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.
Paying user area
Try for free
Northrop Grumman Corp. pages available for free this week:
- Balance Sheet: Assets
- Balance Sheet: Liabilities and Stockholders’ Equity
- Common-Size Income Statement
- Common-Size Balance Sheet: Liabilities and Stockholders’ Equity
- Analysis of Liquidity Ratios
- Dividend Discount Model (DDM)
- Present Value of Free Cash Flow to Equity (FCFE)
- Selected Financial Data since 2005
- Return on Equity (ROE) since 2005
- Aggregate Accruals
The data is hidden behind: . Unhide it.
Get full access to the entire website from $10.42/mo, or
get 1-month access to Northrop Grumman Corp. for $22.49.
This is a one-time payment. There is no automatic renewal.
We accept:
Short-term Activity Ratios (Summary)
Northrop Grumman Corp., 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).
The analysis of the quarterly financial ratios and operating cycle metrics reveals several noteworthy trends over the period under review. These metrics provide insight into the efficiency of the company in managing its inventory, receivables, payables, and overall working capital.
- Inventory Turnover
- The inventory turnover ratio exhibited relative stability with fluctuations around the low 30s, peaking at 38.63 in December 2020 before gradually declining to 26.48 by March 2023. This suggests that the company’s efficiency in managing inventory experienced some volatility, with a notable peak in late 2020 followed by a gradual reduction in turnover speed, indicating potentially slower inventory movement more recently.
- Receivables Turnover
- Receivables turnover showed considerable variability, with low points in mid-2022 (14.64) and early 2019 (14.57) and high points in late 2019 and late 2020 (above 24). This pattern indicates fluctuating efficiency in collecting receivables, with some quarters reflecting faster collections and others slower, which could indicate changes in credit policy or market conditions impacting customer payments.
- Payables Turnover
- Payables turnover remained relatively steady, mostly ranging between 11 and 16 times per year, with the highest figure in December 2020 (16.24). The stability indicates consistent management of payment terms to suppliers, with no radical shifts in payment speed throughout the period.
- Working Capital Turnover
- This ratio showed notable volatility, starting high at 19.45 in early 2019, dropping to lows near 6.38 in late 2020, then sharply increasing to 40.62 in late 2022, before falling back to 15.95 by March 2023. This suggests significant fluctuations in how efficiently the company utilized its working capital to generate revenues, possibly reflecting varying operational circumstances, investment levels, or changes in current assets and liabilities management.
- Average Inventory Processing Period
- The average inventory processing period remained relatively stable around 11 days for most of the timeframe but increased slightly to 13–14 days towards the end of the period. This aligns with the declining inventory turnover ratio, reinforcing the conclusion of slower inventory movement in recent quarters.
- Average Receivable Collection Period
- The collection period varied appreciably, ranging from lows of about 14–15 days in late 2019 and 2020 to highs near 25 days in early 2022. These fluctuations mirror the behavior seen in receivables turnover and indicate periods of slower and faster collection cycles, potentially linked to customer payment behavior or credit management adjustments.
- Operating Cycle
- The operating cycle, measuring the period from inventory acquisition to cash collection, ranged from a low of 24 days in December 2020 to a high of 37 days in mid-2022. The fluctuations reflect the combined effects of inventory processing and receivables collection periods and suggest occasional improvements in overall operating efficiency but a tendency towards longer cycles in more recent periods.
- Average Payables Payment Period
- The average period for paying suppliers remained fairly consistent around 27–29 days, with slight increases towards the end of the period (up to 32 days). This consistency indicates stable supplier payment practices, with a modest lengthening of payment terms in recent quarters.
- Cash Conversion Cycle
- The cash conversion cycle showed significant variability, oscillating between negative values (e.g., -6 days in December 2019 and -5 days in December 2022) and positive values reaching 9 days in mid-2022. Negative cycles are indicative of a favorable situation where payables periods exceed the sum of receivables and inventory days, reflecting strong liquidity management. The oscillation reveals shifts in working capital dynamics affecting cash flow timing over the period.
In summary, the company displayed generally consistent management of payables, moderate variability in receivables and inventory efficiency, and significant volatility in working capital turnover and cash conversion cycles. The most recent quarters indicate some slowing in inventory turnover and an increase in inventory processing days, alongside fluctuating receivables collection efficiency. Meanwhile, working capital turnover and cash conversion cycles show marked instability, suggesting areas for potential operational focus to enhance liquidity and asset utilization efficiency.
Turnover Ratios
Average No. Days
Inventory Turnover
Northrop Grumman Corp., 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 millions) | |||||||||||||||||||||||
| Cost of sales | |||||||||||||||||||||||
| Inventoried costs, net | |||||||||||||||||||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Inventory turnover1 | |||||||||||||||||||||||
| Benchmarks | |||||||||||||||||||||||
| Inventory Turnover, Competitors2 | |||||||||||||||||||||||
| Boeing Co. | |||||||||||||||||||||||
| Caterpillar Inc. | |||||||||||||||||||||||
| Eaton Corp. plc | |||||||||||||||||||||||
| GE Aerospace | |||||||||||||||||||||||
| Honeywell International Inc. | |||||||||||||||||||||||
| Lockheed Martin Corp. | |||||||||||||||||||||||
| RTX 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).
1 Q1 2023 Calculation
Inventory turnover
= (Cost of salesQ1 2023
+ Cost of salesQ4 2022
+ Cost of salesQ3 2022
+ Cost of salesQ2 2022)
÷ Inventoried costs, net
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The analysis of the quarterly financial data reveals several notable trends in the cost of sales, inventoried costs, and inventory turnover over the period examined.
- Cost of Sales
- The cost of sales exhibited fluctuations throughout the quarters, with a general upward trend from the early periods in 2019 through the end of 2020. Specifically, costs increased from 6,493 million USD in March 2019 to a peak of 8,209 million USD in December 2022. However, there are periods of decline observed, such as in mid-2021 and early 2023, where costs notably reduced before rising again. This pattern indicates variability potentially influenced by operational adjustments, market conditions, or supply chain factors.
- Inventoried Costs, Net
- Inventoried costs experienced steady growth over the time frame, rising from 778 million USD in March 2019 to 1,115 million USD in March 2023. This gradual increase suggests an accumulation or buildup of inventory assets. While minor quarter-to-quarter fluctuations occurred, the prevailing direction is an expanding inventory base, which may reflect either strategic stockpiling or changes in sales dynamics.
- Inventory Turnover Ratio
- The inventory turnover ratio presents a less consistent trend. Initially, the ratio rose from 31.65 in the first quarter of 2019 to a peak of 38.63 in December 2020, implying improved efficiency in managing inventory relative to cost of sales. However, following this peak, there is a marked decline in turnover ratio, descending to 26.48 by March 2023. This downward trend indicates a reduction in how quickly inventory is being converted into sales, potentially signaling slower sales velocity or accumulating excess inventory.
In summary, while cost of sales and inventoried costs both demonstrate upward trends, inventory turnover exhibits a rise followed by a significant decline. This juxtaposition may suggest challenges in inventory management or shifts in demand and supply patterns impacting the company's operational efficiency in the most recent periods.
Receivables Turnover
Northrop Grumman Corp., 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 millions) | |||||||||||||||||||||||
| Sales | |||||||||||||||||||||||
| Accounts receivable, net | |||||||||||||||||||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Receivables turnover1 | |||||||||||||||||||||||
| Benchmarks | |||||||||||||||||||||||
| Receivables Turnover, Competitors2 | |||||||||||||||||||||||
| Boeing Co. | |||||||||||||||||||||||
| Caterpillar Inc. | |||||||||||||||||||||||
| Eaton Corp. plc | |||||||||||||||||||||||
| GE Aerospace | |||||||||||||||||||||||
| Honeywell International Inc. | |||||||||||||||||||||||
| Lockheed Martin Corp. | |||||||||||||||||||||||
| RTX 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).
1 Q1 2023 Calculation
Receivables turnover
= (SalesQ1 2023
+ SalesQ4 2022
+ SalesQ3 2022
+ SalesQ2 2022)
÷ Accounts receivable, net
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The analysis of the quarterly financial data reveals several key trends and patterns regarding sales, accounts receivable, and receivables turnover over the examined periods.
- Sales
- Sales values exhibit a generally upward trajectory with some fluctuations throughout the periods. Starting from $8,189 million in the first quarter of 2019, sales showed incremental increases, peaking notably at $10,212 million in the fourth quarter of 2020. Following this peak, sales figures experienced minor declines and volatility, with quarters showing decreases and recoveries, such as a dip to $8,639 million in the fourth quarter of 2021 and a recovery to $10,033 million by the fourth quarter of 2022. The latest quarter, ending March 31, 2023, records sales at $9,301 million, indicating a slight decline from the previous quarter but remaining relatively stable compared to earlier periods.
- Accounts Receivable, Net
- Accounts receivable figures show a mixed pattern with considerable variability across quarters. Initial levels were around $2,166 million at the start of 2019, declining notably to $1,326 million by the end of that year, potentially reflecting tighter collection efforts or changes in credit terms. Following this, receivables increased again reaching $2,387 million in the second quarter of 2022, marking the highest point in the timeline. However, subsequent quarters saw a reduction in receivables, dropping to $2,061 million by the first quarter of 2023. This variation suggests fluctuations in the credit extended to customers or collection efficiency across quarters.
- Receivables Turnover
- The receivables turnover ratio experienced considerable fluctuations, reflecting changes in collection efficiency relative to outstanding receivables. Starting from 14.57 in early 2019, the ratio surged to a high of around 25.52 by the end of 2019, indicating a faster collection cycle during that period. Throughout 2020 and 2021, turnover remained elevated with figures generally between 18 and 24, suggesting relatively efficient receivables management despite fluctuations. Notably, in mid-2022, the ratio declined to 14.64, coinciding with higher accounts receivable levels, which may indicate slower collection rates. The turnover rebounded again to 24.22 in late 2022 but tapered to 18.00 by the first quarter of 2023, reflecting variability in the efficiency with which receivables translate into cash.
Overall, the data present a picture of steady sales growth tempered by varying efficiency in managing accounts receivable. The fluctuations in receivables turnover emphasize the cyclical nature of collection processes and possible shifts in credit policy or customer payment behavior over time. The company's ability to maintain receivables turnover at relatively high levels in most quarters suggests generally effective working capital management despite the observed variability.
Payables Turnover
Northrop Grumman Corp., payables turnover calculation (quarterly data)
| Mar 31, 2023 | Dec 31, 2022 | Sep 30, 2022 | Jun 30, 2022 | Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | |||||||||||||||||||||||
| Cost of sales | |||||||||||||||||||||||
| Trade accounts payable | |||||||||||||||||||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Payables turnover1 | |||||||||||||||||||||||
| Benchmarks | |||||||||||||||||||||||
| Payables Turnover, Competitors2 | |||||||||||||||||||||||
| Boeing Co. | |||||||||||||||||||||||
| Caterpillar Inc. | |||||||||||||||||||||||
| Eaton Corp. plc | |||||||||||||||||||||||
| GE Aerospace | |||||||||||||||||||||||
| Honeywell International Inc. | |||||||||||||||||||||||
| Lockheed Martin Corp. | |||||||||||||||||||||||
| RTX 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).
1 Q1 2023 Calculation
Payables turnover
= (Cost of salesQ1 2023
+ Cost of salesQ4 2022
+ Cost of salesQ3 2022
+ Cost of salesQ2 2022)
÷ Trade accounts payable
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The financial data over multiple quarters reveals several patterns concerning cost of sales, trade accounts payable, and payables turnover ratio.
- Cost of Sales
- The cost of sales shows fluctuations across the observed periods with a generally increasing trend. Starting at 6,493 million US dollars in the first quarter of 2019, it experienced small increases and decreases through 2019, reaching 6,615 million at year's end. The cost rose notably in the second half of 2020, peaking at 8,122 million in December 2020, possibly indicating higher production or procurement costs. It then decreased slightly through 2021 but remained volatile. In 2022 and early 2023, the cost tended to increase again, with a significant rise to 8,209 million in December 2022 before declining to 7,316 million by March 2023.
- Trade Accounts Payable
- The trade accounts payable show a varied pattern without a clear linear trend. Beginning at 1,932 million US dollars in early 2019, payables increased to around 2,226 million by the end of 2019 but then fell to 1,806 million in December 2020. Subsequently, there was a recovery and upward movement, reaching as high as 2,587 million by December 2022, before decreasing to 2,136 million in the first quarter of 2023. These fluctuations suggest changing payment timings or credit terms with suppliers.
- Payables Turnover Ratio
- The payables turnover ratio reflected varying payment efficiency across quarters. Starting near 12.74 in the first quarter of 2019, it rose to approximately 13.62 by mid-2020, indicating faster payment of accounts payable. The ratio peaked sharply at 16.24 in December 2020, suggesting a very rapid payables turnover during that quarter. Following this peak, there was a gradual decline to 11.26 by the end of 2022, which may imply slower payment processing or extended credit terms. In the first quarter of 2023, it rebounded to 13.82, indicating improved payment turnover.
Overall, the data indicate cost increases over time with periodic volatility, trade payables that fluctuate without a sustained trend, and a payables turnover ratio that shows periods of accelerated payments followed by slower turnover before improving again recently. These variations could reflect operational, market, or supply chain dynamics influencing procurement costs and supplier payment practices.
Working Capital Turnover
Northrop Grumman Corp., 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 millions) | |||||||||||||||||||||||
| Current assets | |||||||||||||||||||||||
| Less: Current liabilities | |||||||||||||||||||||||
| Working capital | |||||||||||||||||||||||
| Sales | |||||||||||||||||||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Working capital turnover1 | |||||||||||||||||||||||
| Benchmarks | |||||||||||||||||||||||
| Working Capital Turnover, Competitors2 | |||||||||||||||||||||||
| Boeing Co. | |||||||||||||||||||||||
| Caterpillar Inc. | |||||||||||||||||||||||
| Eaton Corp. plc | |||||||||||||||||||||||
| GE Aerospace | |||||||||||||||||||||||
| Honeywell International Inc. | |||||||||||||||||||||||
| Lockheed Martin Corp. | |||||||||||||||||||||||
| RTX 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).
1 Q1 2023 Calculation
Working capital turnover
= (SalesQ1 2023
+ SalesQ4 2022
+ SalesQ3 2022
+ SalesQ2 2022)
÷ Working capital
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The analysis of the quarterly financial data indicates notable fluctuations in working capital, sales, and working capital turnover ratios over the examined periods. The observation of these metrics provides insight into the operational efficiency and liquidity management across different quarters.
- Working Capital
- Working capital exhibited a generally volatile trend with peaks and troughs. It started at 1,622 million US dollars in the first quarter of 2019 and reached its highest value of 5,764 million US dollars by the end of 2020. However, from 2021 onwards, working capital showed a declining pattern with intermittent slightly higher values but trending downward to 901 million US dollars in the last quarter of 2022 before recovering modestly to 2,327 million US dollars by the first quarter of 2023.
- Sales
- Sales figures showed relative stability with a gradual upward trend and seasonal fluctuations. Sales increased from 8,189 million US dollars in early 2019 to their peak of 10,212 million US dollars at the end of 2020. Following this peak, sales remained stable but slightly lower, fluctuating around values between approximately 8,600 million and 10,000 million US dollars through 2021 to early 2023, ending at 9,301 million US dollars in the first quarter of 2023.
- Working Capital Turnover Ratio
- The working capital turnover ratio showed substantial variations reflecting changes in both sales and working capital levels. This ratio was relatively high at 19.45 in early 2019, fell steadily to 6.38 by the end of 2020 as working capital increased sharply relative to sales, then rebounded sharply in 2022 reaching an unprecedented peak of 40.62 in the last quarter of 2022. This spike was associated with significant contraction in working capital while sales remained steady. In early 2023, the ratio normalized to 15.95, suggesting a recalibration of operational efficiency and working capital usage.
Overall, the data suggests that while sales remained broadly stable with gradual growth and seasonal dynamics, working capital management experienced significant fluctuations. The sharp increase in working capital during 2020 might indicate increased inventory, receivables, or other current assets possibly related to operational adjustments or external conditions. The subsequent rapid decline and the associated spikes in the turnover ratio suggest periods of heightened working capital efficiency or potentially tight liquidity positions. The trends merit attention for cash management and operational planning to maintain a balance between liquidity and sales growth.
Average Inventory Processing Period
Northrop Grumman Corp., 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 | |||||||||||||||||||||||
| Short-term Activity Ratio (no. days) | |||||||||||||||||||||||
| Average inventory processing period1 | |||||||||||||||||||||||
| Benchmarks (no. days) | |||||||||||||||||||||||
| Average Inventory Processing Period, Competitors2 | |||||||||||||||||||||||
| Boeing Co. | |||||||||||||||||||||||
| Caterpillar Inc. | |||||||||||||||||||||||
| Eaton Corp. plc | |||||||||||||||||||||||
| GE Aerospace | |||||||||||||||||||||||
| Honeywell International Inc. | |||||||||||||||||||||||
| Lockheed Martin Corp. | |||||||||||||||||||||||
| RTX 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).
1 Q1 2023 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =
2 Click competitor name to see calculations.
The analysis of inventory turnover ratios over the examined quarterly periods reveals a fluctuating trend with notable variations. Initially, the inventory turnover ratio shows a gradual increase from 31.65 to a peak of 38.63 by the end of 2020, indicating an improvement in the frequency at which inventory is sold and replaced. However, following this peak, there is a consistent decline observed through 2022 and into early 2023, with the ratio dropping to 26.48. This downward trend suggests a reduction in inventory turnover efficiency during the latest periods.
Conversely, the average inventory processing period, expressed in number of days, displays a generally inverse pattern to the inventory turnover ratio. It remains relatively stable at approximately 11 days for much of 2019 and 2020, dropping to 9 days during the peak inventory turnover period in late 2020. From 2021 onward, the processing period gradually increases, reaching 14 days by the first quarter of 2023. This increase indicates that inventory remains in stock for a longer duration before being sold, which aligns with the observed decline in inventory turnover in the same timeframe.
Together, these indicators suggest that the company's inventory management efficiency improved up to late 2020 but has experienced a deterioration since then. The lengthening of the average inventory processing period combined with a decreasing inventory turnover ratio points to potentially slower sales or overstocking issues emerging in recent quarters. Continuous monitoring and further analysis of underlying causes would be prudent to address these trends.
Average Receivable Collection Period
Northrop Grumman Corp., 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 | |||||||||||||||||||||||
| Short-term Activity Ratio (no. days) | |||||||||||||||||||||||
| Average receivable collection period1 | |||||||||||||||||||||||
| Benchmarks (no. days) | |||||||||||||||||||||||
| Average Receivable Collection Period, Competitors2 | |||||||||||||||||||||||
| Boeing Co. | |||||||||||||||||||||||
| Caterpillar Inc. | |||||||||||||||||||||||
| Eaton Corp. plc | |||||||||||||||||||||||
| GE Aerospace | |||||||||||||||||||||||
| Honeywell International Inc. | |||||||||||||||||||||||
| Lockheed Martin Corp. | |||||||||||||||||||||||
| RTX 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).
1 Q1 2023 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =
2 Click competitor name to see calculations.
The receivables turnover ratio exhibits a fluctuating pattern over the observed periods. Initially, the ratio increased from 14.57 to 25.52 by the end of 2019, indicating an improvement in the efficiency of receivables collection during that year. In 2020, the ratio saw moderate fluctuations, ranging mostly between 16.04 and 24.52, suggesting some variability but maintaining relatively efficient collection. The year 2021 showed a generally stable to improving trend, with the ratio moving from 21.83 up to 24.31, implying continued strong performance in receivables turnover.
However, starting from 2022, there is a notable decrease in the turnover ratio, particularly in the second quarter of 2022 where it dropped sharply to 14.64, signaling a potential slowdown in collections or an increase in receivables outstanding. Following this dip, the ratio rebounded somewhat in subsequent periods but remained inconsistent, registering 18.19, 24.22, and then dropping again to 18 in the first quarter of 2023.
The average receivable collection period complements these observations. It shortened significantly from 25 days to 14 days by the end of 2019, reflecting faster collections. Throughout 2020 and 2021, the period generally ranged from about 15 to 20 days, indicating stable and efficient collections. In 2022, the collection period increased notably to 25 days in the second quarter, coinciding with the dip in turnover ratio, which supports the inference of slower collections during this time frame. This period shortened again afterward, reaching 15 days by the end of 2022, but extended to 20 days by the first quarter of 2023.
Overall, the data indicate that receivables management was most effective during 2019 and 2021, with a clear decline in performance during 2022 as reflected by longer collection periods and lower turnover ratios. The first quarter of 2023 shows signs of ongoing variability in collection efficiency, warranting attention to cash conversion cycles and potential receivables aging.
Operating Cycle
Northrop Grumman Corp., 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 | |||||||||||||||||||||||
| Average receivable collection period | |||||||||||||||||||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Operating cycle1 | |||||||||||||||||||||||
| Benchmarks | |||||||||||||||||||||||
| Operating Cycle, Competitors2 | |||||||||||||||||||||||
| Boeing Co. | |||||||||||||||||||||||
| Caterpillar Inc. | |||||||||||||||||||||||
| Eaton Corp. plc | |||||||||||||||||||||||
| GE Aerospace | |||||||||||||||||||||||
| Honeywell International Inc. | |||||||||||||||||||||||
| Lockheed Martin Corp. | |||||||||||||||||||||||
| RTX 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).
1 Q1 2023 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= + =
2 Click competitor name to see calculations.
- Inventory Processing Period
- The average inventory processing period showed relative stability between 9 and 14 days over the observed quarters. It consistently remained around 11 days in most periods from 2019 to early 2022, with a noticeable decrease to 9 days in December 2020. However, from mid-2022 onwards, there was a gradual increase, reaching a peak of 14 days by March 2023. This suggests a trend of slower inventory turnover in the most recent quarters.
- Receivable Collection Period
- The average receivable collection period experienced fluctuations throughout the period. Initially, it varied between 14 and 25 days from 2019 into early 2020, with a notable dip to 14 days at the end of 2019 and December 2020. From 2021 onwards, the collection period remained mostly between 15 and 20 days but spiked to 25 days in June 2022. Subsequently, it decreased back to 15-20 days by March 2023. These fluctuations indicate some variability in the time taken to collect receivables, with a temporary elongation mid-2022.
- Operating Cycle
- The operating cycle, which combines inventory processing and receivable collection, generally reflected the trends of the underlying components. It ranged from a low of 24 days (December 2020) to a high of 37 days (March 2019 and June 2022). Notably, the operating cycle shortened towards the end of 2019 and 2020, corresponding to faster inventory and receivable management, but then extended again notably in mid-2022. By March 2023, the operating cycle was 34 days, indicating an overall lengthening compared to the lows seen in late 2020 and 2021.
- Summary
- Over the examined timeframe, there is evidence of relative consistency in inventory and receivables management during 2019-2021, with periods of shorter processing and collection times contributing to a reduced operating cycle. However, there is a discernible reversal starting mid-2022, when both inventory processing and receivable collection periods lengthened, resulting in an extended operating cycle. This may imply potential challenges in inventory turnover and collections efficiency in the most recent quarters.
Average Payables Payment Period
Northrop Grumman Corp., 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 | |||||||||||||||||||||||
| Short-term Activity Ratio (no. days) | |||||||||||||||||||||||
| Average payables payment period1 | |||||||||||||||||||||||
| Benchmarks (no. days) | |||||||||||||||||||||||
| Average Payables Payment Period, Competitors2 | |||||||||||||||||||||||
| Boeing Co. | |||||||||||||||||||||||
| Caterpillar Inc. | |||||||||||||||||||||||
| Eaton Corp. plc | |||||||||||||||||||||||
| GE Aerospace | |||||||||||||||||||||||
| Honeywell International Inc. | |||||||||||||||||||||||
| Lockheed Martin Corp. | |||||||||||||||||||||||
| RTX 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).
1 Q1 2023 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ =
2 Click competitor name to see calculations.
The payables turnover ratio exhibits fluctuations over the observed periods without a consistent upward or downward trend. Starting from 12.74 in the first quarter of 2019, the ratio peaked at 16.24 in the last quarter of 2020, indicating an increased frequency of payments to suppliers during that period. Subsequent quarters saw a decline to as low as 11.26 by the end of 2022, followed by a recovery to 13.82 in the first quarter of 2023. These variations suggest shifts in the company’s payment practices or supplier terms across quarters.
The average payables payment period, expressed in days, inversely correlates with the payables turnover ratio. The period decreased to a low of 22 days in the last quarter of 2020, aligning with the peak in payables turnover, indicating faster payment cycles at that time. Conversely, the payment period extended to 32 days by the end of 2022, reflecting slower payments to suppliers during that timeframe. By the first quarter of 2023, the payment period shortened again to 26 days, suggesting a return to somewhat quicker settlements.
Overall, the data points to variability in the company's payment strategies. Periods of higher payables turnover and lower average payment days correspond with more rapid payments to suppliers, possibly to take advantage of early payment discounts or maintain strong supplier relationships. Conversely, longer payment periods and lower turnover ratios may imply tighter cash flow management or extended supplier credit terms. The recent trend towards shortening the payment period may signify improved liquidity or strategic adjustments in working capital management.
Cash Conversion Cycle
Northrop Grumman Corp., 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 | |||||||||||||||||||||||
| Average receivable collection period | |||||||||||||||||||||||
| Average payables payment period | |||||||||||||||||||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Cash conversion cycle1 | |||||||||||||||||||||||
| Benchmarks | |||||||||||||||||||||||
| Cash Conversion Cycle, Competitors2 | |||||||||||||||||||||||
| Boeing Co. | |||||||||||||||||||||||
| Caterpillar Inc. | |||||||||||||||||||||||
| Eaton Corp. plc | |||||||||||||||||||||||
| GE Aerospace | |||||||||||||||||||||||
| Honeywell International Inc. | |||||||||||||||||||||||
| Lockheed Martin Corp. | |||||||||||||||||||||||
| RTX 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).
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.
An analysis of the financial efficiency metrics over the observed periods reveals several key trends and fluctuations. The focus is on inventory management, receivables collection, payables payment, and the overall cash conversion cycle to assess operational effectiveness.
- Average Inventory Processing Period
- This metric remained relatively stable around 11 days for most quarters until the end of 2020, when it briefly decreased to 9 days. However, from early 2022, there was a gradual increase, reaching up to 14 days by the first quarter of 2023. This upward shift suggests a slight slowdown in inventory turnover, potentially indicating either longer holding times or supply chain delays.
- Average Receivable Collection Period
- The period exhibited noticeable volatility, ranging from a low of 14 days in late 2019 to highs around 25 days in multiple quarters such as the first quarter of 2019 and mid-2022. A notable decrease occurred during late 2019 and early 2020, implying improved receivables collection efficiency. However, the spike in mid-2022 suggests some deterioration in collection processes or customer payment delays during that timeframe. Overall, this metric fluctuated without a clear trend indicating consistent improvement or decline.
- Average Payables Payment Period
- Payables payment periods mostly hovered in the high 20s range, with occasional dips as low as 22 days in the final quarter of 2020. The period generally held steady between 27 and 32 days across the timeline, indicating consistent payment terms management. Some increase in payment period was observed by late 2022 and early 2023, suggesting the company might have slightly extended its payment cycle during these later periods.
- Cash Conversion Cycle
- The cash conversion cycle (CCC) showed considerable variability, with values oscillating from as low as -6 days (indicative of negative cycle and favorable cash flow timing) in late 2019 to positive days around 9 in mid-2022. Negative CCC values occurred notably at year-end 2019 and near the end of 2021, implying highly efficient working capital management during those periods. Conversely, positive peaks, such as in early 2022, point to extended cash flow cycles potentially due to slower collections or inventory turnover. The inconsistency in the CCC emphasizes fluctuating operational efficiencies over the quarters.
In summary, the data indicates generally stable payables management alongside variable inventory and receivables cycles. The incremental rise in inventory processing and fluctuations in receivables suggest areas where operational efficiency might have been challenged, particularly in 2022. The cash conversion cycle reflects these changes, underscoring periods of both efficient and stretched working capital management throughout the observed timeline.