 9.50 | — | — | — | — | ||||||
| AppLovin Corp. | 2.03 | 2.07 | 2.27 | 2.49 | 1.86 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Cadence Design Systems Inc. | 7.12 | 9.92 | 8.31 | 5.34 | 4.07 | 4.01 | 4.68 | 5.45 | 5.03 | — | — | — | — | — | — | — | — | ||||||
| CrowdStrike Holdings Inc. | 1.32 | 1.25 | 1.15 | 1.02 | 0.95 | 0.61 | 1.19 | 0.92 | 0.81 | — | — | — | — | — | — | — | — | ||||||
| Datadog Inc. | 1.06 | 1.06 | 1.02 | 0.95 | 0.85 | 0.77 | 0.68 | 0.61 | 0.47 | — | — | — | — | — | — | — | — | ||||||
| International Business Machines Corp. | 12.14 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Intuit Inc. | 10.83 | 8.98 | 5.68 | 21.87 | 4.39 | 3.85 | 3.40 | 5.45 | 1.74 | — | — | — | — | — | — | — | — | ||||||
| Microsoft Corp. | 2.77 | 2.66 | 2.52 | 1.91 | 1.88 | 1.76 | 1.71 | 1.44 | 1.37 | — | — | — | — | — | — | — | — | ||||||
| Oracle Corp. | — | 3.50 | 3.86 | 3.39 | 1.70 | 1.29 | 1.69 | 1.58 | 1.26 | — | — | — | — | — | — | — | — | ||||||
| Palantir Technologies Inc. | 0.75 | 0.78 | 0.81 | 0.78 | 0.73 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Palo Alto Networks Inc. | — | — | — | — | — | — | 3.52 | — | 2.15 | — | — | — | — | — | — | — | — | ||||||
| Salesforce Inc. | 54.57 | 24.95 | 27.10 | — | 4.36 | 5.11 | 7.48 | 10.29 | 9.75 | — | — | — | — | — | — | — | — | ||||||
| ServiceNow Inc. | 7.83 | 11.16 | 6.63 | 11.21 | 10.61 | 21.76 | 11.15 | 16.31 | 5.62 | — | — | — | — | — | — | — | — | ||||||
| Synopsys Inc. | 17.05 | 21.34 | 14.02 | 7.78 | 9.47 | 10.65 | 9.50 | 9.18 | 16.88 | 9.00 | 27.06 | — | — | — | — | — | — | ||||||
| Workday Inc. | 2.03 | 35.15 | 11.69 | 24.99 | — | 8.31 | 12.50 | 3.44 | 5.62 | — | — | — | — | — | — | — | — | ||||||
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).
1 Q1 2023 Calculation
Working capital turnover
= (RevenueQ1 2023
+ RevenueQ4 2022
+ RevenueQ3 2022
+ RevenueQ2 2022)
÷ Working capital
= (1,262,300 + 1,283,000 + 1,149,500 + 1,030,100)
÷ 1,096,900 = 4.31
2 Click competitor name to see calculations.
The financial analysis over the observed quarters reveals fluctuating patterns across working capital, revenue, and working capital turnover ratios.
- Working Capital
- The working capital demonstrates significant variability throughout the periods. Initially, there is a steady increase from approximately 1,059,000 to 1,295,400 thousand US dollars between March 2019 and December 2019. Subsequently, a sharp decline occurs in the first quarter of 2020, dropping to around 492,300 thousand US dollars. This downturn is followed by a recovery phase in the latter half of 2020, reaching 910,900 thousand US dollars by December. Entering 2021, working capital increases substantially, peaking at 1,909,700 thousand US dollars mid-year, after which it declines steadily through the end of 2022 to a low of approximately 202,600 thousand US dollars. The first quarter of 2023 shows a partial rebound to 1,096,900 thousand US dollars.
- Revenue
- Revenue trends indicate a generally upward trajectory over the entire period. From a baseline of 472,600 thousand US dollars in March 2019, revenue gradually climbs to 614,400 thousand by December 2019. Despite a minor dip in early 2020 (577,700 thousand US dollars), the overall trend remains positive, with revenue rising steadily to over 1,283,000 thousand US dollars by December 2022. A slight decrease is observed in the first quarter of 2023, settling at approximately 1,262,300 thousand US dollars, marking a near plateau.
- Working Capital Turnover
- The working capital turnover ratio presents considerable volatility, reflecting the interplay between revenue and working capital. Initially, the ratio maintains a narrow range around 1.66 to 1.83 from March to December 2019. With the sharp decrease in working capital during early 2020 while revenue holds steady, this ratio spikes dramatically, reaching a peak of 4.59 in March 2020 and further increasing to 3.95 and 3.33 in the following quarters, before declining to 2.85 by December 2020. The ratio drops again in 2021 to lows near 1.43, aligning with the increase in working capital during that year. From March 2022 onward, the turnover ratio surges significantly, peaking at 20.23 in September 2022, likely driven by a major contraction in working capital amidst rising revenue. This surge is followed by a decrease back toward 4.31 by the first quarter of 2023.
In summary, the data displays a pattern of revenue growth with intermittent periods of contraction, while working capital experiences pronounced fluctuations, occasionally diverging sharply from revenue trends. The working capital turnover ratio, sensitive to these variations, reveals periods where capital efficiency markedly improves, especially during times of working capital compression, and periods of reduced efficiency when working capital is elevated. This behavior suggests dynamic working capital management relative to revenue generation across the quarters analyzed.
Average Inventory Processing Period
Fortinet Inc., average inventory processing period calculation (quarterly data)
| 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 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | |||||||||||||||||||||||
| Inventory turnover | 3.76 | 4.10 | 4.71 | 4.84 | 4.77 | 4.45 | 4.06 | 4.34 | 4.00 | 4.08 | 4.04 | 4.19 | 4.97 | 4.29 | 4.98 | 5.62 | 5.27 | ||||||
| Short-term Activity Ratio (no. days) | |||||||||||||||||||||||
| Average inventory processing period1 | 97 | 89 | 78 | 75 | 77 | 82 | 90 | 84 | 91 | 90 | 90 | 87 | 73 | 85 | 73 | 65 | 69 | ||||||
| Benchmarks (no. days) | |||||||||||||||||||||||
| Average Inventory Processing Period, Competitors2 | |||||||||||||||||||||||
| Cadence Design Systems Inc. | 117 | 126 | 120 | 115 | 125 | 138 | 119 | 104 | 89 | — | — | — | — | — | — | — | — | ||||||
| International Business Machines Corp. | 21 | 20 | 23 | 22 | 24 | 23 | 24 | 21 | 19 | — | — | — | — | — | — | — | — | ||||||
| Microsoft Corp. | 24 | 22 | 20 | 19 | 23 | 18 | 16 | 14 | 21 | — | — | — | — | — | — | — | — | ||||||
| Synopsys Inc. | 74 | 73 | 79 | 82 | 85 | 97 | 103 | 100 | 104 | 88 | 77 | 81 | 72 | — | — | — | — | ||||||
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).
1 Q1 2023 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ 3.76 = 97
2 Click competitor name to see calculations.
- Inventory Turnover
- The inventory turnover ratio exhibits a declining trend over the analyzed period. Beginning at 5.27 in March 2019, the ratio generally decreases, with minor fluctuations, reaching a low of 3.76 by March 2023. This indicates that inventory is being sold or used less frequently over time, suggesting slower inventory movement or potential buildup of stock.
- Average Inventory Processing Period
- The average inventory processing period, measured in days, shows an opposite pattern to the inventory turnover ratio. Starting at 69 days in March 2019, it tends to increase over the quarters, peaking at 97 days by March 2023. This rise means the company is taking more time to process its inventory, which could be a sign of slower sales or operational inefficiencies.
- Relationship Between Metrics
- There is a clear inverse relationship between inventory turnover and the average inventory processing period. As the turnover ratio decreases, the processing period increases, consistent with standard inventory management principles. This reciprocal movement suggests a gradual slowdown in inventory management effectiveness throughout the period.
- Quarterly Fluctuations
- Although both metrics reveal long-term trends, short-term fluctuations are observable. For example, inventory turnover shows slight recoveries in some quarters, but these are not sustained. Similarly, the days inventory remains relatively variable but exhibits an overall upward trajectory.
- Overall Implications
- The trend toward lower inventory turnover and longer processing periods may suggest challenges in sales velocity or stock management. The increasing inventory held for longer durations may impact liquidity and storage costs. This pattern warrants further investigation to identify underlying causes and opportunities for improvement in inventory practices.
Average Receivable Collection Period
Fortinet Inc., average receivable collection period calculation (quarterly data)
| 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 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | |||||||||||||||||||||||
| Receivables turnover | 4.35 | 3.50 | 4.25 | 4.15 | 4.54 | 4.14 | 5.17 | 4.98 | 4.28 | 3.60 | 4.50 | 4.73 | 4.76 | 3.96 | 5.33 | 4.85 | 4.92 | ||||||
| Short-term Activity Ratio (no. days) | |||||||||||||||||||||||
| Average receivable collection period1 | 84 | 104 | 86 | 88 | 80 | 88 | 71 | 73 | 85 | 101 | 81 | 77 | 77 | 92 | 68 | 75 | 74 | ||||||
| Benchmarks (no. days) | |||||||||||||||||||||||
| Average Receivable Collection Period, Competitors2 | |||||||||||||||||||||||
| Adobe Inc. | 37 | 43 | 37 | 35 | 38 | 43 | 37 | 37 | 41 | 40 | 39 | 41 | 43 | — | — | — | — | ||||||
| AppLovin Corp. | 80 | 91 | 84 | 86 | 89 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Cadence Design Systems Inc. | 48 | 50 | 42 | 44 | 42 | 41 | 40 | 49 | 51 | — | — | — | — | — | — | — | — | ||||||
| CrowdStrike Holdings Inc. | 82 | 93 | 80 | 85 | 77 | 100 | 83 | 83 | 93 | — | — | — | — | — | — | — | — | ||||||
| Datadog Inc. | 75 | 87 | 83 | 82 | 84 | 95 | 93 | 90 | 84 | — | — | — | — | — | — | — | — | ||||||
| International Business Machines Corp. | 35 | 39 | 33 | 36 | 37 | 43 | 40 | 38 | 34 | — | — | — | — | — | — | — | — | ||||||
| Intuit Inc. | 11 | 13 | 21 | 28 | 15 | 15 | 23 | 22 | 5 | — | — | — | — | — | — | — | — | ||||||
| Microsoft Corp. | 56 | 81 | 62 | 66 | 57 | 83 | 60 | 65 | 57 | — | — | — | — | — | — | — | — | ||||||
| Oracle Corp. | 49 | 51 | 40 | 39 | 40 | 49 | 43 | 41 | 43 | — | — | — | — | — | — | — | — | ||||||
| Palantir Technologies Inc. | 47 | 49 | 68 | 56 | 57 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Palo Alto Networks Inc. | 78 | 142 | 88 | 72 | 65 | 106 | 70 | 65 | 69 | — | — | — | — | — | — | — | — | ||||||
| Salesforce Inc. | 52 | 134 | 59 | 63 | 52 | 134 | 60 | 65 | 62 | — | — | — | — | — | — | — | — | ||||||
| ServiceNow Inc. | 53 | 87 | 47 | 47 | 48 | 86 | 51 | 55 | 49 | — | — | — | — | — | — | — | — | ||||||
| Synopsys Inc. | 73 | 57 | 50 | 55 | 84 | 49 | 52 | 56 | 75 | 77 | 66 | 68 | 86 | — | — | — | — | ||||||
| Workday Inc. | 53 | 88 | 65 | 68 | 53 | 87 | 65 | 63 | 56 | — | — | — | — | — | — | — | — | ||||||
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).
1 Q1 2023 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ 4.35 = 84
2 Click competitor name to see calculations.
The analysis of the receivables turnover ratio reveals fluctuating efficiency in managing and collecting receivables over the observed periods. Initially, the ratio exhibits moderate stability around values close to 5, with slight variations ranging from 4.85 to 5.33 in early 2019, indicating reasonably consistent collection efficiency. However, a notable decline occurs in December 2019 and December 2020, where the turnover decreases to 3.96 and 3.6 respectively, signaling slower collection of receivables and potentially increased credit risk or extended payment terms during these quarters.
The average receivable collection period complements these observations, showing an inverse trend to the turnover ratio. The number of days gradually increases towards the end of 2019 and late 2020, peaking at 92 and 101 days, which points to a lengthening collection cycle and possible challenges in receivables management. This elongation in days outstanding corresponds to the dips seen in the turnover ratio at the same points in time.
In 2021, an improvement is observed with the receivables turnover climbing back to higher values near or above 5 in some quarters (e.g., 5.17 in September), and the collection period shortening to as low as 71 days, reflecting enhanced effectiveness in receivable collections. However, this positive trend is not sustained throughout 2022 and into early 2023, with turnover ratios declining again to lows around 3.5 to 4.25 and collection periods extending to between 80 and 104 days. This indicates recurring difficulties in collecting outstanding payments promptly and suggests a possible shift in credit policies, customer payment behavior, or market conditions impacting receivables turnover negatively.
- Receivables Turnover Ratio
- Shows variability with notable downturns in December 2019 and 2020, marginal recovery in 2021, followed by decline in 2022 and early 2023, illustrating inconsistent efficiency in receivables management.
- Average Receivable Collection Period
- Mirrors the turnover trend inversely, with longer collection periods during times of lower turnover ratios, peaking over 100 days at certain points, indicating delays in cash inflow from receivables.
The overall pattern suggests that the company faces periodic challenges in maintaining steady receivables collection performance. These fluctuations may reflect changes in credit terms, customer payment behavior, or macroeconomic factors influencing customer liquidity and payment cycles. Close monitoring and potentially enhanced credit risk management strategies could be advisable to stabilize and improve collections efficiency.
Operating Cycle
Fortinet Inc., operating cycle calculation (quarterly data)
No. days
| 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 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | |||||||||||||||||||||||
| Average inventory processing period | 97 | 89 | 78 | 75 | 77 | 82 | 90 | 84 | 91 | 90 | 90 | 87 | 73 | 85 | 73 | 65 | 69 | ||||||
| Average receivable collection period | 84 | 104 | 86 | 88 | 80 | 88 | 71 | 73 | 85 | 101 | 81 | 77 | 77 | 92 | 68 | 75 | 74 | ||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Operating cycle1 | 181 | 193 | 164 | 163 | 157 | 170 | 161 | 157 | 176 | 191 | 171 | 164 | 150 | 177 | 141 | 140 | 143 | ||||||
| Benchmarks | |||||||||||||||||||||||
| Operating Cycle, Competitors2 | |||||||||||||||||||||||
| Cadence Design Systems Inc. | 165 | 176 | 162 | 159 | 167 | 179 | 159 | 153 | 140 | — | — | — | — | — | — | — | — | ||||||
| International Business Machines Corp. | 56 | 59 | 56 | 58 | 61 | 66 | 64 | 59 | 53 | — | — | — | — | — | — | — | — | ||||||
| Microsoft Corp. | 80 | 103 | 82 | 85 | 80 | 101 | 76 | 79 | 78 | — | — | — | — | — | — | — | — | ||||||
| Synopsys Inc. | 147 | 130 | 129 | 137 | 169 | 146 | 155 | 156 | 179 | 165 | 143 | 149 | 158 | — | — | — | — | ||||||
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).
1 Q1 2023 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= 97 + 84 = 181
2 Click competitor name to see calculations.
- Average Inventory Processing Period
- The average inventory processing period exhibits notable fluctuations over the analyzed timeframe. Starting at 69 days at the end of March 2019, it experienced some variability, with a peak of 90 days in both September and December 2020. Following this, the period slightly decreased but remained relatively high compared to the initial periods, reaching 97 days by the end of March 2023. This indicates a general trend toward longer inventory holding times, particularly in recent quarters.
- Average Receivable Collection Period
- The average receivable collection period shows irregular changes across the quarters. After an initial moderate range between 68 and 75 days in 2019, a pronounced increase is observed towards the end of 2020, reaching 101 days in December 2020. Subsequently, this period oscillated between 71 and 104 days, with a slight downward adjustment by March 2023 to 84 days. These variations suggest challenges in maintaining consistent receivable turnover, with some periods of slower collection.
- Operating Cycle
- The operating cycle illustrates the combined effect of inventory processing and receivables collection periods. Beginning at 143 days in March 2019, it showed an upward trend, reaching peaks of 191 days in December 2020 and 193 days in December 2022. Although some intermediate periods indicated slight declines, the longer-term trend points toward an extension of the operating cycle duration. This extension may reflect increased time tied up in working capital components, potentially impacting cash flow efficiency.
- Summary
- Overall, the data reveals a tendency for the company to experience lengthening cycles in inventory processing and receivables collection over the analyzed period. This has contributed to an increase in the total operating cycle duration. Such trends may highlight operational or market-related influences affecting inventory turnover and customer payment behaviors. Close monitoring and potential management actions could be warranted to optimize working capital management and enhance operational efficiency.
Average Payables Payment Period
Fortinet Inc., average payables payment period calculation (quarterly data)
| 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 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | |||||||||||||||||||||||
| Payables turnover | 4.78 | 4.46 | 4.72 | 4.89 | 5.04 | 5.28 | 5.07 | 4.92 | 4.62 | 4.03 | 5.67 | 4.93 | 5.94 | 5.25 | 5.75 | 6.65 | 6.74 | ||||||
| Short-term Activity Ratio (no. days) | |||||||||||||||||||||||
| Average payables payment period1 | 76 | 82 | 77 | 75 | 72 | 69 | 72 | 74 | 79 | 91 | 64 | 74 | 61 | 70 | 63 | 55 | 54 | ||||||
| Benchmarks (no. days) | |||||||||||||||||||||||
| Average Payables Payment Period, Competitors2 | |||||||||||||||||||||||
| Accenture PLC | 21 | 22 | 22 | 21 | 22 | 24 | 22 | 20 | 18 | — | — | — | — | — | — | — | — | ||||||
| Adobe Inc. | 51 | 64 | 55 | 66 | 56 | 61 | 68 | 65 | 54 | 65 | 48 | 61 | 56 | — | — | — | — | ||||||
| AppLovin Corp. | 84 | 79 | 83 | 94 | 129 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| CrowdStrike Holdings Inc. | 9 | 45 | 8 | 24 | 5 | 19 | 13 | 20 | 15 | — | — | — | — | — | — | — | — | ||||||
| Datadog Inc. | 41 | 25 | 32 | 61 | 26 | 39 | 61 | 60 | 29 | — | — | — | — | — | — | — | — | ||||||
| International Business Machines Corp. | 49 | 53 | 50 | 49 | 47 | 56 | 54 | 49 | 44 | — | — | — | — | — | — | — | — | ||||||
| Intuit Inc. | 92 | 112 | 145 | 158 | 105 | 135 | 142 | 129 | 70 | — | — | — | — | — | — | — | — | ||||||
| Microsoft Corp. | 94 | 111 | 98 | 97 | 99 | 106 | 97 | 96 | 98 | — | — | — | — | — | — | — | — | ||||||
| Oracle Corp. | 54 | 54 | 48 | 45 | 34 | 35 | 38 | 34 | 25 | — | — | — | — | — | — | — | — | ||||||
| Palantir Technologies Inc. | 4 | 40 | 55 | 56 | 28 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Palo Alto Networks Inc. | 26 | 27 | 25 | 30 | 25 | 16 | 22 | 14 | 17 | — | — | — | — | — | — | — | — | ||||||
| ServiceNow Inc. | 51 | 64 | 46 | 65 | 43 | 24 | 19 | 31 | 37 | — | — | — | — | — | — | — | — | ||||||
| Workday Inc. | 30 | 14 | 13 | 15 | 14 | 23 | 17 | 18 | 11 | — | — | — | — | — | — | — | — | ||||||
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).
1 Q1 2023 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ 4.78 = 76
2 Click competitor name to see calculations.
- Payables Turnover
- The payables turnover ratio exhibits a clear declining trend over the period analyzed. Starting from a relatively high ratio of 6.74 in March 2019, the figure generally decreases with some fluctuations, reaching a low point of 4.03 by December 2020. Following this, a modest recovery is observed, with the ratio rising slightly to a range between 4.46 and 5.28 in 2021 and 2022. However, the values remain notably below the initial levels seen in early 2019, signaling a reduction in the rate at which the company settles its payables over time.
- Average Payables Payment Period
- The average payables payment period, which measures the number of days taken to pay suppliers, confirms the trend identified in the turnover ratio. Initially at 54 days in March 2019, the payment period gradually increases, peaking at 91 days in December 2020. This indicates a lengthening in the time the company takes to fulfill its payable obligations. After the peak, the payment period fluctuates between the high 60s and low 80s, ending at 76 days by March 2023. This sustained increase implies an extension of the company's payment cycle compared to the earlier periods.
- Overall Analysis
- The inverse relationship observed between the payables turnover and the average payables payment period aligns with typical financial behavior: as the payment period lengthens, the turnover ratio decreases. The data suggest that the company has, over the years, extended the duration for settling its accounts payable. This strategy might be an effort to optimize cash flow or respond to changes in supplier terms. However, the persistent increase in payment days could also carry implications for supplier relationships and credit terms. The partial recovery in the payables turnover ratio post-2020 indicates some adjustments in payment practices, though the overall pattern points to slower payment trends compared to the start of the period.
Cash Conversion Cycle
Fortinet Inc., cash conversion cycle calculation (quarterly data)
No. days
| 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 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | |||||||||||||||||||||||
| Average inventory processing period | 97 | 89 | 78 | 75 | 77 | 82 | 90 | 84 | 91 | 90 | 90 | 87 | 73 | 85 | 73 | 65 | 69 | ||||||
| Average receivable collection period | 84 | 104 | 86 | 88 | 80 | 88 | 71 | 73 | 85 | 101 | 81 | 77 | 77 | 92 | 68 | 75 | 74 | ||||||
| Average payables payment period | 76 | 82 | 77 | 75 | 72 | 69 | 72 | 74 | 79 | 91 | 64 | 74 | 61 | 70 | 63 | 55 | 54 | ||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Cash conversion cycle1 | 105 | 111 | 87 | 88 | 85 | 101 | 89 | 83 | 97 | 100 | 107 | 90 | 89 | 107 | 78 | 85 | 89 | ||||||
| Benchmarks | |||||||||||||||||||||||
| Cash Conversion Cycle, Competitors2 | |||||||||||||||||||||||
| International Business Machines Corp. | 7 | 6 | 6 | 9 | 14 | 10 | 10 | 10 | 9 | — | — | — | — | — | — | — | — | ||||||
| Microsoft Corp. | -14 | -8 | -16 | -12 | -19 | -5 | -21 | -17 | -20 | — | — | — | — | — | — | — | — | ||||||
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).
1 Q1 2023 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= 97 + 84 – 76 = 105
2 Click competitor name to see calculations.
- Average Inventory Processing Period
- The average inventory processing period exhibits variability over the observed quarters. Starting at 69 days in March 2019, there is a general upward trend with fluctuations, reaching peaks around 90 days in late 2020 and again in early 2023. The highest value is observed at 97 days in March 2023, indicating a lengthening duration of inventory processing over the period.
- Average Receivable Collection Period
- The average receivable collection period fluctuates throughout the timeframe. Initial values around 74 to 75 days in early 2019 decreased slightly before rising sharply to 101 days in December 2020. Subsequently, it shows oscillations, peaking again at 104 days in December 2022, then declining to 84 days in March 2023. This pattern suggests variability in the speed of receivables collection, with periods of slower collections noted.
- Average Payables Payment Period
- The average payables payment period generally increases over the period analyzed. Beginning at 54 days in March 2019, it escalates with intermittent drops, reaching 91 days in December 2020. Following this peak, the period fluctuates in the 70 to 80-day range, ending at 76 days in March 2023. This growth indicates a tendency towards extended payment durations to suppliers in certain periods.
- Cash Conversion Cycle
- The cash conversion cycle shows considerable variation and generally longer cycles in the latter periods. It starts at 89 days in March 2019, experiences a peak of 107 days in December 2019, followed by another stretch of values around 100 days. The cycle decreases somewhat in mid-2021 before increasing again to reach 111 days in December 2022, ultimately marginally reducing to 105 days in March 2023. This indicates an overall increase in the length of time to convert resource inputs into cash flows.