Stock Analysis on Net

Micron Technology Inc. (NASDAQ:MU)

$24.99

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

Microsoft Excel

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Short-term Activity Ratios (Summary)

Micron Technology Inc., short-term (operating) activity ratios (quarterly data)

Microsoft Excel
May 29, 2025 Feb 27, 2025 Nov 28, 2024 Aug 29, 2024 May 30, 2024 Feb 29, 2024 Nov 30, 2023 Aug 31, 2023 Jun 1, 2023 Mar 2, 2023 Dec 1, 2022 Sep 1, 2022 Jun 2, 2022 Mar 3, 2022 Dec 2, 2021 Sep 2, 2021 Jun 3, 2021 Mar 4, 2021 Dec 3, 2020 Sep 3, 2020 May 28, 2020 Feb 27, 2020 Nov 28, 2019 Aug 29, 2019 May 30, 2019 Feb 28, 2019 Nov 29, 2018
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: 2025-05-29), 10-Q (reporting date: 2025-02-27), 10-Q (reporting date: 2024-11-28), 10-K (reporting date: 2024-08-29), 10-Q (reporting date: 2024-05-30), 10-Q (reporting date: 2024-02-29), 10-Q (reporting date: 2023-11-30), 10-K (reporting date: 2023-08-31), 10-Q (reporting date: 2023-06-01), 10-Q (reporting date: 2023-03-02), 10-Q (reporting date: 2022-12-01), 10-K (reporting date: 2022-09-01), 10-Q (reporting date: 2022-06-02), 10-Q (reporting date: 2022-03-03), 10-Q (reporting date: 2021-12-02), 10-K (reporting date: 2021-09-02), 10-Q (reporting date: 2021-06-03), 10-Q (reporting date: 2021-03-04), 10-Q (reporting date: 2020-12-03), 10-K (reporting date: 2020-09-03), 10-Q (reporting date: 2020-05-28), 10-Q (reporting date: 2020-02-27), 10-Q (reporting date: 2019-11-28), 10-K (reporting date: 2019-08-29), 10-Q (reporting date: 2019-05-30), 10-Q (reporting date: 2019-02-28), 10-Q (reporting date: 2018-11-29).


Inventory Turnover
The inventory turnover ratio showed a gradual increase from 2.48 to a peak of 3.85 between November 2019 and June 2021. After this peak, a steady decline followed, reaching a low of 1.91 in September 2022. Post this trough, the ratio displayed a moderate recovery, stabilizing around the low 2.0s through early 2025.
Receivables Turnover
Receivables turnover decreased from 7.33 to values between 5 and 6 in the period between late 2019 and early 2022, indicating slower collection during this timeframe. A sharp improvement was observed reaching 10.12 in March 2023, after which a notable decline took place, falling steadily below 4.0 by mid-2024 before a mild rebound occurred near 4.5 later in the period.
Working Capital Turnover
This ratio showed a mostly decreasing trend from 2.31 in late 2019 to a trough of 0.94 in August 2023, signaling reduced efficiency in generating sales from working capital. From this low, there was a meaningful recovery to around 1.9 by mid-2025, reflecting some operational improvement.
Average Inventory Processing Period
The average number of days to process inventory declined notably from 147 days in late 2019 to 95 days by September 2021, indicating more efficient inventory management. However, after this date, the period increased significantly, peaking at 192 days in September 2022, suggesting slower inventory turnover. Subsequently, it gradually decreased again to approximately 150 days by mid-2025.
Average Receivable Collection Period
This metric initially increased from 50 days in November 2019 to a high of 70 days around September 2021, implying longer collection times. Afterward, there was an improvement with a sharp drop to 36 days by March 2023, followed by a reversal toward longer periods, reaching nearly 96 days by late 2024. Slight improvement was seen thereafter, remaining around 80 days by mid-2025.
Operating Cycle
The operating cycle lengthened from 197 days in late 2019 to a peak of 254 days by late 2024. This extension corresponds to the increases observed in both inventory processing and receivable collection periods. A minor decrease was noted toward mid-2025, but the overall trend indicates a longer operating cycle over the analyzed period, reflecting slower asset turnover and potential liquidity challenges.

Turnover Ratios


Average No. Days


Inventory Turnover

Micron Technology Inc., inventory turnover calculation (quarterly data)

Microsoft Excel
May 29, 2025 Feb 27, 2025 Nov 28, 2024 Aug 29, 2024 May 30, 2024 Feb 29, 2024 Nov 30, 2023 Aug 31, 2023 Jun 1, 2023 Mar 2, 2023 Dec 1, 2022 Sep 1, 2022 Jun 2, 2022 Mar 3, 2022 Dec 2, 2021 Sep 2, 2021 Jun 3, 2021 Mar 4, 2021 Dec 3, 2020 Sep 3, 2020 May 28, 2020 Feb 27, 2020 Nov 28, 2019 Aug 29, 2019 May 30, 2019 Feb 28, 2019 Nov 29, 2018
Selected Financial Data (US$ in millions)
Cost of goods sold
Inventories
Short-term Activity Ratio
Inventory turnover1
Benchmarks
Inventory Turnover, Competitors2
Advanced Micro Devices Inc.
Analog Devices Inc.
Applied Materials Inc.
Broadcom Inc.
Intel Corp.
KLA Corp.
Lam Research Corp.
NVIDIA Corp.
Qualcomm Inc.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-05-29), 10-Q (reporting date: 2025-02-27), 10-Q (reporting date: 2024-11-28), 10-K (reporting date: 2024-08-29), 10-Q (reporting date: 2024-05-30), 10-Q (reporting date: 2024-02-29), 10-Q (reporting date: 2023-11-30), 10-K (reporting date: 2023-08-31), 10-Q (reporting date: 2023-06-01), 10-Q (reporting date: 2023-03-02), 10-Q (reporting date: 2022-12-01), 10-K (reporting date: 2022-09-01), 10-Q (reporting date: 2022-06-02), 10-Q (reporting date: 2022-03-03), 10-Q (reporting date: 2021-12-02), 10-K (reporting date: 2021-09-02), 10-Q (reporting date: 2021-06-03), 10-Q (reporting date: 2021-03-04), 10-Q (reporting date: 2020-12-03), 10-K (reporting date: 2020-09-03), 10-Q (reporting date: 2020-05-28), 10-Q (reporting date: 2020-02-27), 10-Q (reporting date: 2019-11-28), 10-K (reporting date: 2019-08-29), 10-Q (reporting date: 2019-05-30), 10-Q (reporting date: 2019-02-28), 10-Q (reporting date: 2018-11-29).

1 Q3 2025 Calculation
Inventory turnover = (Cost of goods soldQ3 2025 + Cost of goods soldQ2 2025 + Cost of goods soldQ1 2025 + Cost of goods soldQ4 2024) ÷ Inventories
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The analysis of the quarterly financial data reveals several notable trends in cost of goods sold, inventories, and inventory turnover ratios over the periods presented.

Cost of Goods Sold (COGS)
COGS demonstrates a generally increasing trend with some fluctuations across the periods. Starting from 3,298 million USD in late 2018, there is a progressive increase reaching a peak around mid-2024 at 5,793 million USD. Some quarters, such as late 2019 and early 2020, show moderate decreases or stabilization, but the overall trajectory is upward. This suggests rising production or sales volume levels, or potentially increasing cost pressures over time.
Inventories
Inventories show a consistent upward trend throughout the period analyzed. Beginning at 3,876 million USD in late 2018, inventory levels increased steadily with minor fluctuations, peaking at 9,007 million USD around mid-2024. There is a marked increase from 2021 onward, which may indicate stockpiling, increased production capacity, or slower inventory turnover periods. The large inventory buildup corresponds with the rise in COGS but at a faster pace, pointing to potential challenges in inventory management or sales absorption.
Inventory Turnover Ratio
Inventory turnover ratios, available from mid-2019, initially range between approximately 2.48 and 2.74, indicating moderate inventory efficiency. There is a noticeable improvement in turnover through 2020 and early 2021, peaking near 3.85, which suggests more efficient inventory management or increased sales velocity relative to inventory held. However, starting from mid-2021, the ratio declines significantly, reaching lows around 1.91 in early 2023, followed by slight recovery but remaining below earlier highs through 2025. This decline in turnover efficiency may reflect excess inventory levels or slower sales growth relative to inventory accumulation.

In summary, the data reveals increasing cost structures alongside substantial inventory accumulation, with a peak and subsequent decline in inventory turnover ratio indicating fluctuating operational efficiency. The overall pattern highlights challenges in balancing inventory levels with cost and sales dynamics, suggesting potential areas for inventory and cost control improvements going forward.


Receivables Turnover

Micron Technology Inc., receivables turnover calculation (quarterly data)

Microsoft Excel
May 29, 2025 Feb 27, 2025 Nov 28, 2024 Aug 29, 2024 May 30, 2024 Feb 29, 2024 Nov 30, 2023 Aug 31, 2023 Jun 1, 2023 Mar 2, 2023 Dec 1, 2022 Sep 1, 2022 Jun 2, 2022 Mar 3, 2022 Dec 2, 2021 Sep 2, 2021 Jun 3, 2021 Mar 4, 2021 Dec 3, 2020 Sep 3, 2020 May 28, 2020 Feb 27, 2020 Nov 28, 2019 Aug 29, 2019 May 30, 2019 Feb 28, 2019 Nov 29, 2018
Selected Financial Data (US$ in millions)
Revenue
Receivables
Short-term Activity Ratio
Receivables turnover1
Benchmarks
Receivables Turnover, Competitors2
Advanced Micro Devices Inc.
Analog Devices Inc.
Applied Materials Inc.
Broadcom Inc.
Intel Corp.
KLA Corp.
Lam Research Corp.
NVIDIA Corp.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-05-29), 10-Q (reporting date: 2025-02-27), 10-Q (reporting date: 2024-11-28), 10-K (reporting date: 2024-08-29), 10-Q (reporting date: 2024-05-30), 10-Q (reporting date: 2024-02-29), 10-Q (reporting date: 2023-11-30), 10-K (reporting date: 2023-08-31), 10-Q (reporting date: 2023-06-01), 10-Q (reporting date: 2023-03-02), 10-Q (reporting date: 2022-12-01), 10-K (reporting date: 2022-09-01), 10-Q (reporting date: 2022-06-02), 10-Q (reporting date: 2022-03-03), 10-Q (reporting date: 2021-12-02), 10-K (reporting date: 2021-09-02), 10-Q (reporting date: 2021-06-03), 10-Q (reporting date: 2021-03-04), 10-Q (reporting date: 2020-12-03), 10-K (reporting date: 2020-09-03), 10-Q (reporting date: 2020-05-28), 10-Q (reporting date: 2020-02-27), 10-Q (reporting date: 2019-11-28), 10-K (reporting date: 2019-08-29), 10-Q (reporting date: 2019-05-30), 10-Q (reporting date: 2019-02-28), 10-Q (reporting date: 2018-11-29).

1 Q3 2025 Calculation
Receivables turnover = (RevenueQ3 2025 + RevenueQ2 2025 + RevenueQ1 2025 + RevenueQ4 2024) ÷ Receivables
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


Revenue
The revenue displays notable fluctuations over the examined period. Initially, revenue decreased from approximately 7,913 million US dollars in late 2018 to a low point around 4,085 million by late 2022. Following this trough, a gradual recovery trend is observable, with revenue rising again, reaching approximately 9,301 million in mid-2025. This pattern suggests cycles affected by external or internal factors influencing sales and operational conditions. Mid-2021 represents a pivot point from which revenue begins a sustained upward trajectory, though several intermediate downswings occur, especially visible in late 2022.
Receivables
Receivables values similarly show variability but with a less consistent trend relative to revenue. Initially, receivables declined from 5,418 million in late 2018 to a minimum of 2,278 million in mid-2023. Subsequently, the data reveals a strong upward rebound, with receivables reaching about 7,436 million by mid-2025. The initial decline in receivables may indicate tighter credit policies or improved collections, while the later increase could reflect expanding sales volumes or relaxed credit terms in tandem with revenue recovery.
Receivables Turnover
The receivables turnover ratio exhibits variability, starting at an approximate level of 7.33 and experiencing generally downward trends with fluctuations throughout the periods. The ratio peaks at 10.12 in mid-2023, corresponding with the lowest point in receivables balances, indicating highly efficient collection during this time. However, afterward, the ratio declines steadily to the mid-4 range by mid-2025, which correlates with the substantial increase in receivables balances. This suggests a gradual reduction in collection efficiency or lengthening of receivables days, possibly due to expansion in credit sales or changes in customer payment behaviors.
Overall Analysis
The interplay between revenue, receivables, and receivables turnover points to several operational dynamics. Revenue and receivables have both experienced cycles of decline and recovery, with receivables turnover inversely reflecting these changes. Periods of declining revenue generally coincide with improved receivables turnover, implying stricter collection or reduced credit sales, while recovery in revenue aligns with rising receivables and reduced turnover ratio, suggesting increasing sales and extended credit terms. The trends imply that financial management adapted to changing market or internal conditions by modulating credit policies and collection efforts, impacting the cash conversion cycle and working capital needs. The recent trend towards higher receivables and lower turnover ratios merits ongoing monitoring to manage credit risk and optimize liquidity.

Working Capital Turnover

Micron Technology Inc., working capital turnover calculation (quarterly data)

Microsoft Excel
May 29, 2025 Feb 27, 2025 Nov 28, 2024 Aug 29, 2024 May 30, 2024 Feb 29, 2024 Nov 30, 2023 Aug 31, 2023 Jun 1, 2023 Mar 2, 2023 Dec 1, 2022 Sep 1, 2022 Jun 2, 2022 Mar 3, 2022 Dec 2, 2021 Sep 2, 2021 Jun 3, 2021 Mar 4, 2021 Dec 3, 2020 Sep 3, 2020 May 28, 2020 Feb 27, 2020 Nov 28, 2019 Aug 29, 2019 May 30, 2019 Feb 28, 2019 Nov 29, 2018
Selected Financial Data (US$ in millions)
Current assets
Less: Current liabilities
Working capital
 
Revenue
Short-term Activity Ratio
Working capital turnover1
Benchmarks
Working Capital Turnover, Competitors2
Advanced Micro Devices Inc.
Analog Devices Inc.
Applied Materials Inc.
Broadcom Inc.
Intel Corp.
KLA Corp.
Lam Research Corp.
NVIDIA Corp.
Qualcomm Inc.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-05-29), 10-Q (reporting date: 2025-02-27), 10-Q (reporting date: 2024-11-28), 10-K (reporting date: 2024-08-29), 10-Q (reporting date: 2024-05-30), 10-Q (reporting date: 2024-02-29), 10-Q (reporting date: 2023-11-30), 10-K (reporting date: 2023-08-31), 10-Q (reporting date: 2023-06-01), 10-Q (reporting date: 2023-03-02), 10-Q (reporting date: 2022-12-01), 10-K (reporting date: 2022-09-01), 10-Q (reporting date: 2022-06-02), 10-Q (reporting date: 2022-03-03), 10-Q (reporting date: 2021-12-02), 10-K (reporting date: 2021-09-02), 10-Q (reporting date: 2021-06-03), 10-Q (reporting date: 2021-03-04), 10-Q (reporting date: 2020-12-03), 10-K (reporting date: 2020-09-03), 10-Q (reporting date: 2020-05-28), 10-Q (reporting date: 2020-02-27), 10-Q (reporting date: 2019-11-28), 10-K (reporting date: 2019-08-29), 10-Q (reporting date: 2019-05-30), 10-Q (reporting date: 2019-02-28), 10-Q (reporting date: 2018-11-29).

1 Q3 2025 Calculation
Working capital turnover = (RevenueQ3 2025 + RevenueQ2 2025 + RevenueQ1 2025 + RevenueQ4 2024) ÷ Working capital
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The financial data reveals several key trends and shifts in working capital, revenue, and working capital turnover over the periods analyzed.

Working Capital
The working capital exhibited a general upward trend from November 2018 through May 2025, beginning at $9,850 million and increasing to $17,784 million by May 2025. There are some fluctuations along the timeline, notably a dip around September 2022 to December 2022, followed by a recovery and new highs reached toward the end of the dataset. This increase suggests a strengthening liquidity position over the period analyzed.
Revenue
Revenue demonstrated considerable volatility throughout the periods. Initially, revenue declined from $7,913 million in November 2018 to a low near $3,693 million by September 2022. Following this decline, there was a notable rebound, with revenue increasing substantially to a peak of $9,301 million by August 2024 before a minor pullback to $8,053 million in the final reported period. The revenue pattern suggests cycles of contraction and expansion possibly linked to market dynamics or product demand.
Working Capital Turnover
The working capital turnover ratio, available only from May 2019 onwards, shows a declining trend from 2.31 to a trough of 0.94 around September 2022, coinciding with the lower revenue figures and increased working capital levels. This ratio recovered thereafter, climbing to 1.90 by May 2025. A lower turnover ratio during the period of declining revenue and increasing working capital indicates less efficient use of working capital to generate sales during that time, with some improvement in efficiency toward the end of the timeline.

Overall, the data shows a company that experienced a challenging environment around 2021 and 2022, reflected in decreasing revenue and a deterioration in working capital turnover. However, improvements in later periods suggest a recovery phase with increases in both revenue and efficiency in working capital utilization.


Average Inventory Processing Period

Micron Technology Inc., average inventory processing period calculation (quarterly data)

Microsoft Excel
May 29, 2025 Feb 27, 2025 Nov 28, 2024 Aug 29, 2024 May 30, 2024 Feb 29, 2024 Nov 30, 2023 Aug 31, 2023 Jun 1, 2023 Mar 2, 2023 Dec 1, 2022 Sep 1, 2022 Jun 2, 2022 Mar 3, 2022 Dec 2, 2021 Sep 2, 2021 Jun 3, 2021 Mar 4, 2021 Dec 3, 2020 Sep 3, 2020 May 28, 2020 Feb 27, 2020 Nov 28, 2019 Aug 29, 2019 May 30, 2019 Feb 28, 2019 Nov 29, 2018
Selected Financial Data
Inventory turnover
Short-term Activity Ratio (no. days)
Average inventory processing period1
Benchmarks (no. days)
Average Inventory Processing Period, Competitors2
Advanced Micro Devices Inc.
Analog Devices Inc.
Applied Materials Inc.
Broadcom Inc.
Intel Corp.
KLA Corp.
Lam Research Corp.
NVIDIA Corp.
Qualcomm Inc.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-05-29), 10-Q (reporting date: 2025-02-27), 10-Q (reporting date: 2024-11-28), 10-K (reporting date: 2024-08-29), 10-Q (reporting date: 2024-05-30), 10-Q (reporting date: 2024-02-29), 10-Q (reporting date: 2023-11-30), 10-K (reporting date: 2023-08-31), 10-Q (reporting date: 2023-06-01), 10-Q (reporting date: 2023-03-02), 10-Q (reporting date: 2022-12-01), 10-K (reporting date: 2022-09-01), 10-Q (reporting date: 2022-06-02), 10-Q (reporting date: 2022-03-03), 10-Q (reporting date: 2021-12-02), 10-K (reporting date: 2021-09-02), 10-Q (reporting date: 2021-06-03), 10-Q (reporting date: 2021-03-04), 10-Q (reporting date: 2020-12-03), 10-K (reporting date: 2020-09-03), 10-Q (reporting date: 2020-05-28), 10-Q (reporting date: 2020-02-27), 10-Q (reporting date: 2019-11-28), 10-K (reporting date: 2019-08-29), 10-Q (reporting date: 2019-05-30), 10-Q (reporting date: 2019-02-28), 10-Q (reporting date: 2018-11-29).

1 Q3 2025 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =

2 Click competitor name to see calculations.


Inventory Turnover
The inventory turnover ratio shows a clear upward trend from early 2019 through mid-2021, increasing from approximately 2.48 to a peak around 3.85. This suggests improved efficiency in managing and selling inventory during that period. After reaching the peak, the ratio begins to decline steadily from late 2021, dropping as low as approximately 1.91 by early 2023. Following this trough, the turnover ratio rises moderately but remains below previous highs, fluctuating in the 2.0 to 2.4 range through mid-2025. The overall pattern indicates a phase of strengthened inventory management efficiency followed by a period of reduced turnover rates, with some recovery towards the end of the observed period.
Average Inventory Processing Period
The average inventory processing period, measured in days, moves inversely to the inventory turnover ratio. It starts relatively high at 147 days in late 2019, then decreases consistently to reach its shortest duration of 95 days around mid-2021. This decline corresponds to the increase in inventory turnover, reflecting faster inventory movement. However, from mid-2021 onward, the processing period lengthens significantly, peaking near 192 days in early 2023. This increase indicates a slowdown in inventory processing, coinciding with the decline in turnover ratio. After this peak, the period shortens somewhat but remains elevated around 150 to 166 days through mid-2025, suggesting a partial but incomplete return to more efficient inventory management.
Summary of Trends and Insights
The data reflects a cycle in inventory efficiency over the analyzed timeframe. The initial improvement in inventory turnover and reduction in processing days points to enhanced operational effectiveness and possibly stronger demand or better supply chain management during 2019 to mid-2021. The subsequent reversal starting around mid-2021, characterized by decreased turnover and prolonged processing periods, implies challenges such as excess inventory, slower sales, or disruptions affecting inventory flows. The partial recovery in recent quarters suggests some stabilization, yet inventory management had not returned to the optimal levels observed earlier in the period. These trends warrant further investigation into the causes behind the declining efficiency post-2021 and assessment of strategies to sustain improvements.

Average Receivable Collection Period

Micron Technology Inc., average receivable collection period calculation (quarterly data)

Microsoft Excel
May 29, 2025 Feb 27, 2025 Nov 28, 2024 Aug 29, 2024 May 30, 2024 Feb 29, 2024 Nov 30, 2023 Aug 31, 2023 Jun 1, 2023 Mar 2, 2023 Dec 1, 2022 Sep 1, 2022 Jun 2, 2022 Mar 3, 2022 Dec 2, 2021 Sep 2, 2021 Jun 3, 2021 Mar 4, 2021 Dec 3, 2020 Sep 3, 2020 May 28, 2020 Feb 27, 2020 Nov 28, 2019 Aug 29, 2019 May 30, 2019 Feb 28, 2019 Nov 29, 2018
Selected Financial Data
Receivables turnover
Short-term Activity Ratio (no. days)
Average receivable collection period1
Benchmarks (no. days)
Average Receivable Collection Period, Competitors2
Advanced Micro Devices Inc.
Analog Devices Inc.
Applied Materials Inc.
Broadcom Inc.
Intel Corp.
KLA Corp.
Lam Research Corp.
NVIDIA Corp.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-05-29), 10-Q (reporting date: 2025-02-27), 10-Q (reporting date: 2024-11-28), 10-K (reporting date: 2024-08-29), 10-Q (reporting date: 2024-05-30), 10-Q (reporting date: 2024-02-29), 10-Q (reporting date: 2023-11-30), 10-K (reporting date: 2023-08-31), 10-Q (reporting date: 2023-06-01), 10-Q (reporting date: 2023-03-02), 10-Q (reporting date: 2022-12-01), 10-K (reporting date: 2022-09-01), 10-Q (reporting date: 2022-06-02), 10-Q (reporting date: 2022-03-03), 10-Q (reporting date: 2021-12-02), 10-K (reporting date: 2021-09-02), 10-Q (reporting date: 2021-06-03), 10-Q (reporting date: 2021-03-04), 10-Q (reporting date: 2020-12-03), 10-K (reporting date: 2020-09-03), 10-Q (reporting date: 2020-05-28), 10-Q (reporting date: 2020-02-27), 10-Q (reporting date: 2019-11-28), 10-K (reporting date: 2019-08-29), 10-Q (reporting date: 2019-05-30), 10-Q (reporting date: 2019-02-28), 10-Q (reporting date: 2018-11-29).

1 Q3 2025 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =

2 Click competitor name to see calculations.


Receivables turnover ratio
The receivables turnover ratio demonstrates a fluctuating but generally declining trend over the analyzed periods. Starting from 7.33 in November 2018, the ratio declines to lower values around 5.2 to 6 between late 2019 and early 2022. There is an observed spike to 8.18 and then a significant peak of 10.12 in mid-2022, indicating a period of more efficient receivables collection during this time. However, after this peak, a downward trend resumes, with the turnover ratio decreasing steadily to around 3.8 by August 2024 before a slight recovery to 4.55 in May 2025. This pattern suggests variability in how quickly receivables are converted to cash, with recent periods indicating slower collections compared to earlier years.
Average receivable collection period (days)
The average receivable collection period exhibits an inverse pattern relative to the receivables turnover ratio, as expected. Initially, the days outstanding increase from around 50 days in late 2018 to a peak near 70 days between late 2019 through 2021. A notable improvement is evident around early to mid-2022, where collection days drop sharply from 70 to 36 days, corresponding with the peak in turnover ratio. Following this improvement, the collection period lengthens again, reaching a high of 96 days near mid-2024, indicating slower collections. By May 2025, there is a moderate improvement to 80 days, but this remains elevated compared to earlier years. The variability in collection periods suggests fluctuations in credit policies or customer payment behavior over time.

Operating Cycle

Micron Technology Inc., operating cycle calculation (quarterly data)

No. days

Microsoft Excel
May 29, 2025 Feb 27, 2025 Nov 28, 2024 Aug 29, 2024 May 30, 2024 Feb 29, 2024 Nov 30, 2023 Aug 31, 2023 Jun 1, 2023 Mar 2, 2023 Dec 1, 2022 Sep 1, 2022 Jun 2, 2022 Mar 3, 2022 Dec 2, 2021 Sep 2, 2021 Jun 3, 2021 Mar 4, 2021 Dec 3, 2020 Sep 3, 2020 May 28, 2020 Feb 27, 2020 Nov 28, 2019 Aug 29, 2019 May 30, 2019 Feb 28, 2019 Nov 29, 2018
Selected Financial Data
Average inventory processing period
Average receivable collection period
Short-term Activity Ratio
Operating cycle1
Benchmarks
Operating Cycle, Competitors2
Advanced Micro Devices Inc.
Analog Devices Inc.
Applied Materials Inc.
Broadcom Inc.
Intel Corp.
KLA Corp.
Lam Research Corp.
NVIDIA Corp.
Texas Instruments Inc.

Based on: 10-Q (reporting date: 2025-05-29), 10-Q (reporting date: 2025-02-27), 10-Q (reporting date: 2024-11-28), 10-K (reporting date: 2024-08-29), 10-Q (reporting date: 2024-05-30), 10-Q (reporting date: 2024-02-29), 10-Q (reporting date: 2023-11-30), 10-K (reporting date: 2023-08-31), 10-Q (reporting date: 2023-06-01), 10-Q (reporting date: 2023-03-02), 10-Q (reporting date: 2022-12-01), 10-K (reporting date: 2022-09-01), 10-Q (reporting date: 2022-06-02), 10-Q (reporting date: 2022-03-03), 10-Q (reporting date: 2021-12-02), 10-K (reporting date: 2021-09-02), 10-Q (reporting date: 2021-06-03), 10-Q (reporting date: 2021-03-04), 10-Q (reporting date: 2020-12-03), 10-K (reporting date: 2020-09-03), 10-Q (reporting date: 2020-05-28), 10-Q (reporting date: 2020-02-27), 10-Q (reporting date: 2019-11-28), 10-K (reporting date: 2019-08-29), 10-Q (reporting date: 2019-05-30), 10-Q (reporting date: 2019-02-28), 10-Q (reporting date: 2018-11-29).

1 Q3 2025 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= + =

2 Click competitor name to see calculations.


The analysis of the quarterly financial data reveals notable trends in the company's operational efficiency and working capital management over the examined periods.

Average Inventory Processing Period
The average inventory processing period exhibits a fluctuating trend with initial values around 147 days, slightly decreasing to a low of 95 days by September 2021. Subsequently, there is an observable upward movement reaching a peak near 192 days around March 2023. Towards the latest data points, the period moderately declines again to approximately 150 days by May 2025. This pattern suggests variable inventory turnover rates with phases of improving efficiency interspersed with periods of slower inventory processing.
Average Receivable Collection Period
This metric shows moderate fluctuations with periods ranging from 50 to 96 days. Early in the series, the collection period increased from about 50 days to 70 days, indicating a slowdown in the receivables turnover. Following this, there is a significant drop to a low near 36 days by June 2023, reflecting enhanced collections efficiency. However, the latter periods exhibit an uptrend again, rising above 90 days before slightly decreasing to around 80 days by the last data point. Overall, this indicates variability in the company's ability to manage its receivables and cash inflow timing.
Operating Cycle
The operating cycle, combining inventory and receivables periods, fluctuates between roughly 158 and 262 days. Initially stable around the 197-day mark, it drops to a minimum near 158 days by mid-2021, coinciding with improved inventory and receivables management. Thereafter, the operating cycle lengthens substantially, peaking in the range of 254 to 262 days between early 2024 and mid-2025. This extended cycle suggests increased capital tied up in operational processes during this timeframe, potentially impacting liquidity or operational flexibility.

In summary, the data indicates periods of both improvement and deterioration in inventory and receivable management, impacting the overall operating cycle. The long-term trend reflects volatility, with recent periods showing extended operating cycles mainly driven by increases in both inventory holding and receivables collection durations. Continuous monitoring and management focus on these areas would be essential to optimize working capital efficiency.