Stock Analysis on Net

Norfolk Southern Corp. (NYSE:NSC)

$22.49

This company has been moved to the archive! The financial data has not been updated since April 27, 2022.

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

Microsoft Excel

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Short-term Activity Ratios (Summary)

Norfolk Southern Corp., short-term (operating) activity ratios (quarterly data)

Microsoft Excel
Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
Turnover Ratios
Inventory turnover
Receivables turnover
Payables turnover
Working capital turnover
Average No. Days
Average inventory processing period
Add: Average receivable collection period
Operating cycle
Less: Average payables payment period
Cash conversion cycle

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


The analysis of the quarterly financial ratios reveals several notable trends and fluctuations across the observed periods.

Inventory Turnover
The inventory turnover ratio exhibited variability, with a significant peak at the end of 2018 reaching 13.61, indicating a faster rate of inventory being sold or used. Subsequently, the ratio moderated and fluctuated mostly between 9 and 11, with an upward trend toward 11.58 by the end of 2021, before settling at 10.2 in early 2022. This suggests periods of both efficient inventory management and slower turnover cycles at times.
Receivables Turnover
The receivables turnover ratio remained relatively stable, generally ranging between 10.5 and 12.5. It showed a slight improvement up to the end of 2019, peaking at 12.46 by mid-2020, indicating enhanced efficiency in collecting receivables during that period. However, it experienced some decline toward early 2022, reaching 10.67, reflecting a modest lengthening of the collection period.
Payables Turnover
Payables turnover fluctuated within a narrow range from approximately 1.85 to 2.28. Noteworthy is the gradual increase in early 2022, reaching 2.28, the highest value observed, which may indicate quicker payment to suppliers. Conversely, there were occasional dips, such as in late 2018 and parts of 2019, suggesting periodic delays or extended payment terms.
Working Capital Turnover
The data for working capital turnover is limited. However, available figures indicate considerable volatility, with a notably low value in mid-2020 (17.26) followed by a sharp increase toward the end of 2020 and a substantial peak at 181.54, implying significant fluctuations in operational efficiency and management of working capital during this period.
Average Inventory Processing Period
The average inventory processing period decreased sharply at the end of 2018 to 27 days, consistent with the peak in inventory turnover, indicating faster inventory handling. Subsequently, it generally hovered between 32 and 40 days, reflecting relatively stable inventory management with some fluctuations.
Average Receivable Collection Period
This period remained fairly consistent, mostly within the range of 29 to 35 days. A slight upward trend occurred around early 2021 (up to 35 days), but overall collection times remained stable throughout the analyzed timeline.
Operating Cycle
The operating cycle shortened significantly at the close of 2018 to 59 days, reflecting improved efficiency. Following that, it fluctuated around the mid-60s to low 70s in days, with periodic decreases and increases, indicative of variability in combined inventory turnover and receivable collection periods over time.
Average Payables Payment Period
This period decreased from near 195-197 days in early periods to a low of 160 days in early 2022. The general trend shows some shortening of the payment period over time, implying faster payment cycles to suppliers, which can affect cash flow.
Cash Conversion Cycle (CCC)
The cash conversion cycle remained negative throughout the timeline, ranging from approximately -90 to -136 days. A negative CCC suggests that the company receives payments from customers quicker than it pays its suppliers, effectively financing its operations with supplier credit. Notably, the CCC improved (became less negative) towards early 2022, reaching -90 days, indicating a relative tightening of the cash conversion process compared to prior periods when it reached as low as -136 days in late 2018.

Overall, the data reflects periods of operational efficiency interspersed with variability in inventory management, receivables collection, and payables payments. The consistent negative cash conversion cycle highlights strong supplier credit utilization. Notwithstanding fluctuations, key liquidity and operational efficiency ratios suggest the company maintained a generally effective working capital management approach, with some tightening of activities in the latest periods analyzed.


Turnover Ratios


Average No. Days


Inventory Turnover

Norfolk Southern Corp., inventory turnover calculation (quarterly data)

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

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.


The financial data reveals several notable trends over the analyzed periods. Cost of railway operating revenues exhibits fluctuations with a general downward trend starting from early 2020, reaching a trough mid-2020, and gradually increasing afterward. Materials and supplies costs display moderate variability, with a slight decline in the middle of 2020 followed by periods of relative stabilization and a modest rise toward early 2022. The inventory turnover ratio shows some volatility but generally maintains a range between approximately 9.0 and 13.6, peaking notably at the end of 2018 and exhibiting a gradual improvement in late 2021 and early 2022 compared to mid-2020.

Cost of Railway Operating Revenues
Initially stable with values around 670 to 720 million US dollars through 2018 and 2019, this cost lowers significantly during the first half of 2020, coinciding with a period that may reflect external market or operational impacts. A recovery trend emerges from the second half of 2020 onward, with costs increasing steadily and reaching the highest observed value in the first quarter of 2022.
Materials and Supplies
Spending on materials and supplies mirrors the broader cost trend but with less pronounced fluctuations. After a peak in late 2018, there is a gradual decrease mid-2020, followed by stabilization and minor variability across subsequent quarters. Costs edged up in early 2022, potentially indicating increased material usage or price increases.
Inventory Turnover Ratio
This ratio, representing the frequency of inventory replacement, shows a notable peak around the end of 2018, reaching over 13 times per period, suggesting efficient inventory management or higher sales volumes then. Thereafter, the ratio declines and stabilizes in the lower range of 9 to 10 through mid-2020. Improvement in turnover rates is observed later, with values surpassing 11 in late 2021 and early 2022, which may reflect operational efficiency gains or stronger revenue performance.

Overall, the data suggests a period of operational and cost challenges in early 2020, followed by a gradual recovery. Inventory management seems to have become more efficient toward the end of the period under review, as indicated by increasing turnover ratios. Cost components, after a dip, have risen again, possibly reflecting both demand recovery and inflationary pressures.


Receivables Turnover

Norfolk Southern Corp., receivables turnover calculation (quarterly data)

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

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.


Over the analyzed period, railway operating revenues exhibited a fluctuating yet generally resilient pattern. Starting around 2,717 million US dollars in the first quarter of 2018, revenues peaked near the end of 2018 before showing a notable decline through 2020, particularly in the second quarter coinciding with broader economic disruptions. However, from early 2021 onward, revenues demonstrated a recovery trend, stabilizing and slightly increasing, reaching 2,915 million US dollars by the first quarter of 2022, suggesting a progressive rebound in operational performance.

Accounts receivable, net, displayed a moderately variable trajectory without a consistent upward or downward trend. Initially at 973 million US dollars in early 2018, the figure saw periodic increases and decreases, with a general dip visible through 2020 tied likely to lower sales activity. By early 2022, the balance had risen to approximately 1,070 million US dollars, indicating an accumulation of receivables that may reflect increased sales volumes or changes in credit terms.

The receivables turnover ratio, which measures the efficiency in collecting receivables, showed subtle fluctuations throughout the timeline. Starting near 11, the ratio improved slightly through 2019, peaking above 12, implying faster collections during that period. During 2020, it remained relatively stable but declined somewhat by 2021 and early 2022, dropping closer to 10.7. This decline may point to slower collection processes or relaxed credit policies amid changing market conditions.

Summary of Key Trends:
Operating Revenues:
Experienced volatility with a marked drop during 2020 followed by a recovery in 2021-2022, nearing pre-2020 levels.
Accounts Receivable, Net:
Presented moderate variation with a gradual increase by early 2022, reflecting possible revenue recovery or alterations in credit management.
Receivables Turnover Ratio:
Fluctuated with a high point in 2019 but decreased in recent periods suggesting a potential slowdown in receivable collections.

Collectively, these indicators suggest that while the company faced challenges in revenue generation and collections during 2020, there are signs of operational recovery and adjustment in credit practices as of early 2022. Continued monitoring of accounts receivable and receivables turnover will be essential to ensure sustained liquidity and financial stability.


Payables Turnover

Norfolk Southern Corp., payables turnover calculation (quarterly data)

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

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.


Cost of Railway Operating Revenues
The cost of railway operating revenues exhibited fluctuations over the periods observed. From the first quarter of 2018 to the end of 2018, the cost remained relatively stable, oscillating around the range of 667 to 724 million USD. A modest decline was observed in early 2019, with values dropping to the mid-600s, followed by a slight increase towards the end of 2019. In 2020, a notable decrease occurred, reaching a low point of 456 million USD in the second quarter, which could be indicative of reduced operations or cost-saving initiatives during that period. However, from the third quarter of 2020 onwards, a recovery trend is evident, with the cost steadily increasing to reach 738 million USD by the first quarter of 2022, surpassing previous years’ levels.
Accounts Payable
The accounts payable balance demonstrated a general upward trajectory from early 2018 through to mid-2019, increasing from 1,217 million USD to 1,428 million USD by the last quarter of 2019. A declining trend began in 2020, particularly notable in the last quarter, coinciding with reduced accounts payable levels, potentially reflecting lowered procurement or expense deferrals during this period. However, from late 2020 through the first quarter of 2022, accounts payable rebounded gradually, reaching 1,351 million USD by early 2022, indicating restoration towards pre-2020 levels but with some quarters showing variability.
Payables Turnover Ratio
The payables turnover ratio generally fluctuated within a narrow range between approximately 1.84 and 2.28 over the span analyzed. Higher turnover ratios were recorded intermittently, such as peaks at 2.19 in the last quarter of 2020 and 2.28 in the first quarter of 2022, suggesting periods where payables were settled more rapidly. Conversely, lower values near 1.84 in the third quarter of 2020 indicate a slowdown in payables turnover. The ratio appears to have minor cyclical behavior without evidence of a sustained long-term trend, reflecting variability in payment policies or operational cash management across quarters.
Overall Insights
The data indicates a pattern where operating costs and accounts payable were relatively stable before the significant disruptions of 2020, followed by reductions likely linked to external factors impacting business activity. Recovery phases are visible in the latter part of 2020 and into 2021 and early 2022. The payables turnover ratio's fluctuations suggest adaptive management of payment terms or varying cash flow conditions across quarters. The increase in cost of railway operating revenues towards early 2022 points towards an expansion or rebound in operational activity.

Working Capital Turnover

Norfolk Southern Corp., working capital turnover calculation (quarterly data)

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

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 company's working capital exhibits significant fluctuations over the observed periods. Initially, working capital was positive but declined sharply through 2018 and into 2019, reaching considerable negative values. This downward trend suggests increasing current liabilities relative to current assets during that time. In 2020, there is a notable recovery, with working capital turning positive again mid-year, peaking at 574 million US dollars in the third quarter, followed by some volatility but remaining mostly positive until the end of 2021. However, in early 2022, the working capital drops back into negative territory, indicating a resurgence of liquidity pressure.

Railway operating revenues show a relatively stable pattern with minor seasonal fluctuations. Revenues generally hover around the 2800 million US dollars mark across many quarters. Notably, there is a decline in revenue during 2020, particularly in the second quarter, which aligns with broader economic disruptions likely impacting demand. After this dip, revenues gradually improve and return to levels similar to or slightly above those seen before the revenue decline. This recovery demonstrates resilience and steady demand in the company's operational activities.

The working capital turnover ratio, available for select periods, starts exceptionally high at 117.51 in the first quarter of 2018 but then data is absent for several quarters. When available again in 2020, the ratio is significantly lower, reflecting either an increase in working capital relative to sales or a decrease in revenues affecting turnover calculation. The ratio shows considerable variability, culminating in a peak of 181.54 in the fourth quarter of 2020, followed by a decline. Such volatility suggests periodic changes in the efficiency with which working capital is deployed to generate revenue, potentially influenced by the underlying fluctuations in working capital and revenue levels observed during this time.


Average Inventory Processing Period

Norfolk Southern Corp., average inventory processing period calculation (quarterly data)

Microsoft Excel
Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
Selected Financial Data
Inventory turnover
Short-term Activity Ratio (no. days)
Average inventory processing period1
Benchmarks (no. days)
Average Inventory Processing Period, Competitors2
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).

1 Q1 2022 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =

2 Click competitor name to see calculations.


Inventory Turnover
The inventory turnover ratio exhibited fluctuations throughout the period analyzed. Initially, it was around 9.5 in early 2018, followed by a notable increase to a peak of 13.61 by the end of 2018, indicating a faster rate of inventory turnover during that quarter. However, from 2019 onwards, the ratio generally declined, staying mostly between 9 and 11, with some quarterly variations. By March 2022, the ratio stood at 10.2, which suggests a moderate inventory turnover frequency comparable to earlier periods but below the peak experienced in late 2018.
Average Inventory Processing Period
The average inventory processing period, representing the number of days inventory remains before being sold or used, demonstrated an inverse trend to the inventory turnover ratio, as expected. Early 2018 values hovered around 37 to 39 days, and this period shortened significantly to 27 days by the end of 2018, corresponding with the peak in turnover. Subsequently, there was an increase to about 33-40 days during 2019 and 2020, indicating slower inventory processing. Most recently, from 2021 through the first quarter of 2022, this period fluctuated between 32 and 40 days, suggesting some improvement in inventory management speed relative to the previous two years but still longer than the lowest point in late 2018.
Overall Trends and Insights
There is a noticeable inverse relationship between inventory turnover and the average inventory processing period, consistent with standard inventory management principles. The peak turnover and corresponding minimal processing period at the end of 2018 indicate a period of efficient inventory management or increased sales velocity. The subsequent decline in turnover and increase in processing days during 2019 and 2020 could reflect changes in demand, supply chain adjustments, or strategic shifts in inventory policy. The recent data from 2021 and early 2022 suggest a partial recovery in efficiency but not to the levels seen at the end of 2018.

Average Receivable Collection Period

Norfolk Southern Corp., average receivable collection period calculation (quarterly data)

Microsoft Excel
Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
Selected Financial Data
Receivables turnover
Short-term Activity Ratio (no. days)
Average receivable collection period1
Benchmarks (no. days)
Average Receivable Collection Period, Competitors2
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).

1 Q1 2022 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =

2 Click competitor name to see calculations.


Receivables Turnover Ratio
The receivables turnover ratio exhibited a generally increasing trend from early 2018 through the end of 2019, moving from approximately 11.0 to a peak of 12.28. This indicates an improvement in the efficiency of collecting receivables during this period. In early 2020, the ratio reached its highest points around 12.46 but then experienced a decline through the remainder of 2020. The ratio fluctuated moderately throughout 2021, hovering between 10.38 and 11.50, and then declined to about 10.67 by the first quarter of 2022. Overall, the pattern suggests a peak in receivables management efficiency before 2020, followed by some weakening in subsequent quarters.
Average Receivable Collection Period (Days)
The average collection period inversely mirrored the trends observed in receivables turnover. From early 2018 to the end of 2019, the collection period shortened from 33 days to around 30 days, reflecting faster collection of receivables and improved liquidity. During 2020, the collection period briefly stabilized near 29 to 33 days, then increased slightly in early 2021 reaching 35 days, suggesting a temporary slowdown in collection efficiency. In the later quarters of 2021 and into early 2022, the collection period averaged about 32 to 34 days, indicating a modest return to longer collection times relative to the pre-2020 period.
Overall Analysis
The company demonstrated enhanced receivables management from 2018 through 2019, achieving quicker collections and higher turnover ratios. However, starting in 2020, there was a discernible reversal with turnover ratios declining and collection periods gradually lengthening, which could suggest emerging challenges in credit management or changes in customer payment behavior. The fluctuations in 2021 might indicate adjustments or responses to external economic conditions. Additional monitoring would be advisable to assess if these trends continue or stabilize in subsequent periods.

Operating Cycle

Norfolk Southern Corp., operating cycle calculation (quarterly data)

No. days

Microsoft Excel
Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019 Dec 31, 2018 Sep 30, 2018 Jun 30, 2018 Mar 31, 2018
Selected Financial Data
Average inventory processing period
Average receivable collection period
Short-term Activity Ratio
Operating cycle1
Benchmarks
Operating Cycle, Competitors2
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).

1 Q1 2022 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= + =

2 Click competitor name to see calculations.


Average Inventory Processing Period
The average inventory processing period exhibited some variability over the analyzed quarters. Initially, it remained relatively stable around the high 30-day range in early 2018, then showed a marked decrease towards the end of 2018, reaching a low of 27 days. In 2019, the period fluctuated moderately between 29 and 36 days. The year 2020 saw a return to higher values, peaking at 39 days in mid-year, followed by a gradual decline by the end of 2021. The first quarter of 2022 indicated a slight increase again to 36 days. Overall, the inventory processing period demonstrates cyclical patterns without a clear long-term upward or downward trend.
Average Receivable Collection Period
The average receivable collection period remained fairly consistent throughout the observed timeframe, generally oscillating between 29 and 35 days. Early 2018 and mid-2019 periods were near the lower bound of this range, around 29-31 days. Occasional crests occurred, such as during the first quarter of 2021 when the period reached 35 days. The data indicates stable receivables management with minor fluctuations but no significant trend towards lengthening or shortening collection times.
Operating Cycle
The operating cycle, which integrates inventory processing and receivable collection periods, displayed notable fluctuations across quarters. It initially ranged around 70-73 days in early 2018 before a substantial drop to 59 days at the end of 2018. During 2019, it hovered in the low to mid-60s. In 2020, the operating cycle increased again, peaking around 71 days before decreasing toward the end of 2021. The first quarter of 2022 saw the operating cycle rise slightly to 70 days. These variations reflect the combined effect of changes in inventory and receivables periods, indicating intermittent shifts in the efficiency of working capital management but no consistent linear trend over time.

Average Payables Payment Period

Norfolk Southern Corp., average payables payment period calculation (quarterly data)

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

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 demonstrates moderate fluctuations between 2018 and the first quarter of 2022. Initially, the ratio ranged from 1.85 to 1.92 in 2018, indicating a relatively stable ability to pay suppliers. In 2019, the ratio showed a slight increase, peaking at 2.12 in the first quarter, followed by a gradual decline toward the end of the year. During 2020, the ratio remained somewhat volatile, fluctuating between 1.84 and 2.19, with the highest value in the fourth quarter. Subsequently, the ratio persisted in a narrow range around 2.0 in 2021, ending with a slight decrease. Notably, in the first quarter of 2022, it reached its highest level in the given series at 2.28, reflecting potentially improved efficiency or quicker payment to suppliers during that period.
Average Payables Payment Period (Days)
The average payables payment period exhibits an inverse movement compared to the payables turnover ratio, ranging broadly between 160 and 198 days over the analyzed timeframe. In 2018, the company generally took around 195 to 197 days to pay suppliers, with a slight decline evident in the first quarters of 2019 (172 days) and again in early 2021 (167 days). This indicates periods of accelerated payment cycles. Conversely, several quarters, particularly in mid to late 2019 and 2020, saw longer payment periods nearing or surpassing 190 days, suggesting a slower payment pace during those times. The first quarter of 2022 recorded the shortest payment period of 160 days in the dataset, corroborating the observed increase in payables turnover ratio, and suggesting improved liquidity management or favorable supplier terms.
Overall Trends and Insights
The data suggest a cyclical pattern in both payables turnover and payment period, with periods of quicker payments alternating with stretched payment durations. The inverse correlation between the two metrics is consistent with financial principles, as a higher turnover ratio corresponds with a shorter payment period and vice versa. The notable improvement in early 2022, illustrated by the highest payables turnover ratio and the shortest payment days, might indicate a strategic focus on optimizing payables management, potentially enhancing supplier relations or cash flow positioning. Throughout the timeline, there is no extreme volatility, reflecting relatively stable yet adaptative accounts payable practices within the company.

Cash Conversion Cycle

Norfolk Southern Corp., cash conversion cycle calculation (quarterly data)

No. days

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

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 quarterly financial data reveals several noteworthy trends in inventory management, receivables, payables, and overall cash conversion efficiency over the observed period.

Average Inventory Processing Period
The average inventory processing period shows moderate fluctuations ranging between 27 and 40 days. It generally decreased from 38 days in early 2018 to a low of 27 days by the end of 2018, indicating improved inventory turnover efficiency during that period. Starting in 2019, the period varied somewhat, trending upward again to around 40 days in early 2021, before declining to 32–36 days by the first quarter of 2022. This suggests some variability in inventory management, with a trend towards faster processing in the most recent quarters.
Average Receivable Collection Period
The average receivable collection period has remained relatively stable over time, consistently oscillating between 29 and 35 days. Minor decreases were seen in 2020, with the period dropping to 29 days mid-year, followed by a slight increase in 2021 and early 2022 back to the mid-30-day range. Overall, the company maintained steady efficiency in collecting receivables throughout the period, with no significant deterioration or improvement.
Average Payables Payment Period
The payables payment period exhibits a more pronounced downward trend over time. Starting from a high range around 190–197 days in 2018, the period decreased notably to a low of 160 days by March 2022. This indicates that the company has been progressively shortening its payment cycle to suppliers. However, some quarterly variability is evident, with occasional increases such as the 195 days observed in late 2021. This shortening of payment periods may reflect changes in credit terms or a strategic move to improve supplier relationships.
Cash Conversion Cycle
The cash conversion cycle, consistently negative throughout the timeline, presents fluctuations between approximately -90 and -136 days. The deepest negatives occurred in late 2018 and 2019, indicating that the company was receiving cash much faster than it needed to pay its suppliers, effectively benefiting from supplier credit. Although the cash conversion cycle rose closer to -90 days in early 2022, signifying a slight reduction in this advantage, it remained substantially negative, pointing to an efficient working capital management strategy that minimizes the cash tied up in operations.

In summary, the company demonstrates stable receivable collection efficiency, some variability but generally improved inventory processing times, a clear trend towards faster payment to suppliers, and consistently negative cash conversion cycles indicative of strong cash flow management. These factors combined suggest a balanced approach to managing operational liquidity over the observed period.