Stock Analysis on Net

T-Mobile US Inc. (NASDAQ:TMUS)

$24.99

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

Microsoft Excel

Short-term Activity Ratios (Summary)

T-Mobile US Inc., short-term (operating) activity ratios (quarterly data)

Microsoft Excel
Mar 31, 2025 Dec 31, 2024 Sep 30, 2024 Jun 30, 2024 Mar 31, 2024 Dec 31, 2023 Sep 30, 2023 Jun 30, 2023 Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020
Turnover Ratios
Inventory turnover
Receivables turnover
Working capital turnover
Average No. Days
Average inventory processing period
Add: Average receivable collection period
Operating cycle

Based on: 10-Q (reporting date: 2025-03-31), 10-K (reporting date: 2024-12-31), 10-Q (reporting date: 2024-09-30), 10-Q (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-K (reporting date: 2023-12-31), 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31).


Inventory Turnover
The inventory turnover ratio shows a generally increasing trend from March 2020 through the end of 2025, with some fluctuations. Starting at 11.19 in March 2020, the ratio peaks around 23.32 in September 2023 and then dips slightly before fluctuating again in early 2025. The rises indicate improved efficiency in inventory management over the period, though variability suggests potential seasonal or operational influences.
Receivables Turnover
Receivables turnover exhibits moderate fluctuations across the quarters, ranging from around 16.0 in early 2020 to a more stable range between 17 and 19 in later periods. The ratio peaks at 21.33 in June 2020 and generally maintains levels between 17 and 19 thereafter, indicating consistent efficiency in collecting receivables with minor seasonal variations.
Working Capital Turnover
The working capital turnover data is sparse, with noticeable values only at select intervals. A peak value of 50.77 is observed in March 2025, while prior values tend to be lower or missing. This suggests a potential significant improvement in the utilization of working capital in early 2025, though limited data points restrict comprehensive trend analysis.
Average Inventory Processing Period
The average inventory processing period demonstrates a general downward trend, moving from 33 days in March 2020 to a range around 16-22 days in the most recent periods. This points to increased speed and efficiency in inventory turnover, which aligns with the rising inventory turnover ratio noted earlier. However, some fluctuations are present, suggesting occasional variations in inventory management.
Average Receivable Collection Period
The average receivable collection period fluctuates modestly around 20 days throughout the reported timeframe. It remains relatively stable, with slight rises and falls between 17 and 23 days, indicating consistent management of receivables collection without material deterioration or improvement.
Operating Cycle
The operating cycle, which combines inventory and receivables periods, shows a declining trend from 56 days in March 2020 to values mostly around 37 to 42 days in later reports. This suggests an overall improvement in operational efficiency, enabling quicker conversion of inventory and receivables into cash, although minor fluctuations imply some variability in cycle length.

Turnover Ratios


Average No. Days


Inventory Turnover

T-Mobile US Inc., inventory turnover calculation (quarterly data)

Microsoft Excel
Mar 31, 2025 Dec 31, 2024 Sep 30, 2024 Jun 30, 2024 Mar 31, 2024 Dec 31, 2023 Sep 30, 2023 Jun 30, 2023 Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020
Selected Financial Data (US$ in millions)
Cost of revenues
Inventory
Short-term Activity Ratio
Inventory turnover1
Benchmarks
Inventory Turnover, Competitors2
AT&T Inc.
Verizon Communications Inc.

Based on: 10-Q (reporting date: 2025-03-31), 10-K (reporting date: 2024-12-31), 10-Q (reporting date: 2024-09-30), 10-Q (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-K (reporting date: 2023-12-31), 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31).

1 Q1 2025 Calculation
Inventory turnover = (Cost of revenuesQ1 2025 + Cost of revenuesQ4 2024 + Cost of revenuesQ3 2024 + Cost of revenuesQ2 2024) ÷ Inventory
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The financial data reveals several notable trends in the cost of revenues and inventory management for the analyzed periods.

Cost of Revenues

The cost of revenues exhibits considerable fluctuations across the reported quarters. Initial figures in early 2020 were relatively moderate, followed by a sharp increase toward the end of 2020, peaking at 10,452 million US dollars in December 2021.

Subsequently, the cost generally decreased through mid-2023, reaching a low near 7,004 million US dollars in June 2023. The figures then oscillated moderately, showing intermittent rises and falls toward the end of 2024 and into early 2025, ending at 7,400 million US dollars in March 2025.

This pattern may suggest seasonal or cyclical factors influencing operational expenses, with considerable expenditures in certain quarters balanced by strategic cost reductions in others.

Inventory

Inventory levels increased steadily during the initial periods, climbing from 1,225 million US dollars in March 2020 to a peak of 2,715 million US dollars in March 2022. Following this peak, inventory levels generally declined through mid-2023, reaching around 1,373 million US dollars in June 2023.

Thereafter, inventory values showed variability, with a minor upward trend toward the end of the reporting horizon, ending at approximately 1,937 million US dollars in March 2025.

The initial buildup in inventory could reflect preparatory stocking or increased demand expectations, while the later decrease might indicate improved inventory turnover or strategic inventory management adaptations.

Inventory Turnover Ratio

The inventory turnover ratio started to be reported from late 2020, exhibiting generally high and variable levels by period. The ratio reached peaks above 23 times in September 2023, indicating rapid inventory cycling relative to sales or cost of goods sold during that period.

Lower turnover ratios appeared intermittently, falling to approximately 14.26 in December 2020 and 15.47 in March 2025, suggesting fluctuations in how efficiently inventory was managed or sold over time.

Overall, the elevated turnover ratios in most periods point to efficient inventory management, with certain quarters showing distinct operational effectiveness in converting inventory into revenue.

In summary, the data indicates that cost of revenues and inventory levels have undergone substantial changes over the analyzed periods, with cost spikes offset by later reductions. Inventory management appears to have improved progressively, as evidenced by generally high inventory turnover ratios, though with some variability likely driven by market or operational conditions. These patterns reflect a dynamic operational environment with efforts toward cost control and inventory efficiency.


Receivables Turnover

T-Mobile US Inc., receivables turnover calculation (quarterly data)

Microsoft Excel
Mar 31, 2025 Dec 31, 2024 Sep 30, 2024 Jun 30, 2024 Mar 31, 2024 Dec 31, 2023 Sep 30, 2023 Jun 30, 2023 Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020
Selected Financial Data (US$ in millions)
Revenues
Accounts receivable, net of allowance for credit losses
Short-term Activity Ratio
Receivables turnover1
Benchmarks
Receivables Turnover, Competitors2
AT&T Inc.
Verizon Communications Inc.

Based on: 10-Q (reporting date: 2025-03-31), 10-K (reporting date: 2024-12-31), 10-Q (reporting date: 2024-09-30), 10-Q (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-K (reporting date: 2023-12-31), 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31).

1 Q1 2025 Calculation
Receivables turnover = (RevenuesQ1 2025 + RevenuesQ4 2024 + RevenuesQ3 2024 + RevenuesQ2 2024) ÷ Accounts receivable, net of allowance for credit losses
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The quarterly financial data presents trends in revenues, accounts receivable, and receivables turnover ratios over a five-year period from March 2020 to March 2025. The following analysis summarizes the key patterns observed in these items.

Revenues
Revenues exhibit a generally fluctuating yet slightly upward trend over the periods analyzed. Starting at $11,113 million in March 2020, revenues increased sharply to a peak of $20,785 million by December 2021. Subsequently, revenues experienced moderate oscillations, with values ranging between approximately $19,000 million and $20,000 million through 2022 and 2023. The data shows a marked rebound to $21,872 million by December 2024, followed by a slight decrease to $20,886 million in March 2025. This pattern suggests some seasonality or external market influences impacting revenues but overall growth despite short-term volatility.
Accounts Receivable, Net of Allowance for Credit Losses
Accounts receivable values start at $1,862 million in March 2020 and display a substantial increase through 2020, reaching about $4,276 million by December 2020. From 2021 onward, the balances fluctuate within a narrower range of approximately $4,000 million to $4,600 million. The variation appears relatively contained, with minor increases and decreases quarter-over-quarter. This stability in accounts receivable indicates consistent credit terms and collection practices during the period. The increase from the initial quarters in 2020 may reflect a change in credit policies or higher sales on credit during that time.
Receivables Turnover Ratio
The receivables turnover ratio data starts appearing from March 2021 onward. This ratio oscillates between approximately 16 and 21 throughout the analyzed quarters. The ratio shows moderate variation quarter to quarter but remains mostly in the range of 17 to 19. Notably, the highest recorded turnover ratio is 21.33 in June 2021, indicating more rapid collection of receivables during that period. Periods of lower turnover around 16-17 suggest slower collection rates. Overall, the turnover ratio exhibits a relatively stable collection efficiency over the years with some variability, possibly influenced by seasonal factors or changes in credit management.

In summary, the financial data reflect a growing revenue base with intermittent fluctuations, stabilized accounts receivable levels maintaining consistent credit management, and a generally steady receivables turnover ratio indicating stable collection performance. The slight variations observed in revenues and turnover ratios may warrant further investigation into seasonal impacts or operational changes affecting cash flow efficiency.


Working Capital Turnover

T-Mobile US Inc., working capital turnover calculation (quarterly data)

Microsoft Excel
Mar 31, 2025 Dec 31, 2024 Sep 30, 2024 Jun 30, 2024 Mar 31, 2024 Dec 31, 2023 Sep 30, 2023 Jun 30, 2023 Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020
Selected Financial Data (US$ in millions)
Current assets
Less: Current liabilities
Working capital
 
Revenues
Short-term Activity Ratio
Working capital turnover1
Benchmarks
Working Capital Turnover, Competitors2
AT&T Inc.
Verizon Communications Inc.

Based on: 10-Q (reporting date: 2025-03-31), 10-K (reporting date: 2024-12-31), 10-Q (reporting date: 2024-09-30), 10-Q (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-K (reporting date: 2023-12-31), 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31).

1 Q1 2025 Calculation
Working capital turnover = (RevenuesQ1 2025 + RevenuesQ4 2024 + RevenuesQ3 2024 + RevenuesQ2 2024) ÷ Working capital
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The analysis of the quarterly financial data reveals several notable trends and fluctuations across the presented periods.

Working Capital
The working capital values demonstrate significant volatility over the quarters, oscillating between negative and positive figures. Starting with a large negative value of -5,269 million US$ in March 2020, there is an abrupt increase to a positive 1,130 million US$ in June 2020, followed by fluctuations that generally maintain negative values through the subsequent quarters to December 2023. The negative trend appears to moderate gradually from late 2023 into 2024, culminating in a positive 3,812 million US$ in December 2024 before dipping again to 3,812 million US$ in March 2025. This pattern indicates challenges in managing current assets and liabilities efficiently during much of the period, with intermittent recoveries suggesting improvements in short-term liquidity management in specific quarters.
Revenues
Revenues exhibit a generally stable yet somewhat fluctuating pattern. The level rises sharply from 11,113 million US$ in March 2020 to a peak of 20,785 million US$ in December 2020, reflecting substantial growth within the year. Subsequent quarters show a modest decline and relative stabilization around the 19,000 to 20,000 million US$ range through most of 2021, 2022, and 2023. By 2024, revenues increase slightly again, reaching a new high of 21,872 million US$ in December 2024 before a minor decrease to 20,886 million US$ in March 2025. This trend suggests sustained revenue generation capability with some seasonality or market variability affecting quarterly results.
Working Capital Turnover
The working capital turnover ratio data are sparse, with values only reported for specific quarters. The ratio is reported as 31.35 at some point early in the dataset, followed by an increase to 50.77 later and then a decrease to 21.69 toward the end. These figures reflect a highly variable relationship between revenues and working capital, indicating shifts in operational efficiency or liquidity management. High turnover ratios typically suggest efficient use of working capital relative to revenue, whereas declining or fluctuating ratios may point to periods of inefficiency or liquidity constraints.

Overall, the data depict a company experiencing variable working capital conditions with occasional improvements, consistent revenue growth with seasonal or cyclical fluctuations, and volatile working capital turnover rates indicating changes in operational effectiveness. The negative working capital positions in many quarters could imply reliance on short-term liabilities or inventory management challenges, while the eventual shift to positive working capital suggests an improving liquidity stance. Meanwhile, revenue resilience and growth toward later periods signal solid market performance despite operational working capital concerns.


Average Inventory Processing Period

T-Mobile US Inc., average inventory processing period calculation (quarterly data)

Microsoft Excel
Mar 31, 2025 Dec 31, 2024 Sep 30, 2024 Jun 30, 2024 Mar 31, 2024 Dec 31, 2023 Sep 30, 2023 Jun 30, 2023 Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020
Selected Financial Data
Inventory turnover
Short-term Activity Ratio (no. days)
Average inventory processing period1
Benchmarks (no. days)
Average Inventory Processing Period, Competitors2
AT&T Inc.
Verizon Communications Inc.

Based on: 10-Q (reporting date: 2025-03-31), 10-K (reporting date: 2024-12-31), 10-Q (reporting date: 2024-09-30), 10-Q (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-K (reporting date: 2023-12-31), 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31).

1 Q1 2025 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =

2 Click competitor name to see calculations.


The inventory turnover ratio exhibits notable fluctuations over the observed periods. Beginning with a value of 11.19 in the first quarter of 2020, there is a marked upward trend reaching a peak of 23.32 in the third quarter of 2023. Intermittent dips occur, such as the decline to 18.08 in the fourth quarter of 2023 and further to 15.47 by the first quarter of 2025. This pattern indicates periods of intensified inventory management efficiency interspersed with phases of relatively slower turnover.

Correspondingly, the average inventory processing period, measured in days, demonstrates an inverse relationship with the inventory turnover ratio. Starting from 33 days in early 2020, the processing period decreases steadily to as low as 16 days during certain quarters (notably in the third quarter of 2023 and third quarter of 2024). Occasional increases to around 20 to 24 days appear toward the later periods, specifically the fourth quarter of 2023 and first quarter of 2025. This suggests that on average, the company is processing inventory more rapidly over time, with some irregularities.

Inventory Turnover Ratio
Demonstrates an overall improving trend indicating increased inventory efficiency, with values generally moving from around 11 to above 20 across the reported quarters. Peaks and troughs indicate cyclical or operational variability in turnover speeds.
Average Inventory Processing Period
Consistent with the turnover ratio, the average days to process inventory declines from over 30 days to approximately 16–20 days in most recent periods. This reflects enhanced inventory handling and potentially improved demand forecasting or supply chain management.
Relationship Between Metrics
The inverse correlation between inventory turnover and processing period aligns with standard operational expectations, confirming reliability of the data trends. Efficiency improvements in inventory management are evident through these complementary metrics.

In summary, the data points to progressive improvements in inventory efficiency over the reported quarters, with faster turnover and reduced processing times. However, the presence of some variability toward the end of the period indicates potential challenges or adjustments in inventory practices that merit further investigation.


Average Receivable Collection Period

T-Mobile US Inc., average receivable collection period calculation (quarterly data)

Microsoft Excel
Mar 31, 2025 Dec 31, 2024 Sep 30, 2024 Jun 30, 2024 Mar 31, 2024 Dec 31, 2023 Sep 30, 2023 Jun 30, 2023 Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020
Selected Financial Data
Receivables turnover
Short-term Activity Ratio (no. days)
Average receivable collection period1
Benchmarks (no. days)
Average Receivable Collection Period, Competitors2
AT&T Inc.
Verizon Communications Inc.

Based on: 10-Q (reporting date: 2025-03-31), 10-K (reporting date: 2024-12-31), 10-Q (reporting date: 2024-09-30), 10-Q (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-K (reporting date: 2023-12-31), 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31).

1 Q1 2025 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =

2 Click competitor name to see calculations.


Receivables Turnover
The receivables turnover ratio demonstrates variability over the observed periods starting from the first available data point. There is an initial increase from 16 to 21.33, indicating a period where the company collected its receivables more rapidly. Subsequently, the ratio declines to around the 17 to 19 range, fluctuating modestly within these bounds throughout the later periods. This pattern implies some degree of inconsistency in how efficiently the company managed receivable collections over time, but generally maintaining a stable level in the latter periods.
Average Receivable Collection Period
The collection period mirrors the inverse movement of the receivables turnover, beginning at 23 days and dropping to 17 days, which corresponds with the initial improvement in collections. Following this, the number of days fluctuates between 19 and 22 days in the majority of subsequent quarters. This persistence in a relatively narrow range indicates that the average time to collect receivables remained fairly steady in these periods, with no drastic improvements or deteriorations evident.
Summary of Trends
The overall analysis reveals that the company's efficiency in receivables management improved notably at one point, as reflected in the higher turnover ratio and shorter collection period. However, this efficiency did not continue to improve consistently and instead stabilized with some fluctuations around a moderate level. The relationship between both metrics is consistent, showing an expected inverse relationship throughout the periods analyzed.

Operating Cycle

T-Mobile US Inc., operating cycle calculation (quarterly data)

No. days

Microsoft Excel
Mar 31, 2025 Dec 31, 2024 Sep 30, 2024 Jun 30, 2024 Mar 31, 2024 Dec 31, 2023 Sep 30, 2023 Jun 30, 2023 Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020
Selected Financial Data
Average inventory processing period
Average receivable collection period
Short-term Activity Ratio
Operating cycle1
Benchmarks
Operating Cycle, Competitors2
AT&T Inc.
Verizon Communications Inc.

Based on: 10-Q (reporting date: 2025-03-31), 10-K (reporting date: 2024-12-31), 10-Q (reporting date: 2024-09-30), 10-Q (reporting date: 2024-06-30), 10-Q (reporting date: 2024-03-31), 10-K (reporting date: 2023-12-31), 10-Q (reporting date: 2023-09-30), 10-Q (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-K (reporting date: 2022-12-31), 10-Q (reporting date: 2022-09-30), 10-Q (reporting date: 2022-06-30), 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31).

1 Q1 2025 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 shows a fluctuating downward trend from March 2021 through March 2025. It begins at 33 days in March 2021, then decreases to 16 days by September 2023, with minor oscillations observed in between. Notable increases occur in December 2023 and again in September 2024, reaching up to 24 days. Overall, the trend indicates improved inventory turnover efficiency but with some variability in recent quarters.
Average Receivable Collection Period
The average receivable collection period displays relatively stable behavior over the observed timeline, ranging mostly between 17 and 22 days. Starting at 23 days in March 2021, it reduces to a low of 17 days in June 2021, then fluctuates slightly around the 20-day mark thereafter. The collection period shows no significant upward or downward trend, suggesting consistent effectiveness in receivables management.
Operating Cycle
The operating cycle follows a pattern analogous to the inventory processing period but shows less volatility. It decreases from 56 days in March 2021 to approximately 37-39 days by late 2023. Minor fluctuations are evident, such as slight increases to 42 days in March and June 2024. The overall decline points to a shortening of the time between inventory acquisition and cash collection, implying improved operational efficiency over time.