Stock Analysis on Net

Ross Stores Inc. (NASDAQ:ROST)

$22.49

This company has been moved to the archive! The financial data has not been updated since December 7, 2022.

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

Microsoft Excel

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Short-term Activity Ratios (Summary)

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

Microsoft Excel
Oct 29, 2022 Jul 30, 2022 Apr 30, 2022 Jan 29, 2022 Oct 30, 2021 Jul 31, 2021 May 1, 2021 Jan 30, 2021 Oct 31, 2020 Aug 1, 2020 May 2, 2020 Feb 1, 2020 Nov 2, 2019 Aug 3, 2019 May 4, 2019 Feb 2, 2019 Nov 3, 2018 Aug 4, 2018 May 5, 2018 Feb 3, 2018 Oct 28, 2017 Jul 29, 2017 Apr 29, 2017 Jan 28, 2017 Oct 29, 2016 Jul 30, 2016 Apr 30, 2016
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: 2022-10-29), 10-Q (reporting date: 2022-07-30), 10-Q (reporting date: 2022-04-30), 10-K (reporting date: 2022-01-29), 10-Q (reporting date: 2021-10-30), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-05-01), 10-K (reporting date: 2021-01-30), 10-Q (reporting date: 2020-10-31), 10-Q (reporting date: 2020-08-01), 10-Q (reporting date: 2020-05-02), 10-K (reporting date: 2020-02-01), 10-Q (reporting date: 2019-11-02), 10-Q (reporting date: 2019-08-03), 10-Q (reporting date: 2019-05-04), 10-K (reporting date: 2019-02-02), 10-Q (reporting date: 2018-11-03), 10-Q (reporting date: 2018-08-04), 10-Q (reporting date: 2018-05-05), 10-K (reporting date: 2018-02-03), 10-Q (reporting date: 2017-10-28), 10-Q (reporting date: 2017-07-29), 10-Q (reporting date: 2017-04-29), 10-K (reporting date: 2017-01-28), 10-Q (reporting date: 2016-10-29), 10-Q (reporting date: 2016-07-30), 10-Q (reporting date: 2016-04-30).


The analysis of the company's quarterly financial ratios and related periods reveals several noteworthy trends and fluctuations across the reported intervals.

Inventory Turnover
This ratio demonstrates moderate fluctuation with values generally ranging between approximately 5.0 and 8.9. Notably, there is a peak around the August 2020 period reaching 8.91, indicating an accelerated rotation of inventory during that time. Subsequent values return closer to the 5.0 to 6.5 range, suggesting some stabilization after the spike.
Receivables Turnover
The receivables turnover ratio exhibits significant variability. It sharply increases to an exceptional high of 283.84 in February 2019, which may reflect improved collection efficiency or a timing anomaly. Prior to and following this peak, the ratio hovers mostly between 90 and 160, with some dips below 100 observed in later periods, indicating fluctuating efficiency in collecting receivables.
Payables Turnover
Values for payables turnover generally fluctuate between 4.0 and 9.5, with a pronounced spike to 15.18 in February 2019. Following this peak, turnover declines notably, reaching lows around 4.0 in late 2020 and early 2021, indicating slower payment to suppliers during that period. The trend slightly recovers towards the end of the dataset, stabilizing around values of 6.0 to 7.0.
Working Capital Turnover
Working capital turnover shows a considerable increase starting around May 2019, reaching a high above 21 in November 2019 and February 2020. This increase suggests more efficient use of working capital in generating sales during that time frame. However, from May 2020 onwards, the turnover falls significantly to below 6 by mid-2021 and remains relatively stable but low through late 2022, indicating a reduced turnover effectiveness post early 2020.
Average Inventory Processing Period
This period mostly fluctuates between about 56 and 72 days, with occasional dips to 41 days in May 2020 and a notable rise to over 70 days during 2017 and late 2022. These shifts imply varying speeds in inventory turnover, with a marked inventory acceleration observed in mid-2020.
Average Receivable Collection Period
Receivable collection days remain consistently low and relatively stable at 2 to 3 days throughout the entire period, occasionally reaching 5 days in February 2019. This indicates a strong and consistent collections process.
Operating Cycle
The operating cycle length tends to oscillate mostly between 59 and 75 days, with an outlier low of 46 days in May 2020. Periods of increase coincide with higher inventory days, showing some sensitivity to inventory management practices.
Average Payables Payment Period
The average payables payment period reveals considerable volatility. It peaks sharply at 89 days in February 2019, then retraces downward to as low as 24 days in May 2020. Following this trough, payment periods lengthen again but remain generally below earlier highs, suggesting a shift toward quicker supplier payments in mid-2020 before easing back somewhat.
Cash Conversion Cycle
The cash conversion cycle fluctuates significantly, ranging from a high of 37 days in May 2020 to negative values around -25 days in August and October 2020, indicating periods where supplier payments are made after cash is collected from customers, effectively using supplier credit to finance operations. Post-2020, the cycle rises back into positive territory, stabilizing around 16 to 19 days towards late 2022.

Overall, the data suggests episodic improvements in operational efficiency, particularly around early 2019 and mid-2020, evidenced by spikes in turnover ratios and reductions in days for inventory and payables. However, these improvements are followed by reversion towards longer periods and lower turnover ratios in subsequent quarters. Noteworthy is the negative cash conversion cycle during late 2020, reflecting optimized working capital management at that time. The consistent low receivables collection period across all quarters demonstrates an effective receivables process throughout the timeframe.


Turnover Ratios


Average No. Days


Inventory Turnover

Ross Stores Inc., inventory turnover calculation (quarterly data)

Microsoft Excel
Oct 29, 2022 Jul 30, 2022 Apr 30, 2022 Jan 29, 2022 Oct 30, 2021 Jul 31, 2021 May 1, 2021 Jan 30, 2021 Oct 31, 2020 Aug 1, 2020 May 2, 2020 Feb 1, 2020 Nov 2, 2019 Aug 3, 2019 May 4, 2019 Feb 2, 2019 Nov 3, 2018 Aug 4, 2018 May 5, 2018 Feb 3, 2018 Oct 28, 2017 Jul 29, 2017 Apr 29, 2017 Jan 28, 2017 Oct 29, 2016 Jul 30, 2016 Apr 30, 2016
Selected Financial Data (US$ in thousands)
Cost of goods sold
Merchandise inventory
Short-term Activity Ratio
Inventory turnover1
Benchmarks
Inventory Turnover, Competitors2
Amazon.com Inc.
Home Depot Inc.
Lowe’s Cos. Inc.
TJX Cos. Inc.

Based on: 10-Q (reporting date: 2022-10-29), 10-Q (reporting date: 2022-07-30), 10-Q (reporting date: 2022-04-30), 10-K (reporting date: 2022-01-29), 10-Q (reporting date: 2021-10-30), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-05-01), 10-K (reporting date: 2021-01-30), 10-Q (reporting date: 2020-10-31), 10-Q (reporting date: 2020-08-01), 10-Q (reporting date: 2020-05-02), 10-K (reporting date: 2020-02-01), 10-Q (reporting date: 2019-11-02), 10-Q (reporting date: 2019-08-03), 10-Q (reporting date: 2019-05-04), 10-K (reporting date: 2019-02-02), 10-Q (reporting date: 2018-11-03), 10-Q (reporting date: 2018-08-04), 10-Q (reporting date: 2018-05-05), 10-K (reporting date: 2018-02-03), 10-Q (reporting date: 2017-10-28), 10-Q (reporting date: 2017-07-29), 10-Q (reporting date: 2017-04-29), 10-K (reporting date: 2017-01-28), 10-Q (reporting date: 2016-10-29), 10-Q (reporting date: 2016-07-30), 10-Q (reporting date: 2016-04-30).

1 Q3 2023 Calculation
Inventory turnover = (Cost of goods soldQ3 2023 + Cost of goods soldQ2 2023 + Cost of goods soldQ1 2023 + Cost of goods soldQ4 2022) ÷ Merchandise inventory
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


Cost of Goods Sold
The cost of goods sold (COGS) demonstrates a general pattern of fluctuation with periods of increase and decrease over the time frame analyzed. Initial quarters show COGS around 2,176,205 to 2,535,563 thousand USD, with noticeable rises occurring in January 2017 and continuing through early 2018. A significant peak is evident in February 2018 at approximately 2,982,744 thousand USD. Following this, there is variability but an overall upward trend observed through to the end of 2019. In early 2020, a sharp decline is apparent, coinciding with a decrease to 1,889,991 thousand USD in May 2020, likely reflecting external impacts affecting operations. Afterwards, COGS increases again, reaching above 3,700,000 thousand USD by early 2022, signaling recovery and growth in cost levels associated with sales.
Merchandise Inventory
Merchandise inventory values exhibit variability with a general rising trend over the observed period, fluctuating between approximately 1,498,449 and 2,718,878 thousand USD. Inventory levels peak in November 2019 at close to 2,168,796 thousand USD, after which there is a gradual decline into mid-2020, bottoming out near 1,117,983 thousand USD, which aligns temporally with the reduction in COGS. From mid-2020 onwards, inventory levels increase consistently, reaching new highs toward the end of the data range in late 2022, which could indicate strategic stocking or preparation for anticipated demand increases.
Inventory Turnover
Inventory turnover ratios are mostly available from 2017 onwards and show moderate fluctuation. Values generally range from about 5.04 to 8.91 times per period. A notable spike occurs in August 2020, with a turnover of approximately 8.91, indicating a significantly faster rate of inventory liquidation at that time. Before and after this peak, turnover fluctuates between roughly 5 and 7, suggesting typical cyclical variations in inventory management efficiency. A declining trend is observable toward late 2022, signaling somewhat reduced efficiency in inventory movement relative to prior periods.
Summary of Trends
Overall, the data reveal cyclical sales and inventory dynamics with impacts likely related to macroeconomic conditions seen in early 2020. The sharp decline in both COGS and inventory during this period suggests an operational slowdown or reduced demand. Post-2020 trends show recovery with increasing inventory stocks and rising cost of goods sold, indicating resumed operations and growing sales. Inventory turnover ratios maintain typical range variations but highlight periods of notably improved inventory management efficiency, with a pronounced peak mid-2020 likely reflecting adaptive responses in business operations.

Receivables Turnover

Ross Stores Inc., receivables turnover calculation (quarterly data)

Microsoft Excel
Oct 29, 2022 Jul 30, 2022 Apr 30, 2022 Jan 29, 2022 Oct 30, 2021 Jul 31, 2021 May 1, 2021 Jan 30, 2021 Oct 31, 2020 Aug 1, 2020 May 2, 2020 Feb 1, 2020 Nov 2, 2019 Aug 3, 2019 May 4, 2019 Feb 2, 2019 Nov 3, 2018 Aug 4, 2018 May 5, 2018 Feb 3, 2018 Oct 28, 2017 Jul 29, 2017 Apr 29, 2017 Jan 28, 2017 Oct 29, 2016 Jul 30, 2016 Apr 30, 2016
Selected Financial Data (US$ in thousands)
Sales
Accounts receivable
Short-term Activity Ratio
Receivables turnover1
Benchmarks
Receivables Turnover, Competitors2
Home Depot Inc.
TJX Cos. Inc.

Based on: 10-Q (reporting date: 2022-10-29), 10-Q (reporting date: 2022-07-30), 10-Q (reporting date: 2022-04-30), 10-K (reporting date: 2022-01-29), 10-Q (reporting date: 2021-10-30), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-05-01), 10-K (reporting date: 2021-01-30), 10-Q (reporting date: 2020-10-31), 10-Q (reporting date: 2020-08-01), 10-Q (reporting date: 2020-05-02), 10-K (reporting date: 2020-02-01), 10-Q (reporting date: 2019-11-02), 10-Q (reporting date: 2019-08-03), 10-Q (reporting date: 2019-05-04), 10-K (reporting date: 2019-02-02), 10-Q (reporting date: 2018-11-03), 10-Q (reporting date: 2018-08-04), 10-Q (reporting date: 2018-05-05), 10-K (reporting date: 2018-02-03), 10-Q (reporting date: 2017-10-28), 10-Q (reporting date: 2017-07-29), 10-Q (reporting date: 2017-04-29), 10-K (reporting date: 2017-01-28), 10-Q (reporting date: 2016-10-29), 10-Q (reporting date: 2016-07-30), 10-Q (reporting date: 2016-04-30).

1 Q3 2023 Calculation
Receivables turnover = (SalesQ3 2023 + SalesQ2 2023 + SalesQ1 2023 + SalesQ4 2022) ÷ Accounts receivable
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The quarterly financial data reveals several trends in the sales, accounts receivable, and receivables turnover ratios over the periods analyzed.

Sales
Sales figures demonstrate a generally upward trend from April 2016 through early 2020, with periodic fluctuations. The sales increased from approximately 3,088,995 thousand USD in April 2016 to a peak of about 4,413,445 thousand USD by February 2020. However, a sharp decline is observed in May 2020, where sales dropped substantially to 1,842,673 thousand USD, likely reflecting extraordinary circumstances impacting revenue. Following this decline, the sales recovered progressively through subsequent quarters, reaching approximately 5,020,649 thousand USD by January 2022. This recovery suggests resilience and potential growth after the downturn.
Accounts Receivable
Accounts receivable values show some volatility but generally move within a range, without a clear long-term upward or downward trend. Initial values in 2016 are around 96,244 to 103,071 thousand USD, with increases and decreases in subsequent quarters. Notably, there is a significant dip in May 2020 to 49,624 thousand USD, aligning with the concurrent sharp drop in sales during the same period. Following this, accounts receivable increase again, reaching values around 164,071 to 168,483 thousand USD by late 2022. This trend indicates fluctuations in credit extended to customers or collection cycles, which may be influenced by sales volumes and external factors during the downturn period.
Receivables Turnover Ratio
The receivables turnover ratio, indicative of how efficiently the company collects its receivables, shows considerable variation across the quarters. Early ratios in 2017 range between approximately 118 to 171, implying relatively frequent collection cycles. A notable peak occurs in February 2020, with a ratio of approximately 283.84, indicating very rapid collection during that period. Conversely, May 2020 shows a sharp decrease to 78.6, reflecting slower collection or challenges in receivables turnover coinciding with the decreased sales and accounts receivable. Post-May 2020, the turnover ratio recovers and stabilizes in the range of 90 to 158, suggesting normalization in collection efficiency as sales rebound.

Overall, the data shows that the company experienced strong sales growth through early 2020, followed by a significant disruption resulting in reduced sales and corresponding impacts on receivables and turnover. Subsequent periods demonstrate recovery with gradual improvement in all three metrics, highlighting adaptive management of credit and collections alongside sales recovery.


Payables Turnover

Ross Stores Inc., payables turnover calculation (quarterly data)

Microsoft Excel
Oct 29, 2022 Jul 30, 2022 Apr 30, 2022 Jan 29, 2022 Oct 30, 2021 Jul 31, 2021 May 1, 2021 Jan 30, 2021 Oct 31, 2020 Aug 1, 2020 May 2, 2020 Feb 1, 2020 Nov 2, 2019 Aug 3, 2019 May 4, 2019 Feb 2, 2019 Nov 3, 2018 Aug 4, 2018 May 5, 2018 Feb 3, 2018 Oct 28, 2017 Jul 29, 2017 Apr 29, 2017 Jan 28, 2017 Oct 29, 2016 Jul 30, 2016 Apr 30, 2016
Selected Financial Data (US$ in thousands)
Cost of goods sold
Accounts payable
Short-term Activity Ratio
Payables turnover1
Benchmarks
Payables Turnover, Competitors2
Amazon.com Inc.
Home Depot Inc.
Lowe’s Cos. Inc.
TJX Cos. Inc.

Based on: 10-Q (reporting date: 2022-10-29), 10-Q (reporting date: 2022-07-30), 10-Q (reporting date: 2022-04-30), 10-K (reporting date: 2022-01-29), 10-Q (reporting date: 2021-10-30), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-05-01), 10-K (reporting date: 2021-01-30), 10-Q (reporting date: 2020-10-31), 10-Q (reporting date: 2020-08-01), 10-Q (reporting date: 2020-05-02), 10-K (reporting date: 2020-02-01), 10-Q (reporting date: 2019-11-02), 10-Q (reporting date: 2019-08-03), 10-Q (reporting date: 2019-05-04), 10-K (reporting date: 2019-02-02), 10-Q (reporting date: 2018-11-03), 10-Q (reporting date: 2018-08-04), 10-Q (reporting date: 2018-05-05), 10-K (reporting date: 2018-02-03), 10-Q (reporting date: 2017-10-28), 10-Q (reporting date: 2017-07-29), 10-Q (reporting date: 2017-04-29), 10-K (reporting date: 2017-01-28), 10-Q (reporting date: 2016-10-29), 10-Q (reporting date: 2016-07-30), 10-Q (reporting date: 2016-04-30).

1 Q3 2023 Calculation
Payables turnover = (Cost of goods soldQ3 2023 + Cost of goods soldQ2 2023 + Cost of goods soldQ1 2023 + Cost of goods soldQ4 2022) ÷ Accounts payable
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The data reveals several noteworthy trends in the financial performance and operational efficiency metrics over the observed period.

Cost of Goods Sold (COGS)
The COGS exhibits a general upward trajectory from 2016 through early 2022, indicating increased expenses related to product sales. Periodic fluctuations are apparent, with peaks typically occurring in the first quarter of each year and troughs mid-year. A significant decrease is seen around May and August 2020, likely reflecting an unusual market or operational event, followed by a recovery and renewed upward trend through late 2022.
Accounts Payable
Accounts payable figures demonstrate considerable volatility over the timeline. Initial values for 2016 to early 2017 are relatively stable with moderate increases, reaching a peak in late 2019. A sharp decline is observed starting in May 2020, correlating with a large drop in payable balances, which may signify changes in supplier payment terms or liquidity management. Subsequent months show a gradual rebound, although levels remain below previous peaks through late 2022.
Payables Turnover Ratio
The payables turnover ratio indicates a pronounced downward trend beginning in early 2019, with values diminishing from around 9 to a low near 4 in early 2021, suggesting slower payment to suppliers or extended credit terms during that period. From mid-2021 onward, the ratio begins to increase gradually, rising to over 7 by late 2022, implying a return to more rapid payments or reduced credit period from suppliers. Notably, the ratio experiences a spike to over 15 in mid-2020 amid the pandemic timeframe, which could reflect exceptional operational measures or data anomalies.

Collectively, these patterns suggest operational adjustments in inventory management and credit management policies during the analyzed timeframe, influenced by external factors such as market conditions and potential disruptions. The marked changes in payables turnover and accounts payable balances particularly reflect shifts in supplier payment strategies and cash flow management.


Working Capital Turnover

Ross Stores Inc., working capital turnover calculation (quarterly data)

Microsoft Excel
Oct 29, 2022 Jul 30, 2022 Apr 30, 2022 Jan 29, 2022 Oct 30, 2021 Jul 31, 2021 May 1, 2021 Jan 30, 2021 Oct 31, 2020 Aug 1, 2020 May 2, 2020 Feb 1, 2020 Nov 2, 2019 Aug 3, 2019 May 4, 2019 Feb 2, 2019 Nov 3, 2018 Aug 4, 2018 May 5, 2018 Feb 3, 2018 Oct 28, 2017 Jul 29, 2017 Apr 29, 2017 Jan 28, 2017 Oct 29, 2016 Jul 30, 2016 Apr 30, 2016
Selected Financial Data (US$ in thousands)
Current assets
Less: Current liabilities
Working capital
 
Sales
Short-term Activity Ratio
Working capital turnover1
Benchmarks
Working Capital Turnover, Competitors2
Amazon.com Inc.
Home Depot Inc.
Lowe’s Cos. Inc.
TJX Cos. Inc.

Based on: 10-Q (reporting date: 2022-10-29), 10-Q (reporting date: 2022-07-30), 10-Q (reporting date: 2022-04-30), 10-K (reporting date: 2022-01-29), 10-Q (reporting date: 2021-10-30), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-05-01), 10-K (reporting date: 2021-01-30), 10-Q (reporting date: 2020-10-31), 10-Q (reporting date: 2020-08-01), 10-Q (reporting date: 2020-05-02), 10-K (reporting date: 2020-02-01), 10-Q (reporting date: 2019-11-02), 10-Q (reporting date: 2019-08-03), 10-Q (reporting date: 2019-05-04), 10-K (reporting date: 2019-02-02), 10-Q (reporting date: 2018-11-03), 10-Q (reporting date: 2018-08-04), 10-Q (reporting date: 2018-05-05), 10-K (reporting date: 2018-02-03), 10-Q (reporting date: 2017-10-28), 10-Q (reporting date: 2017-07-29), 10-Q (reporting date: 2017-04-29), 10-K (reporting date: 2017-01-28), 10-Q (reporting date: 2016-10-29), 10-Q (reporting date: 2016-07-30), 10-Q (reporting date: 2016-04-30).

1 Q3 2023 Calculation
Working capital turnover = (SalesQ3 2023 + SalesQ2 2023 + SalesQ1 2023 + SalesQ4 2022) ÷ Working capital
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The financial data reveals several notable trends through the observed periods. Working capital generally increases over time, with a significant rise from early 2020 onward, reaching its peak values around 2021. This increase suggests improved liquidity and possibly increased operational efficiency or changes in asset and liability management.

Sales exhibit a generally increasing trend over the same span, with some fluctuations. There are visible spikes in sales around early 2018, early 2020, and continuing into 2021, indicating periods of enhanced revenue generation. The drop in sales in the early months of 2020 coincides with a global economic downturn, yet subsequent quarters demonstrate recovery and strong growth.

The working capital turnover ratio, which measures the efficiency of generating sales from working capital, shows variability over time. Early data around 2016 and 2017 indicate relatively high turnover ratios (above 10), pointing to strong efficiency. However, from 2020 onward, the ratio declines sharply to values near 5, reflecting a decrease in how effectively the company is using its working capital to support sales. This trend, combined with the significant growth in working capital, may imply that the company has been investing more in current assets or facing increased current liabilities without proportional sales growth.

Working Capital
There is a steady upward trajectory in working capital from 2016 to early 2020, with values more than doubling by mid-2020 and maintaining high levels through 2022.
Sales
Sales increased over the full period with periodic spikes and some dips, notably a decline in early 2020 followed by strong recovery and record levels in 2021.
Working Capital Turnover
The ratio declines markedly after 2019, suggesting a reduction in working capital efficiency, despite increased absolute sales and working capital. Early periods show turnover above 10, while post-2020 figures hover near 5.

In summary, the data indicates a company experiencing growth in both liquidity and sales but encountering decreasing returns on working capital utilization since 2020. This could reflect strategic decisions to hold more current assets or challenges in converting working capital efficiently into revenue during periods affected by economic changes.


Average Inventory Processing Period

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

Microsoft Excel
Oct 29, 2022 Jul 30, 2022 Apr 30, 2022 Jan 29, 2022 Oct 30, 2021 Jul 31, 2021 May 1, 2021 Jan 30, 2021 Oct 31, 2020 Aug 1, 2020 May 2, 2020 Feb 1, 2020 Nov 2, 2019 Aug 3, 2019 May 4, 2019 Feb 2, 2019 Nov 3, 2018 Aug 4, 2018 May 5, 2018 Feb 3, 2018 Oct 28, 2017 Jul 29, 2017 Apr 29, 2017 Jan 28, 2017 Oct 29, 2016 Jul 30, 2016 Apr 30, 2016
Selected Financial Data
Inventory turnover
Short-term Activity Ratio (no. days)
Average inventory processing period1
Benchmarks (no. days)
Average Inventory Processing Period, Competitors2
Amazon.com Inc.
Home Depot Inc.
Lowe’s Cos. Inc.
TJX Cos. Inc.

Based on: 10-Q (reporting date: 2022-10-29), 10-Q (reporting date: 2022-07-30), 10-Q (reporting date: 2022-04-30), 10-K (reporting date: 2022-01-29), 10-Q (reporting date: 2021-10-30), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-05-01), 10-K (reporting date: 2021-01-30), 10-Q (reporting date: 2020-10-31), 10-Q (reporting date: 2020-08-01), 10-Q (reporting date: 2020-05-02), 10-K (reporting date: 2020-02-01), 10-Q (reporting date: 2019-11-02), 10-Q (reporting date: 2019-08-03), 10-Q (reporting date: 2019-05-04), 10-K (reporting date: 2019-02-02), 10-Q (reporting date: 2018-11-03), 10-Q (reporting date: 2018-08-04), 10-Q (reporting date: 2018-05-05), 10-K (reporting date: 2018-02-03), 10-Q (reporting date: 2017-10-28), 10-Q (reporting date: 2017-07-29), 10-Q (reporting date: 2017-04-29), 10-K (reporting date: 2017-01-28), 10-Q (reporting date: 2016-10-29), 10-Q (reporting date: 2016-07-30), 10-Q (reporting date: 2016-04-30).

1 Q3 2023 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =

2 Click competitor name to see calculations.


The inventory turnover ratio exhibits fluctuation over the analyzed periods, beginning at 6.06 in April 2016 and showing a general pattern of ups and downs throughout the timeline. Noteworthy peaks include a significant increase to 8.91 during August 2020, followed by subsequent decreases to around 5.13 by July 2022. The ratio generally remains within a range between approximately 5.0 and 7.1 outside of the noted high, indicating varying efficiency in managing inventory relative to sales.

The average inventory processing period, measured in days, inversely correlates with the inventory turnover ratio, fluctuating notably between approximately 41 days and 72 days. The shortest processing period occurs around August 2020 with 41 days, corresponding to the peak in inventory turnover, suggesting a faster turnover of inventory during that time. Conversely, longer periods, such as 71 to 72 days noted between mid-2022, indicate slower inventory processing.

Inventory Turnover
Fluctuates between 5.0 and 7.1 typically, with a significant spike to 8.91 observed in August 2020.
This peak suggests a period of exceptionally efficient inventory movement.
Post-peak values trend downward but remain relatively stable around 5.0 to 6.0 thereafter.
Average Inventory Processing Period
Ranges from a low near 41 days to a high of approximately 72 days.
The lowest value coincides with the highest turnover ratio in August 2020, suggesting quicker inventory cycles.
Higher values later in the series indicate a slowing of inventory movement.

Overall, the data indicates periodic volatility in inventory management efficiency, with certain intervals reflecting improved operations marked by higher turnover and faster processing times. The peak in mid-2020 may reflect strategic changes or market conditions enhancing inventory flow. Subsequent periods show a reversion to moderate turnover levels and longer processing times, which may warrant further investigation into operational factors.


Average Receivable Collection Period

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

Microsoft Excel
Oct 29, 2022 Jul 30, 2022 Apr 30, 2022 Jan 29, 2022 Oct 30, 2021 Jul 31, 2021 May 1, 2021 Jan 30, 2021 Oct 31, 2020 Aug 1, 2020 May 2, 2020 Feb 1, 2020 Nov 2, 2019 Aug 3, 2019 May 4, 2019 Feb 2, 2019 Nov 3, 2018 Aug 4, 2018 May 5, 2018 Feb 3, 2018 Oct 28, 2017 Jul 29, 2017 Apr 29, 2017 Jan 28, 2017 Oct 29, 2016 Jul 30, 2016 Apr 30, 2016
Selected Financial Data
Receivables turnover
Short-term Activity Ratio (no. days)
Average receivable collection period1
Benchmarks (no. days)
Average Receivable Collection Period, Competitors2
Home Depot Inc.
TJX Cos. Inc.

Based on: 10-Q (reporting date: 2022-10-29), 10-Q (reporting date: 2022-07-30), 10-Q (reporting date: 2022-04-30), 10-K (reporting date: 2022-01-29), 10-Q (reporting date: 2021-10-30), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-05-01), 10-K (reporting date: 2021-01-30), 10-Q (reporting date: 2020-10-31), 10-Q (reporting date: 2020-08-01), 10-Q (reporting date: 2020-05-02), 10-K (reporting date: 2020-02-01), 10-Q (reporting date: 2019-11-02), 10-Q (reporting date: 2019-08-03), 10-Q (reporting date: 2019-05-04), 10-K (reporting date: 2019-02-02), 10-Q (reporting date: 2018-11-03), 10-Q (reporting date: 2018-08-04), 10-Q (reporting date: 2018-05-05), 10-K (reporting date: 2018-02-03), 10-Q (reporting date: 2017-10-28), 10-Q (reporting date: 2017-07-29), 10-Q (reporting date: 2017-04-29), 10-K (reporting date: 2017-01-28), 10-Q (reporting date: 2016-10-29), 10-Q (reporting date: 2016-07-30), 10-Q (reporting date: 2016-04-30).

1 Q3 2023 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =

2 Click competitor name to see calculations.


The analysis of the provided quarterly financial data reveals several noteworthy trends and fluctuations over the reported periods.

Receivables Turnover Ratio

The receivables turnover ratio exhibits significant volatility across the timeline. Starting from values not reported in the earliest quarters, it registers a marked fluctuation beginning in early 2017. Initial values range from approximately 118 to 171, indicating varying efficiencies in collecting receivables. A pronounced spike is observed in February 2020, reaching 283.84, which suggests an exceptionally rapid conversion of receivables during that quarter. However, immediately following this peak, the ratio sharply declines to a low of 78.6 by May 2020, indicating reduced collection efficiency or changes in credit policies amid that period.

Subsequent quarters demonstrate a recovery trend with moderate fluctuations, maintaining the ratio generally between 90 and 158. The data toward the end of the observed intervals depict stabilization around values slightly above 100, although it remains below the extreme peak experienced in early 2020.

Average Receivable Collection Period (Days)

The average receivable collection period in days largely inversely correlates with the receivables turnover ratio, as anticipated. For most quarters, the collection period remains consistently low, varying mainly between 2 and 3 days. This indicates efficient receivable collections throughout the majority of the periods.

Noteworthy deviations include a reduction to 1 day in the quarter corresponding to the peak turnover ratio in February 2020, reinforcing the observation of accelerated receivables collection. Conversely, there is an increase to 5 days in May 2020, concurrent with the significant drop in turnover ratio, signifying slower collections during that quarter.

Following these fluctuations, the average collection period returns to the 2-3 day range, suggesting a return to standard collection timelines in the subsequent quarters.

Overall, the data portrays a generally efficient receivables management process with short collection periods, punctuated by exceptional volatility around early 2020. The extremes in turnover ratio and collection days during this period likely reflect external factors impacting receivables processing, followed by a return toward established norms in later quarters.


Operating Cycle

Ross Stores Inc., operating cycle calculation (quarterly data)

No. days

Microsoft Excel
Oct 29, 2022 Jul 30, 2022 Apr 30, 2022 Jan 29, 2022 Oct 30, 2021 Jul 31, 2021 May 1, 2021 Jan 30, 2021 Oct 31, 2020 Aug 1, 2020 May 2, 2020 Feb 1, 2020 Nov 2, 2019 Aug 3, 2019 May 4, 2019 Feb 2, 2019 Nov 3, 2018 Aug 4, 2018 May 5, 2018 Feb 3, 2018 Oct 28, 2017 Jul 29, 2017 Apr 29, 2017 Jan 28, 2017 Oct 29, 2016 Jul 30, 2016 Apr 30, 2016
Selected Financial Data
Average inventory processing period
Average receivable collection period
Short-term Activity Ratio
Operating cycle1
Benchmarks
Operating Cycle, Competitors2
Home Depot Inc.
TJX Cos. Inc.

Based on: 10-Q (reporting date: 2022-10-29), 10-Q (reporting date: 2022-07-30), 10-Q (reporting date: 2022-04-30), 10-K (reporting date: 2022-01-29), 10-Q (reporting date: 2021-10-30), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-05-01), 10-K (reporting date: 2021-01-30), 10-Q (reporting date: 2020-10-31), 10-Q (reporting date: 2020-08-01), 10-Q (reporting date: 2020-05-02), 10-K (reporting date: 2020-02-01), 10-Q (reporting date: 2019-11-02), 10-Q (reporting date: 2019-08-03), 10-Q (reporting date: 2019-05-04), 10-K (reporting date: 2019-02-02), 10-Q (reporting date: 2018-11-03), 10-Q (reporting date: 2018-08-04), 10-Q (reporting date: 2018-05-05), 10-K (reporting date: 2018-02-03), 10-Q (reporting date: 2017-10-28), 10-Q (reporting date: 2017-07-29), 10-Q (reporting date: 2017-04-29), 10-K (reporting date: 2017-01-28), 10-Q (reporting date: 2016-10-29), 10-Q (reporting date: 2016-07-30), 10-Q (reporting date: 2016-04-30).

1 Q3 2023 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= + =

2 Click competitor name to see calculations.


Average Inventory Processing Period
This metric exhibits fluctuations throughout the recorded periods, mostly ranging between 56 and 72 days. Initially, values in the mid-60s prevail, with occasional dips to 58 and 59 days. A notable decrease occurs around August 2020, reaching a low of 41 days, suggesting improved inventory turnover during that time. However, this reduction is not sustained, as the period rises again to the 60s and early 70s across subsequent quarters. The overall pattern indicates variability in inventory management efficiency with intermittent improvements.
Average Receivable Collection Period
The receivable collection period remains relatively consistent, primarily hovering between 2 and 4 days, with an occasional peak of 5 days. Early periods show a collection duration of roughly 2 to 3 days, maintaining this range across most quarters. A slight increase is observed in the periods around mid-2020, where collection days rise to 4 or 5 days, potentially reflecting short-term challenges in receivables management. Overall, the collection period indicates stable and prompt collection practices with minor fluctuations.
Operating Cycle
The operating cycle mirrors trends seen in inventory processing and receivables collection. It generally remains between 59 to 75 days, with some volatility noted across quarters. A decrease is observed around mid-2020, dropping to 46 days, corresponding with the earlier noted reduced inventory period, indicating enhanced operational efficiency during that quarter. Subsequently, the cycle lengthens again, stabilizing in the low to mid-60-day range but trending slightly upward toward the end of the series. This pattern points to variable operational timing with occasional efficiency gains.

Average Payables Payment Period

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

Microsoft Excel
Oct 29, 2022 Jul 30, 2022 Apr 30, 2022 Jan 29, 2022 Oct 30, 2021 Jul 31, 2021 May 1, 2021 Jan 30, 2021 Oct 31, 2020 Aug 1, 2020 May 2, 2020 Feb 1, 2020 Nov 2, 2019 Aug 3, 2019 May 4, 2019 Feb 2, 2019 Nov 3, 2018 Aug 4, 2018 May 5, 2018 Feb 3, 2018 Oct 28, 2017 Jul 29, 2017 Apr 29, 2017 Jan 28, 2017 Oct 29, 2016 Jul 30, 2016 Apr 30, 2016
Selected Financial Data
Payables turnover
Short-term Activity Ratio (no. days)
Average payables payment period1
Benchmarks (no. days)
Average Payables Payment Period, Competitors2
Amazon.com Inc.
Home Depot Inc.
Lowe’s Cos. Inc.
TJX Cos. Inc.

Based on: 10-Q (reporting date: 2022-10-29), 10-Q (reporting date: 2022-07-30), 10-Q (reporting date: 2022-04-30), 10-K (reporting date: 2022-01-29), 10-Q (reporting date: 2021-10-30), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-05-01), 10-K (reporting date: 2021-01-30), 10-Q (reporting date: 2020-10-31), 10-Q (reporting date: 2020-08-01), 10-Q (reporting date: 2020-05-02), 10-K (reporting date: 2020-02-01), 10-Q (reporting date: 2019-11-02), 10-Q (reporting date: 2019-08-03), 10-Q (reporting date: 2019-05-04), 10-K (reporting date: 2019-02-02), 10-Q (reporting date: 2018-11-03), 10-Q (reporting date: 2018-08-04), 10-Q (reporting date: 2018-05-05), 10-K (reporting date: 2018-02-03), 10-Q (reporting date: 2017-10-28), 10-Q (reporting date: 2017-07-29), 10-Q (reporting date: 2017-04-29), 10-K (reporting date: 2017-01-28), 10-Q (reporting date: 2016-10-29), 10-Q (reporting date: 2016-07-30), 10-Q (reporting date: 2016-04-30).

1 Q3 2023 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ =

2 Click competitor name to see calculations.


Payables Turnover Ratio
The payables turnover ratio shows variability over the observed periods. Starting from a range around 7.5 to 9.5 in the early periods (2016-2019), it reached a peak at 15.18 in the period ending February 1, 2020, indicating a significantly faster rate of paying off suppliers at that time. After this peak, the ratio declined sharply to values around 4.08 to 4.94 throughout 2020 and early 2021, reflecting a slower turnover of payables. Subsequently, there is a gradual increase from mid-2021 onward, reaching approximately 7.16 by October 29, 2022, suggesting an improvement in payment efficiency compared to the 2020 low, but still below the earlier high levels.
Average Payables Payment Period (Days)
The average payables payment period, measuring the number of days taken to pay suppliers, exhibits notable fluctuations. Early data (2016-2019) shows payments typically between 39 and 49 days, indicating relatively consistent payment timing. A pronounced dip to 24 days occurs in May 2020, aligning with the increase in payables turnover observed at a similar time. Conversely, from August 2020 through roughly mid-2021, the payment period extends significantly, peaking at 89 days in October 2020, which corresponds with the lowest payables turnover ratio in the dataset, signifying slower payments. After mid-2021, the payment period gradually decreases from the high 80s and 70s down to 51 days by October 2022, indicating a return toward quicker payment practices relative to the pandemic-impacted periods.
Overall Pattern and Insights
The data reveals a distinctive impact around early 2020, during which the company’s payment practices shifted noticeably. The sharp peak in payables turnover and the drop in payment period suggest a transient acceleration in supplier payments, likely due to specific operational or strategic responses in that period. Soon after, a contrasting trend emerges with prolonged payment periods and reduced turnover ratios through most of 2020 and early 2021, potentially reflecting operational challenges or liquidity management strategies during that time. The subsequent gradual normalization from mid-2021 onward, seen in both ratios trending back toward historical ranges, points to an adjustment back to more typical supplier payment rhythms.

Cash Conversion Cycle

Ross Stores Inc., cash conversion cycle calculation (quarterly data)

No. days

Microsoft Excel
Oct 29, 2022 Jul 30, 2022 Apr 30, 2022 Jan 29, 2022 Oct 30, 2021 Jul 31, 2021 May 1, 2021 Jan 30, 2021 Oct 31, 2020 Aug 1, 2020 May 2, 2020 Feb 1, 2020 Nov 2, 2019 Aug 3, 2019 May 4, 2019 Feb 2, 2019 Nov 3, 2018 Aug 4, 2018 May 5, 2018 Feb 3, 2018 Oct 28, 2017 Jul 29, 2017 Apr 29, 2017 Jan 28, 2017 Oct 29, 2016 Jul 30, 2016 Apr 30, 2016
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
Home Depot Inc.
TJX Cos. Inc.

Based on: 10-Q (reporting date: 2022-10-29), 10-Q (reporting date: 2022-07-30), 10-Q (reporting date: 2022-04-30), 10-K (reporting date: 2022-01-29), 10-Q (reporting date: 2021-10-30), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-05-01), 10-K (reporting date: 2021-01-30), 10-Q (reporting date: 2020-10-31), 10-Q (reporting date: 2020-08-01), 10-Q (reporting date: 2020-05-02), 10-K (reporting date: 2020-02-01), 10-Q (reporting date: 2019-11-02), 10-Q (reporting date: 2019-08-03), 10-Q (reporting date: 2019-05-04), 10-K (reporting date: 2019-02-02), 10-Q (reporting date: 2018-11-03), 10-Q (reporting date: 2018-08-04), 10-Q (reporting date: 2018-05-05), 10-K (reporting date: 2018-02-03), 10-Q (reporting date: 2017-10-28), 10-Q (reporting date: 2017-07-29), 10-Q (reporting date: 2017-04-29), 10-K (reporting date: 2017-01-28), 10-Q (reporting date: 2016-10-29), 10-Q (reporting date: 2016-07-30), 10-Q (reporting date: 2016-04-30).

1 Q3 2023 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 provided financial data reveals notable patterns and fluctuations in inventory management, receivables, payables, and overall cash conversion efficiency over the observed periods.

Average Inventory Processing Period
The inventory processing period generally shows variability across quarters, fluctuating mostly between 56 and 72 days in recent periods. The highest duration was observed around October 2022 with 72 days, indicating potential delays or slower inventory turnover in that quarter. Earlier periods exhibited more stability, typically around 60 to 70 days. A sharp decrease to 41 days occurred in August 2020, suggesting improved inventory management or faster stock turnover during that time, though it reverted upwards subsequently.
Average Receivable Collection Period
This period remained remarkably stable throughout, fluctuating minimally between 1 and 5 days. Most quarters reported around 2 to 3 days, signifying efficient receivables collection and minimal delays in cash inflows from customers. A slight dip to 1 day in February 2020 suggests accelerated collection processes during that period, while a peak at 5 days in August 2020 represents a minor slowdown.
Average Payables Payment Period
The payables payment period demonstrates considerable variation over time. Initial values were around 39 to 49 days; however, in the mid-2020 period, the figure spikes notably to as high as 89 days, indicating an extended duration in settling payables. After that peak, the period gradually reduced but remained elevated compared to earlier figures, settling around 51 to 63 days in late 2022. This pattern may reflect strategic payment deferrals or liquidity management responses during challenging periods.
Cash Conversion Cycle
The cash conversion cycle exhibits significant volatility, with values ranging from a negative 25 days (indicating a net cash inflow advantage) to a positive 37 days. Notably, between mid-2020 and early 2021, the cycle shifted to negative values (-25 days), which suggests that the company was able to collect cash faster than it paid its suppliers and turned over inventory. Prior to and following this period, the cycle remained positive, typically between 16 and 25 days, with some upward movement towards late 2022. The negative cycle phase corresponds with the same period of increased payables duration and reduced inventory days, implying an intentional strategy to optimize working capital during uncertain conditions.