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.
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Short-term Activity Ratios (Summary)
Norfolk Southern Corp., short-term (operating) activity ratios (quarterly data)
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31).
- Inventory Turnover
- The inventory turnover ratio exhibits fluctuating trends between March 2018 and March 2022. Starting at 10.15 in March 2018, it generally declines toward late 2018, reaching a low near 9.26 in September 2020, followed by a recovery phase that peaks at 11.58 by December 2021 before slightly declining to 10.20 in March 2022. This pattern suggests variability in inventory management efficiency with occasional improvements.
- Receivables Turnover
- Receivables turnover maintains a relatively narrow range throughout the reported periods. From 11.05 in March 2018, it shows a mild upward movement, peaking at about 12.46 in mid-2020, but experiences some volatility thereafter, declining modestly to 10.67 by March 2022. This stability indicates consistent collection performance with minor disturbances.
- Payables Turnover
- The payables turnover ratio generally increases from 1.61 in March 2018 to 2.28 in March 2022, with minor fluctuations along the way. This upward trend indicates that the company has been accelerating its rate of payments to suppliers over time.
- Working Capital Turnover
- Data for working capital turnover is sparse but indicates significant volatility during available reporting periods. Notably, the ratio spikes sharply to 181.54 in December 2020 from a low of 17.26 in June 2020, followed by a decline later on. Such fluctuations may reflect changes in short-term asset and liability management or operational cycles.
- Average Inventory Processing Period
- The average inventory period showcases some cyclical behavior with an initial decrease from 36 days in March 2018 to a low of 27 days in March 2019, suggesting faster inventory turnover. Following this, periods fluctuate mostly between 32 and 40 days, ending at 36 days in March 2022, indicating a return to earlier processing speeds after periods of variation.
- Average Receivable Collection Period
- The receivable collection period remains fairly stable, ranging between 29 and 35 days across the timeline. This reflects consistent credit and collection policies and timing over the analyzed quarters.
- Operating Cycle
- The operating cycle demonstrates moderate stability with slight fluctuations. Beginning around 69-73 days in the earlier quarters, it dips to a low near 59 days in March 2019, then fluctuates between 64 and 75 days, showing no clear long-term upward or downward trend but some short-term variability likely related to changes in inventory or receivable periods.
- Average Payables Payment Period
- The average payables payment period shows a gradual decline from about 227 days in March 2018 to a lower level near 160 days in March 2022, although it experiences intermittent rises. This suggests a tendency to shorten the credit extended by suppliers over time, consistent with the observed increase in payables turnover.
- Cash Conversion Cycle
- The cash conversion cycle remains negative throughout, ranging from approximately -158 days in March 2018 to a relatively less negative -90 days in March 2022. The negative values indicate that the company is able to convert its investments in inventory and other resources into cash before needing to pay its bills, with a trend toward a shorter cash conversion cycle, implying improved cash flow management.
Turnover Ratios
Average No. Days
Inventory Turnover
Norfolk Southern Corp., inventory turnover calculation (quarterly data)
| Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||||
| Cost of railway operating revenues | ||||||||||||||||||||||||||||
| Materials and supplies | ||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||
| Inventory turnover1 | ||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||
| Inventory Turnover, Competitors2 | ||||||||||||||||||||||||||||
| FedEx Corp. | ||||||||||||||||||||||||||||
| Union Pacific Corp. | ||||||||||||||||||||||||||||
| United Airlines Holdings Inc. | ||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31).
1 Q1 2022 Calculation
Inventory turnover
= (Cost of railway operating revenuesQ1 2022
+ Cost of railway operating revenuesQ4 2021
+ Cost of railway operating revenuesQ3 2021
+ Cost of railway operating revenuesQ2 2021)
÷ Materials and supplies
= ( + + + )
÷ =
2 Click competitor name to see calculations.
- Cost of railway operating revenues
- The cost of railway operating revenues demonstrates fluctuations across the periods observed. Initially, values decreased from 590 million USD in March 2017 to 507 million USD in December 2017. Subsequently, the cost rose steadily, peaking at 724 million USD in the fourth quarter of 2018. A downward adjustment followed in 2019, with costs ranging between 649 and 683 million USD. In 2020, a notable decline is evident, coinciding with a low of 456 million USD in the second quarter, potentially due to external economic or operational factors. The value increased after mid-2020, reaching 738 million USD by the first quarter of 2022, indicating recovery or expansion in operating activities.
- Materials and supplies
- This category exhibits variability over the quarters, with an initial downward trend from 281 million USD in March 2017 to 222 million USD in December 2017. This was followed by moderate increases and decreases between 2018 and early 2019, peaking at 267 million USD in September 2018. During 2019 and 2020, values fluctuated around the mid-200 million range, reaching a low of 221 million USD in the fourth quarter of 2020. The figures show some recovery post-2020, culminating at 264 million USD by March 2022. These movements suggest periodic changes in procurement or inventory management strategies.
- Inventory turnover ratio
- Inventory turnover shows a generally stable to slightly increasing trend over the periods with available data. Starting at 10.15 in March 2018, the ratio fluctuates between approximately 9.0 and 13.6, peaking notably at 13.61 in December 2018. This peak indicates a period of efficient inventory management or higher sales volume relative to inventory holdings. Subsequently, the turnover stabilizes around values close to 10, with minor variations through 2019, 2020, and into early 2022. Overall, the data points to consistent inventory utilization, with occasional improvements in turnover efficiency.
Receivables Turnover
Norfolk Southern Corp., receivables turnover calculation (quarterly data)
| Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||||
| Railway operating revenues | ||||||||||||||||||||||||||||
| Accounts receivable, net | ||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||
| Receivables turnover1 | ||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||
| Receivables Turnover, Competitors2 | ||||||||||||||||||||||||||||
| FedEx Corp. | ||||||||||||||||||||||||||||
| Uber Technologies Inc. | ||||||||||||||||||||||||||||
| Union Pacific Corp. | ||||||||||||||||||||||||||||
| United Airlines Holdings Inc. | ||||||||||||||||||||||||||||
| United Parcel Service Inc. | ||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31).
1 Q1 2022 Calculation
Receivables turnover
= (Railway operating revenuesQ1 2022
+ Railway operating revenuesQ4 2021
+ Railway operating revenuesQ3 2021
+ Railway operating revenuesQ2 2021)
÷ Accounts receivable, net
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The analysis of the quarterly financial data reveals several noteworthy trends across the reviewed periods.
- Railway Operating Revenues
- The railway operating revenues demonstrate a generally stable to slightly increasing trend from the first quarter of 2017 through the first quarter of 2022. Initial values near US$2,575 million increased steadily to a peak around US$2,915 million by March 2022, despite some fluctuations. Notably, a dip is observed during the middle quarters of 2020, likely associated with broader economic challenges, where revenues declined from US$2,625 million in March 2020 to US$2,085 million in June 2020. However, a recovery trend followed, with revenues rising again towards the end of 2020 and into 2021 and 2022.
- Accounts Receivable, Net
- The net accounts receivable values reveal a pattern of mild fluctuation throughout the periods analyzed. Starting at US$998 million in the first quarter of 2017, amounts fluctuated with some decline into mid-2020, reaching a low near US$822 million in June 2020, consistent with the observed dip in revenues. Subsequently, the accounts receivable values exhibited a recovery, increasing to US$1,070 million by March 2022. This upward recovery aligns with the revenue rebound, suggesting normalization of customer payments and sales volume.
- Receivables Turnover Ratio
- The receivables turnover ratio exhibits moderate variation over the periods reported, with values generally oscillating between approximately 10.5 and 12.5. The ratio experienced a slight increase from about 11.05 in early 2017 to a peak nearing 12.46 in mid-2019 and mid-2020, indicating improved efficiency in collecting receivables during those periods. However, there was a tendency toward a moderate decline in turnover ratios after 2020, dropping back to about 10.67 by the first quarter of 2022. This pattern suggests some slowdown in collection efficiency or changes in credit policies following the mid-2020 period.
Overall, the data indicate that the company experienced a revenue and accounts receivable contraction during the mid-2020 period, coinciding with the global economic climate, followed by a recovery phase extending into 2022. The fluctuation in the receivables turnover ratio suggests variations in collection efficiency, potentially influenced by external factors affecting customer payment behavior.
Payables Turnover
Norfolk Southern Corp., payables turnover calculation (quarterly data)
| Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||||
| Cost of railway operating revenues | ||||||||||||||||||||||||||||
| Accounts payable | ||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||
| Payables turnover1 | ||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||
| Payables Turnover, Competitors2 | ||||||||||||||||||||||||||||
| FedEx Corp. | ||||||||||||||||||||||||||||
| Uber Technologies Inc. | ||||||||||||||||||||||||||||
| United Airlines Holdings Inc. | ||||||||||||||||||||||||||||
| United Parcel Service Inc. | ||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31).
1 Q1 2022 Calculation
Payables turnover
= (Cost of railway operating revenuesQ1 2022
+ Cost of railway operating revenuesQ4 2021
+ Cost of railway operating revenuesQ3 2021
+ Cost of railway operating revenuesQ2 2021)
÷ Accounts payable
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The analysis of the quarterly financial data reveals several notable trends in the company's cost of railway operating revenues, accounts payable, and payables turnover ratios over the observed periods.
- Cost of Railway Operating Revenues
- The cost of railway operating revenues showed fluctuations throughout the periods under review. Initially, it decreased from 590 million US$ in March 2017 to 507 million US$ in December 2017. Following this decline, there was a marked increase reaching a peak of 724 million US$ in both September and December 2018. Subsequently, the cost trended downward again, hitting its lowest point at 456 million US$ in June 2020, which could be indicative of operational adjustments or external market impacts during that time. From mid-2020 onwards, the cost climbed steadily, reaching 738 million US$ by March 2022. This upward movement in recent quarters suggests increasing expenses associated with railway operations, possibly due to inflationary pressures or expanded operational scale.
- Accounts Payable
- Accounts payable exhibited a generally volatile but overall increasing pattern over the analyzed timeline. Beginning at 1,211 million US$ in March 2017, the figure experienced several fluctuations, peaking at 1,505 million US$ in December 2018 before declining to a lower range around 1,016 million US$ in December 2020. Thereafter, accounts payable increased again steadily, reaching 1,351 million US$ in March 2022. The variation indicates changes in the company's credit terms with suppliers, purchasing behavior, or possibly the timing of payments. The lower level noted during late 2020 may reflect measures to conserve cash or changes in procurement amid economic uncertainties.
- Payables Turnover Ratio
- The payables turnover ratio, available from December 2017 onwards, displayed a range between approximately 1.61 and 2.28 times. It generally hovered close to the 2.0 mark, with periods of both slight increases and decreases. The ratio peaked at 2.28 in March 2022, suggesting an improvement in payment efficiency or a reduction in the average duration to settle payables. The lowest observed ratios, around 1.61 to 1.85 in late 2017 and mid-2020 respectively, may indicate slower payment cycles during these periods. Overall, the ratio demonstrates a relatively stable pattern with a modest trend toward faster payables turnover in recent quarters.
Working Capital Turnover
Norfolk Southern Corp., working capital turnover calculation (quarterly data)
| Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||||
| Current assets | ||||||||||||||||||||||||||||
| Less: Current liabilities | ||||||||||||||||||||||||||||
| Working capital | ||||||||||||||||||||||||||||
| Railway operating revenues | ||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||
| Working capital turnover1 | ||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||
| Working Capital Turnover, Competitors2 | ||||||||||||||||||||||||||||
| FedEx Corp. | ||||||||||||||||||||||||||||
| Uber Technologies Inc. | ||||||||||||||||||||||||||||
| Union Pacific Corp. | ||||||||||||||||||||||||||||
| United Airlines Holdings Inc. | ||||||||||||||||||||||||||||
| United Parcel Service Inc. | ||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31).
1 Q1 2022 Calculation
Working capital turnover
= (Railway operating revenuesQ1 2022
+ Railway operating revenuesQ4 2021
+ Railway operating revenuesQ3 2021
+ Railway operating revenuesQ2 2021)
÷ Working capital
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The analysis of the quarterly financial data reveals several notable trends in working capital, railway operating revenues, and working capital turnover ratios over the observed period.
- Working Capital
- Working capital showed significant volatility across the quarters. Initially, it held a negative position, starting at -116 million USD in early 2017 and deteriorating further towards -729 million USD by the end of 2018. In 2019, the negative working capital trend continued, reaching as low as -963 million USD in the first quarter. A marked improvement surfaced in 2020, turning positive with values peaking at 574 million USD in the third quarter. However, subsequent quarters saw fluctuations again, with working capital values declining to negative incidents, such as -354 and -132 million USD in early 2022. This volatility suggests cyclical liquidity pressures and intermittent improvements in short-term financial positioning.
- Railway Operating Revenues
- Railway operating revenues exhibited a generally stable and slightly increasing trend over the period. Starting at 2,575 million USD in the first quarter of 2017, revenues steadily climbed towards a peak of 2,915 million USD by the first quarter of 2022. Notable dips appeared in 2020, likely impacted by broader economic conditions, with revenues declining to a low of 2,085 million USD in the second quarter. Subsequent recovery occurred throughout late 2020 and 2021, with revenues maintaining a stable upward trajectory.
- Working Capital Turnover
- The working capital turnover ratio data was sporadic, with reported figures only for limited quarters. A significant spike was noted in mid-2018 recording 117.51, which indicates exceptionally high operational efficiency concerning working capital during that period. In 2020 and 2021, the ratio showed wide variability with values such as 24.68, 17.26, and a surge up to 181.54 in the last quarter of 2020, followed by declines towards 34.82 in late 2021. These fluctuations imply varying degrees of operational effectiveness and liquidity management across quarters.
Overall, the data indicates a company experiencing considerable fluctuations in working capital management and turnover efficiency, while revenue streams remain comparatively stable with some cyclical softness around 2020. The positive working capital phase around 2020 suggests temporary improvements in liquidity, but return to negative levels subsequently may indicate ongoing challenges in working capital optimization.
Average Inventory Processing Period
Norfolk Southern Corp., average inventory processing period calculation (quarterly data)
| Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||
| Inventory turnover | ||||||||||||||||||||||||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||
| Average inventory processing period1 | ||||||||||||||||||||||||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||
| Average Inventory Processing Period, Competitors2 | ||||||||||||||||||||||||||||
| FedEx Corp. | ||||||||||||||||||||||||||||
| Union Pacific Corp. | ||||||||||||||||||||||||||||
| United Airlines Holdings Inc. | ||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31).
1 Q1 2022 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =
2 Click competitor name to see calculations.
The analysis of the inventory turnover ratio over the observed quarters reveals notable fluctuations with distinct peaks and troughs. Beginning in the first quarter of 2018, the ratio stood at 10.15, experienced a slight decline reaching 9.43 in the third quarter of 2018, followed by an increase that culminated in the highest value of 13.61 in the first quarter of 2019. Subsequently, the ratio gradually decreased, dipping below 10 in the first three quarters of 2020, before stabilizing around 9.5 to 10.2 through the end of 2020 and early 2021. From the second quarter of 2021 onward, the inventory turnover showed an upward trend, peaking again at 11.58 in the fourth quarter of 2021, before declining to 10.2 in the first quarter of 2022.
The average inventory processing period exhibits an inverse pattern consistent with the changes seen in inventory turnover. Starting at 36 days in the first quarter of 2018, the period increased slightly to 39 days in the third quarter of 2018 before dropping sharply to 27 days by the first quarter of 2019, coinciding with the peak in turnover. Following this, the number of days required to process inventory increased gradually, reaching 39 days again in the third quarter of 2020. Thereafter, the period fluctuated mostly between 32 and 40 days, with a slight decline toward the end of the period analyzed, registering 36 days in the first quarter of 2022.
Overall, the data suggest that the company experienced periods of improved inventory efficiency, particularly in early 2019 and late 2021, reflected by higher turnover ratios and shorter inventory processing periods. Conversely, mid-2018 to mid-2020 marked periods of relatively lower efficiency, with lower turnover ratios and longer inventory holding times. The observed patterns imply dynamic inventory management, potentially influenced by operational adjustments or market conditions during these periods.
- Inventory Turnover Ratio
- Varied between approximately 9.4 and 13.6, with notable peaks in Q1 2019 and Q4 2021, and troughs around mid-2018 and parts of 2020.
- Average Inventory Processing Period
- Ranged from 27 to 40 days, showing a general inverse relationship with the turnover ratio, with the shortest periods aligning with the highest turnovers.
- Trends and Insights
- Periods of heightened turnover correspond with more efficient inventory management and shorter processing times. The fluctuations indicate responsive inventory practices possibly aligned with business cycles or external factors impacting inventory flow.
Average Receivable Collection Period
Norfolk Southern Corp., average receivable collection period calculation (quarterly data)
| Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||
| Receivables turnover | ||||||||||||||||||||||||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||
| Average receivable collection period1 | ||||||||||||||||||||||||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||
| Average Receivable Collection Period, Competitors2 | ||||||||||||||||||||||||||||
| FedEx Corp. | ||||||||||||||||||||||||||||
| Uber Technologies Inc. | ||||||||||||||||||||||||||||
| Union Pacific Corp. | ||||||||||||||||||||||||||||
| United Airlines Holdings Inc. | ||||||||||||||||||||||||||||
| United Parcel Service Inc. | ||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31).
1 Q1 2022 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =
2 Click competitor name to see calculations.
- Receivables Turnover
- The receivables turnover ratio data available from the first quarter of 2017 indicates a generally stable but slightly fluctuating trend over the observed periods through March 2022. Starting near 11.05 in early 2017, the ratio experienced minor variations, with a peak around 12.46 during the first half of 2020. After this peak, the ratio declined somewhat, falling to approximately 10.67 by the first quarter of 2022. This suggests that the company maintained relatively consistent efficiency in collecting receivables, with some periods exhibiting strengthened turnover and others showing modest deceleration.
- Average Receivable Collection Period
- The average receivable collection period, which inversely correlates with receivables turnover, exhibits a complementary developing pattern. Initially recorded at 33 days in early 2017, it fluctuated slightly between 29 and 35 days through the timeline. Notably, the collection period shortened to its lowest around 29 days mid-2020, coinciding with the peak in receivables turnover. After this optimal point, the collection period lengthened again, rising gradually to about 34 days by the first quarter of 2022. Overall, the company shows a stable collection period with brief intervals of both improvement and elongation.
- Insights
- The data indicates a close relationship between receivables turnover and average collection period, consistent with expectations: as turnover increased, the collection period decreased, and vice versa. The peak turnover and shortest collection times occurring in 2020 may reflect specific operational efficiencies or external factors influencing cash flow management during that period. Subsequent declines in turnover and lengthening of the collection period suggest a relaxation in receivables management or changes in customer payment behaviors post-2020. Despite fluctuations, the company maintained solid receivables management metrics, with turnover ratios generally above 10 and collection periods around a month or slightly more, reflecting effective credit and collection control practices.
Operating Cycle
Norfolk Southern Corp., operating cycle calculation (quarterly data)
No. days
| Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||
| Average inventory processing period | ||||||||||||||||||||||||||||
| Average receivable collection period | ||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||
| Operating cycle1 | ||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||
| Operating Cycle, Competitors2 | ||||||||||||||||||||||||||||
| FedEx Corp. | ||||||||||||||||||||||||||||
| Union Pacific Corp. | ||||||||||||||||||||||||||||
| United Airlines Holdings Inc. | ||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31).
1 Q1 2022 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= + =
2 Click competitor name to see calculations.
The data reflects quarterly trends in inventory processing, receivable collection, and operating cycle over multiple years. Notably, the financial periods begin in the second quarter of 2017 with the earliest available data starting in March 2018 for these metrics.
- Average Inventory Processing Period
- The inventory processing period shows variability over the observed periods, with values ranging from a low of 27 days in March 2019 to a high of 40 days in June 2021. The data suggests a general pattern of seasonal fluctuations, with periods towards the end of each year often seeing slightly elevated days. From 2018 to 2022, the inventory processing period demonstrates a tendency to increase gradually until about 2020, peaking in mid-2021 before declining again in early 2022.
- Average Receivable Collection Period
- The receivable collection period remains relatively stable throughout the analyzed quarters. The periods fluctuate narrowly between 29 and 35 days, indicating consistency in collecting receivables. Minor variations occur, with a slight dip around late 2019 to mid-2020 and a modest increase in late 2021. Overall, the receivable collection period does not show any significant upward or downward trend.
- Operating Cycle
- The operating cycle, which combines the inventory processing and receivable collection periods, exhibits variability primarily driven by changes in inventory processing. The operating cycle decreases notably from around 71-73 days in early 2018 to a low of 59 days in March 2019. Subsequently, it trends upward, reaching a peak of 75 days in June 2021 before declining again towards early 2022. The period displays peaks typically aligned with higher inventory processing durations, indicating inventory management as a principal influence on cycle length.
In summary, the analysis reveals that while the receivable collection period has remained largely consistent, fluctuations in the inventory processing period significantly impact the overall operating cycle. The operating cycle shows an underlying seasonal and possibly external factor-driven pattern, with a marked increase around mid-2021 before receding. This suggests areas for potential operational focus, particularly in inventory management efficiency during peak periods.
Average Payables Payment Period
Norfolk Southern Corp., average payables payment period calculation (quarterly data)
| Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||
| Payables turnover | ||||||||||||||||||||||||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||
| Average payables payment period1 | ||||||||||||||||||||||||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||
| Average Payables Payment Period, Competitors2 | ||||||||||||||||||||||||||||
| FedEx Corp. | ||||||||||||||||||||||||||||
| Uber Technologies Inc. | ||||||||||||||||||||||||||||
| United Airlines Holdings Inc. | ||||||||||||||||||||||||||||
| United Parcel Service Inc. | ||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31).
1 Q1 2022 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ =
2 Click competitor name to see calculations.
- Payables Turnover Ratio
- The payables turnover ratio data starts from the first quarter of 2018. From that point, the ratio fluctuates within a relatively narrow range, beginning at 1.61 and generally increasing over time. Notably, there is a peak in the fourth quarter of 2020 where the ratio reaches 2.19, representing the highest turnover in the observed timeframe. The ratio slightly decreases afterward but remains above 1.8 in most quarters, ending at 2.28 in the first quarter of 2022. This upward trend indicates a moderate improvement in the frequency of payments to suppliers over the period analyzed.
- Average Payables Payment Period
- The average payables payment period, measured in the number of days, shows an inverse trend relative to the payables turnover ratio. Starting at 227 days in the first quarter of 2018, this metric declines over time with some fluctuations. It reaches a low of 160 days by the first quarter of 2022, indicating that the company on average took fewer days to settle its payables in the most recent quarter compared to earlier periods. Within this general declining trend, some quarters show short-term increases, such as in the fourth quarter of 2020 and the second quarter of 2021, but the overall long-term pattern reflects a trend toward faster payments.
- Relationships and Insights
- The inverse relationship between the payables turnover ratio and the average payables payment period is consistent with financial principles, where a higher turnover ratio corresponds to a shorter payment period. The data suggests an improving efficiency in payables management, highlighted by a gradual increase in turnover and a corresponding decrease in payment days. This development may reflect strategic efforts to manage supplier relationships, optimize cash flow, or benefit from early payment discounts during the period under review.
Cash Conversion Cycle
Norfolk Southern Corp., cash conversion cycle calculation (quarterly data)
No. days
| Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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 | ||||||||||||||||||||||||||||
| FedEx Corp. | ||||||||||||||||||||||||||||
| United Airlines Holdings Inc. | ||||||||||||||||||||||||||||
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31).
1 Q1 2022 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= + – =
2 Click competitor name to see calculations.
The analysis of the company's quarterly financial metrics reveals several notable trends in working capital management over the observed periods.
- Average Inventory Processing Period
- This metric displays fluctuations with an overall pattern of increase and decrease over time. Beginning with data from March 2018, the days ranged from 27 up to a peak of 40 days in June 2021, before declining again to 32 days by March 2022. The inventory processing period demonstrates some volatility but generally remains within a 27 to 40 days range, indicating moderate variability in inventory turnover speed.
- Average Receivable Collection Period
- The receivable collection period maintains relative stability across the quarters, fluctuating narrowly between 29 and 35 days. Noteworthy is a slight decrease around early 2020, reaching a low of 29 days, followed by a gradual increase peaking at 35 days in mid-2021, before slightly retreating again. This pattern suggests consistent efficiency in collecting receivables with minor seasonal or operational variances.
- Average Payables Payment Period
- The payables payment period exhibits a downward trend overall, decreasing from a high of 227 days in March 2018 down to 160 days by March 2022. Several interim fluctuations are present; for instance, a notable reduction occurs in mid-2019 and again in mid-2021. The decreasing payables period implies a trend towards quicker payments to suppliers, which may affect liquidity management and supplier relationships.
- Cash Conversion Cycle
- The cash conversion cycle, consistently negative throughout the periods, fluctuates between approximately -158 and -90 days. The cycle became less negative around the middle of 2021, reaching its highest point of -90 days by March 2022, indicating a shorter cash conversion timeframe. This negative cycle is driven primarily by the extended payables period relative to the sum of inventory and receivables periods, suggesting efficient cash flow management with delayed outflows relative to inflows.
In summary, the company maintains a relatively steady receivables collection period and a somewhat variable inventory processing duration. The payables payment period shows a declining trend, indicating earlier payments to vendors over time, which contributes to a shortening of the cash conversion cycle's negativity. The consistently negative yet improved cash conversion cycle suggests effective working capital management, where cash outflows are delayed sufficiently to finance inventory and receivables, thereby enhancing liquidity.