Analysis of Short-term (Operating) Activity Ratios
Quarterly Data
Activity ratios measure how efficiently a company performs day-to-day tasks, such us the collection of receivables and management of inventory.
Short-term Activity Ratios (Summary)
Western Digital Corp., short-term (operating) activity ratios (quarterly data)
Based on: 10-Q (reporting date: 2023-12-29), 10-Q (reporting date: 2023-09-29), 10-K (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-Q (reporting date: 2022-12-30), 10-Q (reporting date: 2022-09-30), 10-K (reporting date: 2022-07-01), 10-Q (reporting date: 2022-04-01), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-10-01), 10-K (reporting date: 2021-07-02), 10-Q (reporting date: 2021-04-02), 10-Q (reporting date: 2021-01-01), 10-Q (reporting date: 2020-10-02), 10-K (reporting date: 2020-07-03), 10-Q (reporting date: 2020-04-03), 10-Q (reporting date: 2020-01-03), 10-Q (reporting date: 2019-10-04), 10-K (reporting date: 2019-06-28), 10-Q (reporting date: 2019-03-29), 10-Q (reporting date: 2018-12-28), 10-Q (reporting date: 2018-09-28), 10-K (reporting date: 2018-06-29), 10-Q (reporting date: 2018-03-30), 10-Q (reporting date: 2017-12-29), 10-Q (reporting date: 2017-09-29).
The analysis of the financial ratios over the reported periods reveals several noteworthy trends pertaining to the company's operational efficiency and working capital management.
- Inventory Turnover
- The inventory turnover ratio started at 4.4 and generally declined over time, reaching a low near 2.75 before a slight recovery to 3.2 by the last reported period. This trend suggests a slowing movement of inventory, indicating that the company is taking longer to sell its inventory, which may reflect changes in demand or inventory management challenges.
- Receivables Turnover
- The receivables turnover ratio showed volatility, initially increasing from 9.4 to a peak of 14.76, indicating faster collection early in the period, but subsequently decreased to values near 7.39–7.81 in the later periods. This suggests a slowdown in the efficiency of collecting receivables, potentially increasing the risk of cash flow constraints.
- Payables Turnover
- This ratio exhibited fluctuations with an increasing trend early on, peaking at 9.74, indicating quicker payments to suppliers. However, it later declined to about 6.84, indicating slower payments and potentially extended credit terms or liquidity management efforts.
- Working Capital Turnover
- The working capital turnover ratio overall experienced an upward trend, moving from about 3.34 to a peak of 6.35 before declining in the final period. An improving ratio generally signals better utilization of working capital to generate sales, though the late-period decline warrants attention.
- Average Inventory Processing Period
- The average number of days inventory is held increased significantly from 83 to a peak of 133 days, reflecting the previously noted decline in inventory turnover. This extension in holding period indicates slower inventory movement, which could impact storage costs and obsolescence risk.
- Average Receivable Collection Period
- The average collection period varied, initially declining to 25 days, indicating efficient collection, but then progressively increased to near 53 days, suggesting delays in customer payments and potentially strained credit control processes.
- Operating Cycle
- The operating cycle lengthened from 122 days to a high of 176 days, signaling an overall increase in the time taken from inventory acquisition through receivables collection. This extension mirrors the slower inventory turnover and receivables collection and could have adverse effects on liquidity.
- Average Payables Payment Period
- The payment period to suppliers fluctuated, initially shortening from 64 to 37 days, followed by an increase to about 57 days. The variations indicate adjustments in payable management, possibly balancing supplier relationships with internal cash management.
- Cash Conversion Cycle
- The cash conversion cycle showed a clear increase from 58 days to a peak of 131 days before slightly decreasing to 110 days. This trend reflects the combined effect of slower inventory turnover, longer receivables collection, and varying payables payment terms, highlighting a growing duration between cash outlays and cash inflows that may necessitate focused liquidity management.
In summary, the data indicates a general lengthening of operational and cash flow cycles over the examined periods, with specific signs of slowing inventory movement and receivables collection. While working capital utilization showed improvement mid-period, recent declines and extended cash conversion cycles suggest emerging challenges in working capital efficiency and liquidity that may require strategic attention.
Turnover Ratios
Average No. Days
Inventory Turnover
Western Digital Corp., inventory turnover calculation (quarterly data)
| Dec 29, 2023 | Sep 29, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 30, 2022 | Sep 30, 2022 | Jul 1, 2022 | Apr 1, 2022 | Dec 31, 2021 | Oct 1, 2021 | Jul 2, 2021 | Apr 2, 2021 | Jan 1, 2021 | Oct 2, 2020 | Jul 3, 2020 | Apr 3, 2020 | Jan 3, 2020 | Oct 4, 2019 | Jun 28, 2019 | Mar 29, 2019 | Dec 28, 2018 | Sep 28, 2018 | Jun 29, 2018 | Mar 30, 2018 | Dec 29, 2017 | Sep 29, 2017 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||||||||||
| Cost of revenue | 2,540) | 2,651) | 2,580) | 2,517) | 2,579) | 2,755) | 3,083) | 3,200) | 3,250) | 3,386) | 3,354) | 3,046) | 2,983) | 3,018) | 3,204) | 3,170) | 3,299) | 3,282) | 3,169) | 3,095) | 3,189) | 3,364) | 3,265) | 3,086) | 3,323) | 3,268) | ||||||||
| Inventories | 3,216) | 3,497) | 3,698) | 3,979) | 3,773) | 3,862) | 3,638) | 3,661) | 3,647) | 3,544) | 3,616) | 3,683) | 3,576) | 3,355) | 3,070) | 3,091) | 3,122) | 3,287) | 3,283) | 3,440) | 3,427) | 3,119) | 2,944) | 2,670) | 2,281) | 2,302) | ||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||||||
| Inventory turnover1 | 3.20 | 2.95 | 2.82 | 2.75 | 3.08 | 3.18 | 3.55 | 3.60 | 3.57 | 3.60 | 3.43 | 3.33 | 3.46 | 3.78 | 4.22 | 4.18 | 4.11 | 3.87 | 3.90 | 3.75 | 3.77 | 4.18 | 4.40 | — | — | — | ||||||||
| Benchmarks | ||||||||||||||||||||||||||||||||||
| Inventory Turnover, Competitors2 | ||||||||||||||||||||||||||||||||||
| Apple Inc. | 33.32 | 32.57 | 33.82 | 29.54 | 29.24 | 32.36 | 45.20 | 40.43 | 40.07 | 36.69 | 32.37 | 39.55 | 37.48 | 36.21 | 41.75 | 42.55 | 49.75 | 40.54 | 39.40 | — | — | — | — | — | — | — | ||||||||
| Arista Networks Inc. | 1.23 | 1.11 | 1.15 | 1.16 | 1.12 | 1.15 | 1.32 | 1.36 | 1.53 | 1.65 | 1.64 | 1.74 | 1.75 | 1.85 | 1.74 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Cisco Systems Inc. | 6.38 | 6.30 | 5.83 | 6.01 | 6.45 | 7.41 | 7.52 | 8.52 | 9.19 | 10.06 | 11.50 | 11.15 | 11.98 | 13.25 | 13.74 | 14.85 | 13.73 | 14.14 | 13.91 | — | — | — | — | — | — | — | ||||||||
| Dell Technologies Inc. | 20.02 | 18.72 | 16.67 | 13.40 | 14.38 | 13.11 | 13.45 | 13.76 | 16.63 | 17.53 | 19.05 | 18.62 | 17.40 | 17.47 | 19.27 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Super Micro Computer Inc. | 3.14 | 2.97 | 4.04 | 3.49 | 3.84 | 2.88 | 2.84 | 2.50 | 2.58 | 2.77 | 2.90 | 3.18 | 3.39 | 3.59 | 3.30 | 3.19 | 3.91 | 4.12 | 4.48 | — | — | — | — | — | — | — | ||||||||
Based on: 10-Q (reporting date: 2023-12-29), 10-Q (reporting date: 2023-09-29), 10-K (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-Q (reporting date: 2022-12-30), 10-Q (reporting date: 2022-09-30), 10-K (reporting date: 2022-07-01), 10-Q (reporting date: 2022-04-01), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-10-01), 10-K (reporting date: 2021-07-02), 10-Q (reporting date: 2021-04-02), 10-Q (reporting date: 2021-01-01), 10-Q (reporting date: 2020-10-02), 10-K (reporting date: 2020-07-03), 10-Q (reporting date: 2020-04-03), 10-Q (reporting date: 2020-01-03), 10-Q (reporting date: 2019-10-04), 10-K (reporting date: 2019-06-28), 10-Q (reporting date: 2019-03-29), 10-Q (reporting date: 2018-12-28), 10-Q (reporting date: 2018-09-28), 10-K (reporting date: 2018-06-29), 10-Q (reporting date: 2018-03-30), 10-Q (reporting date: 2017-12-29), 10-Q (reporting date: 2017-09-29).
1 Q2 2024 Calculation
Inventory turnover
= (Cost of revenueQ2 2024
+ Cost of revenueQ1 2024
+ Cost of revenueQ4 2023
+ Cost of revenueQ3 2023)
÷ Inventories
= (2,540 + 2,651 + 2,580 + 2,517)
÷ 3,216 = 3.20
2 Click competitor name to see calculations.
- Cost of Revenue
- The cost of revenue showed fluctuations across the observed periods with no consistent upward or downward trend. Initially, costs were around the low 3,000s million USD and exhibited modest oscillations throughout. Notably, there was a notable decrease from a peak of approximately 3,386 million USD in December 2021 down to approximately 2,540 million USD by December 2023, indicating a progressive reduction in cost structure over the last two years.
- Inventories
- Inventory values experienced an overall increasing trend from late 2017 through early 2022, starting around 2,300 million USD and reaching a peak near 3,862 million USD by December 2022. Subsequent to this peak, inventories started to decline, dropping to about 3,216 million USD by the end of 2023. This pattern reflects an accumulation of stock over several years, followed by a gradual inventory drawdown in the most recent quarters.
- Inventory Turnover
- Inventory turnover ratios, available from early 2018 onward, reveal a decreasing trend, implying a slower rate of inventory turnover over time. Starting at a relatively high turnover of 4.4 in March 2018, the ratio gradually declined to a low of 2.75 in September 2022 before modestly recovering to around 3.2 by December 2023. This suggests that, over time, inventory was held for longer periods before being sold or used.
- Overall Insights
- The company's cost of revenue and inventory levels have displayed inverse movements in recent years, with costs decreasing while inventories initially built up and then began to reduce. The declining inventory turnover ratio suggests increasing inventory holding periods which might reflect changes in demand, supply chain dynamics, or strategic stocking decisions. The recent recovery in turnover ratio hints at improved inventory management or increased sales velocity in the latter part of 2023.
Receivables Turnover
Western Digital Corp., receivables turnover calculation (quarterly data)
| Dec 29, 2023 | Sep 29, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 30, 2022 | Sep 30, 2022 | Jul 1, 2022 | Apr 1, 2022 | Dec 31, 2021 | Oct 1, 2021 | Jul 2, 2021 | Apr 2, 2021 | Jan 1, 2021 | Oct 2, 2020 | Jul 3, 2020 | Apr 3, 2020 | Jan 3, 2020 | Oct 4, 2019 | Jun 28, 2019 | Mar 29, 2019 | Dec 28, 2018 | Sep 28, 2018 | Jun 29, 2018 | Mar 30, 2018 | Dec 29, 2017 | Sep 29, 2017 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||||||||||
| Revenue, net | 3,032) | 2,750) | 2,672) | 2,803) | 3,107) | 3,736) | 4,528) | 4,381) | 4,833) | 5,051) | 4,920) | 4,137) | 3,943) | 3,922) | 4,287) | 4,175) | 4,234) | 4,040) | 3,634) | 3,674) | 4,233) | 5,028) | 5,117) | 5,013) | 5,336) | 5,181) | ||||||||
| Accounts receivable, net | 1,523) | 1,451) | 1,598) | 1,591) | 1,905) | 2,422) | 2,804) | 2,353) | 2,743) | 2,446) | 2,257) | 1,905) | 1,833) | 2,097) | 2,379) | 1,978) | 1,791) | 1,448) | 1,204) | 1,223) | 1,715) | 2,219) | 2,197) | 2,011) | 2,052) | 2,101) | ||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||||||
| Receivables turnover1 | 7.39 | 7.81 | 7.71 | 8.91 | 8.27 | 7.22 | 6.70 | 8.15 | 6.91 | 7.38 | 7.50 | 8.55 | 8.91 | 7.92 | 7.03 | 8.13 | 8.70 | 10.76 | 13.76 | 14.76 | 11.31 | 9.24 | 9.40 | — | — | — | ||||||||
| Benchmarks | ||||||||||||||||||||||||||||||||||
| Receivables Turnover, Competitors2 | ||||||||||||||||||||||||||||||||||
| Apple Inc. | 17.48 | 16.63 | 12.99 | 19.64 | 21.47 | 16.32 | 13.99 | 17.77 | 18.55 | 12.52 | 13.92 | 19.87 | 17.59 | 10.85 | 17.03 | 15.31 | 17.04 | 12.77 | 11.35 | — | — | — | — | — | — | — | ||||||||
| Arista Networks Inc. | 5.14 | 5.58 | 5.72 | 6.71 | 6.75 | 5.63 | 4.75 | 6.03 | 5.98 | 4.87 | 5.71 | 7.01 | 7.22 | 6.47 | 5.95 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Cisco Systems Inc. | 11.72 | 12.01 | 9.74 | 10.76 | 10.15 | 9.61 | 7.79 | 8.92 | 8.59 | 9.57 | 8.64 | 11.04 | 11.15 | 12.08 | 9.01 | 11.07 | 11.91 | 10.66 | 9.45 | — | — | — | — | — | — | — | ||||||||
| Dell Technologies Inc. | 9.04 | 10.33 | 8.20 | 9.21 | 7.96 | 8.85 | 7.84 | 7.01 | 7.46 | 8.70 | 7.37 | 8.10 | 7.86 | 8.53 | 7.38 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Super Micro Computer Inc. | 6.16 | 8.74 | 6.20 | 9.78 | 8.65 | 8.17 | 6.23 | 6.81 | 8.38 | 8.36 | 7.67 | 8.31 | 10.10 | 10.23 | 8.27 | 9.90 | 9.07 | 9.35 | 8.89 | — | — | — | — | — | — | — | ||||||||
Based on: 10-Q (reporting date: 2023-12-29), 10-Q (reporting date: 2023-09-29), 10-K (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-Q (reporting date: 2022-12-30), 10-Q (reporting date: 2022-09-30), 10-K (reporting date: 2022-07-01), 10-Q (reporting date: 2022-04-01), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-10-01), 10-K (reporting date: 2021-07-02), 10-Q (reporting date: 2021-04-02), 10-Q (reporting date: 2021-01-01), 10-Q (reporting date: 2020-10-02), 10-K (reporting date: 2020-07-03), 10-Q (reporting date: 2020-04-03), 10-Q (reporting date: 2020-01-03), 10-Q (reporting date: 2019-10-04), 10-K (reporting date: 2019-06-28), 10-Q (reporting date: 2019-03-29), 10-Q (reporting date: 2018-12-28), 10-Q (reporting date: 2018-09-28), 10-K (reporting date: 2018-06-29), 10-Q (reporting date: 2018-03-30), 10-Q (reporting date: 2017-12-29), 10-Q (reporting date: 2017-09-29).
1 Q2 2024 Calculation
Receivables turnover
= (Revenue, netQ2 2024
+ Revenue, netQ1 2024
+ Revenue, netQ4 2023
+ Revenue, netQ3 2023)
÷ Accounts receivable, net
= (3,032 + 2,750 + 2,672 + 2,803)
÷ 1,523 = 7.39
2 Click competitor name to see calculations.
The financial data reveal a varying trend in net revenue over the analyzed periods. Initially, net revenue remained relatively stable between approximately $5.0 billion and $5.3 billion through late 2017 to mid-2018. Subsequently, there was a noticeable decline starting in the latter half of 2018, bottoming out at around $2.7 billion by late 2023. This indicates a clear downward trend in revenue over the longer term, despite some intermittent recoveries, such as a peak near $5.1 billion in late 2021.
Accounts receivable exhibited a somewhat fluctuating pattern, with values ranging roughly between $1.2 billion and $2.7 billion. Early periods saw a decrease from over $2.1 billion to approximately $1.2 billion in early to mid-2019. Afterward, accounts receivable progressively increased, reaching a peak around $2.8 billion in mid-2022, before declining again towards $1.5 billion by the end of 2023. These fluctuations may reflect changes in credit policies, customer payment behavior, or sales cycles.
Receivables turnover ratios, available from early 2018 onward, indicate considerable variation. The ratio was highest in the first half of 2019, peaking at approximately 14.76, signifying efficient collection of receivables during that period. Following this peak, the turnover ratio steadily declined, stabilizing in the range of roughly 6.7 to 8.9 in more recent quarters. This downward movement suggests a lengthening collection period or less effective receivables management as time progressed.
- Revenue Trends
- Revenue showed initial stability with small fluctuations, followed by a marked decline from late 2018 onward, hitting a low point near the end of the observed period. The brief resurgence around late 2021 did not reverse the overall downward trajectory.
- Accounts Receivable Variations
- The accounts receivable figures moved inversely at times relative to revenue, first declining markedly, then rising to a peak in mid-2022 before dropping again. This dynamic may suggest changes in credit extension or payment cycles that affect working capital.
- Receivables Turnover Fluctuations
- Receivables turnover ratio peaked in early 2019, indicating strong collection efficiency, but declined subsequently, stabilizing at lower levels. This trend may imply deteriorating collection effectiveness or elongation of the average time to collect receivables in recent periods.
Overall, the data highlight challenges in sustaining revenue growth and maintaining efficient receivables management. The negative revenue trend alongside fluctuations in accounts receivable and receivables turnover ratio suggests potential liquidity and operational issues that warrant careful attention.
Payables Turnover
Western Digital Corp., payables turnover calculation (quarterly data)
| Dec 29, 2023 | Sep 29, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 30, 2022 | Sep 30, 2022 | Jul 1, 2022 | Apr 1, 2022 | Dec 31, 2021 | Oct 1, 2021 | Jul 2, 2021 | Apr 2, 2021 | Jan 1, 2021 | Oct 2, 2020 | Jul 3, 2020 | Apr 3, 2020 | Jan 3, 2020 | Oct 4, 2019 | Jun 28, 2019 | Mar 29, 2019 | Dec 28, 2018 | Sep 28, 2018 | Jun 29, 2018 | Mar 30, 2018 | Dec 29, 2017 | Sep 29, 2017 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||||||||||
| Cost of revenue | 2,540) | 2,651) | 2,580) | 2,517) | 2,579) | 2,755) | 3,083) | 3,200) | 3,250) | 3,386) | 3,354) | 3,046) | 2,983) | 3,018) | 3,204) | 3,170) | 3,299) | 3,282) | 3,169) | 3,095) | 3,189) | 3,364) | 3,265) | 3,086) | 3,323) | 3,268) | ||||||||
| Accounts payable | 1,504) | 1,294) | 1,293) | 1,307) | 1,193) | 1,686) | 1,902) | 1,836) | 2,022) | 1,896) | 1,934) | 1,807) | 1,939) | 1,949) | 1,945) | 1,786) | 1,736) | 1,724) | 1,567) | 1,577) | 1,925) | 2,081) | 2,265) | 2,134) | 1,921) | 2,066) | ||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||||||
| Payables turnover1 | 6.84 | 7.98 | 8.07 | 8.37 | 9.74 | 7.29 | 6.79 | 7.18 | 6.45 | 6.73 | 6.41 | 6.78 | 6.38 | 6.51 | 6.66 | 7.23 | 7.40 | 7.39 | 8.18 | 8.19 | 6.70 | 6.27 | 5.71 | — | — | — | ||||||||
| Benchmarks | ||||||||||||||||||||||||||||||||||
| Payables Turnover, Competitors2 | ||||||||||||||||||||||||||||||||||
| Apple Inc. | 4.54 | 3.65 | 3.42 | 4.65 | 5.10 | 3.81 | 3.49 | 4.54 | 4.15 | 2.90 | 3.89 | 5.07 | 4.88 | 2.82 | 4.01 | 4.79 | 5.12 | 3.68 | 3.50 | — | — | — | — | — | — | — | ||||||||
| Arista Networks Inc. | 7.63 | 10.09 | 5.13 | 8.16 | 5.95 | 5.84 | 7.33 | 5.39 | 4.74 | 5.61 | 5.27 | 7.39 | 6.54 | 6.52 | 6.23 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Cisco Systems Inc. | 11.08 | 10.11 | 9.19 | 8.55 | 8.69 | 8.53 | 8.47 | 8.31 | 9.00 | 8.15 | 7.59 | 7.22 | 9.22 | 7.53 | 7.94 | 7.52 | 9.60 | 9.43 | 9.34 | — | — | — | — | — | — | — | ||||||||
| Dell Technologies Inc. | 3.59 | 4.22 | 4.28 | 3.67 | 3.34 | 3.22 | 2.92 | 2.80 | 3.05 | 3.11 | 2.99 | 3.19 | 3.21 | 3.43 | 3.15 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Super Micro Computer Inc. | 6.13 | 5.63 | 7.52 | 8.38 | 9.76 | 6.38 | 6.71 | 5.09 | 5.18 | 5.82 | 4.94 | 6.18 | 6.91 | 8.33 | 6.74 | 5.97 | 7.02 | 8.51 | 8.34 | — | — | — | — | — | — | — | ||||||||
Based on: 10-Q (reporting date: 2023-12-29), 10-Q (reporting date: 2023-09-29), 10-K (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-Q (reporting date: 2022-12-30), 10-Q (reporting date: 2022-09-30), 10-K (reporting date: 2022-07-01), 10-Q (reporting date: 2022-04-01), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-10-01), 10-K (reporting date: 2021-07-02), 10-Q (reporting date: 2021-04-02), 10-Q (reporting date: 2021-01-01), 10-Q (reporting date: 2020-10-02), 10-K (reporting date: 2020-07-03), 10-Q (reporting date: 2020-04-03), 10-Q (reporting date: 2020-01-03), 10-Q (reporting date: 2019-10-04), 10-K (reporting date: 2019-06-28), 10-Q (reporting date: 2019-03-29), 10-Q (reporting date: 2018-12-28), 10-Q (reporting date: 2018-09-28), 10-K (reporting date: 2018-06-29), 10-Q (reporting date: 2018-03-30), 10-Q (reporting date: 2017-12-29), 10-Q (reporting date: 2017-09-29).
1 Q2 2024 Calculation
Payables turnover
= (Cost of revenueQ2 2024
+ Cost of revenueQ1 2024
+ Cost of revenueQ4 2023
+ Cost of revenueQ3 2023)
÷ Accounts payable
= (2,540 + 2,651 + 2,580 + 2,517)
÷ 1,504 = 6.84
2 Click competitor name to see calculations.
The cost of revenue for the company exhibits moderate fluctuations over the analyzed period. Starting at approximately $3.27 billion in late September 2017, it remains relatively stable with minor ups and downs through 2018 and 2019, peaking around $3.38 billion in the fourth quarter of 2021. Notably, from early 2022 onwards, there is a discernible downward trend in cost of revenue, reaching its lowest point near $2.54 billion by the end of 2023. This reduction suggests a potential improvement in cost management or changes in the company's operational scale or product mix during this later period.
Accounts payable values show more variability across the quarters. Initially recorded at just above $2.06 billion in September 2017, the figures decline through the first half of 2019, dipping below $1.6 billion mid-year 2019. Subsequently, accounts payable increase again, peaking at around $2.02 billion in the fourth quarter of 2021. From 2022 onwards, there is again a downward movement, with accounts payable falling markedly to approximately $1.29 billion by September 2023 before a slight uptick in the final quarter of 2023. This pattern indicates fluctuations in the company's short-term obligations or payment cycles that may correspond to purchasing or supplier arrangements.
The payables turnover ratio, reported only from June 2018 onward, exhibits an overall upward trend with some variability. Beginning at approximately 5.71 in mid-2018, this metric increases generally through the periods, reaching values around 6.78 to 7.4 during 2020 and 2021. This indicates an improvement in the rate at which the company settles its payables relative to cost of revenue. Further increases followed, with the ratio peaking significantly at 9.74 in the first quarter of 2023, suggesting an accelerated payoff of accounts payable during that period. Thereafter, the ratio moderates to levels between about 6.84 and 8.37 by the end of 2023. These fluctuations could reflect changes in payment policies, supplier negotiations, or cash flow management strategies over time.
In summary, the financial data reflect a trend of decreasing cost of revenue and accounts payable in the most recent years, coupled with variable but generally improving payables turnover. These developments may indicate enhanced cost control measures and more efficient management of supplier payments, impacting the company's operational liquidity and supplier relationships. Enhanced payables turnover, particularly the peak seen in early 2023, points toward a potentially more aggressive payments approach, which could influence working capital dynamics.
Working Capital Turnover
Western Digital Corp., working capital turnover calculation (quarterly data)
| Dec 29, 2023 | Sep 29, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 30, 2022 | Sep 30, 2022 | Jul 1, 2022 | Apr 1, 2022 | Dec 31, 2021 | Oct 1, 2021 | Jul 2, 2021 | Apr 2, 2021 | Jan 1, 2021 | Oct 2, 2020 | Jul 3, 2020 | Apr 3, 2020 | Jan 3, 2020 | Oct 4, 2019 | Jun 28, 2019 | Mar 29, 2019 | Dec 28, 2018 | Sep 28, 2018 | Jun 29, 2018 | Mar 30, 2018 | Dec 29, 2017 | Sep 29, 2017 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||||||||||
| Current assets | 7,838) | 7,577) | 7,886) | 8,483) | 8,381) | 9,071) | 9,453) | 9,178) | 9,535) | 9,856) | 9,757) | 9,032) | 9,109) | 9,005) | 9,048) | 8,553) | 8,627) | 8,500) | 8,477) | 8,902) | 9,742) | 10,571) | 10,638) | 10,164) | 11,113) | 11,820) | ||||||||
| Less: Current liabilities | 4,693) | 5,792) | 5,434) | 5,261) | 4,382) | 4,966) | 5,237) | 4,397) | 4,929) | 4,709) | 4,870) | 4,501) | 4,526) | 4,429) | 4,406) | 4,471) | 4,482) | 4,288) | 3,817) | 4,212) | 4,350) | 4,385) | 4,456) | 4,259) | 4,353) | 4,469) | ||||||||
| Working capital | 3,145) | 1,785) | 2,452) | 3,222) | 3,999) | 4,105) | 4,216) | 4,781) | 4,606) | 5,147) | 4,887) | 4,531) | 4,583) | 4,576) | 4,642) | 4,082) | 4,145) | 4,212) | 4,660) | 4,690) | 5,392) | 6,186) | 6,182) | 5,905) | 6,760) | 7,351) | ||||||||
| Revenue, net | 3,032) | 2,750) | 2,672) | 2,803) | 3,107) | 3,736) | 4,528) | 4,381) | 4,833) | 5,051) | 4,920) | 4,137) | 3,943) | 3,922) | 4,287) | 4,175) | 4,234) | 4,040) | 3,634) | 3,674) | 4,233) | 5,028) | 5,117) | 5,013) | 5,336) | 5,181) | ||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||||||
| Working capital turnover1 | 3.58 | 6.35 | 5.02 | 4.40 | 3.94 | 4.26 | 4.46 | 4.01 | 4.11 | 3.51 | 3.46 | 3.60 | 3.56 | 3.63 | 3.61 | 3.94 | 3.76 | 3.70 | 3.56 | 3.85 | 3.60 | 3.31 | 3.34 | — | — | — | ||||||||
| Benchmarks | ||||||||||||||||||||||||||||||||||
| Working Capital Turnover, Competitors2 | ||||||||||||||||||||||||||||||||||
| Apple Inc. | 83.07 | 39.69 | — | — | — | — | — | — | — | 67.80 | 39.10 | 52.06 | 21.58 | 13.62 | 7.16 | 6.12 | 5.62 | 4.38 | 4.56 | — | — | — | — | — | — | — | ||||||||
| Arista Networks Inc. | 0.82 | 0.85 | 0.90 | 0.96 | 1.01 | 1.04 | 1.03 | 1.04 | 1.01 | 0.85 | 0.80 | 0.76 | 0.76 | 0.77 | 0.76 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Cisco Systems Inc. | 5.08 | 4.60 | 4.73 | 4.89 | 4.72 | 4.65 | 4.65 | 4.36 | 4.74 | 3.54 | 3.88 | 3.82 | 2.89 | 3.00 | 2.70 | 3.29 | 2.87 | 3.04 | 3.24 | — | — | — | — | — | — | — | ||||||||
| Dell Technologies Inc. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Super Micro Computer Inc. | 3.25 | 3.76 | 3.95 | 4.05 | 3.84 | 3.94 | 3.89 | 3.91 | 3.81 | 4.09 | 3.96 | 3.95 | 3.74 | 3.71 | 3.77 | 3.82 | 3.85 | 4.00 | 4.29 | — | — | — | — | — | — | — | ||||||||
Based on: 10-Q (reporting date: 2023-12-29), 10-Q (reporting date: 2023-09-29), 10-K (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-Q (reporting date: 2022-12-30), 10-Q (reporting date: 2022-09-30), 10-K (reporting date: 2022-07-01), 10-Q (reporting date: 2022-04-01), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-10-01), 10-K (reporting date: 2021-07-02), 10-Q (reporting date: 2021-04-02), 10-Q (reporting date: 2021-01-01), 10-Q (reporting date: 2020-10-02), 10-K (reporting date: 2020-07-03), 10-Q (reporting date: 2020-04-03), 10-Q (reporting date: 2020-01-03), 10-Q (reporting date: 2019-10-04), 10-K (reporting date: 2019-06-28), 10-Q (reporting date: 2019-03-29), 10-Q (reporting date: 2018-12-28), 10-Q (reporting date: 2018-09-28), 10-K (reporting date: 2018-06-29), 10-Q (reporting date: 2018-03-30), 10-Q (reporting date: 2017-12-29), 10-Q (reporting date: 2017-09-29).
1 Q2 2024 Calculation
Working capital turnover
= (Revenue, netQ2 2024
+ Revenue, netQ1 2024
+ Revenue, netQ4 2023
+ Revenue, netQ3 2023)
÷ Working capital
= (3,032 + 2,750 + 2,672 + 2,803)
÷ 3,145 = 3.58
2 Click competitor name to see calculations.
The financial data reveals several important trends in the working capital, net revenue, and working capital turnover ratio over the analyzed periods.
- Working Capital
- The working capital shows a general declining trend across the observed periods. Starting from a high point of 7,351 million US dollars in late September 2017, it decreased steadily with some minor fluctuations. By the end of December 2023, the figure fell to 3,145 million US dollars. Notably, there was a significant reduction observed from late 2021 through 2023, marking a drop from over 5,000 million to the mid-thousands, indicating tightening liquidity or a possible change in asset and liability management practices.
- Net Revenue
- Net revenue exhibited variability but tended to decline over the longer term. It started at approximately 5,181 million US dollars in September 2017 and maintained relative stability through to late 2018 with minor fluctuations. However, from late 2018 onward, there was a noticeable downward movement, dropping to around 3,032 million US dollars at the end of 2023. Despite intermittent quarters of stabilization or mild growth, the overall trajectory was downward, reflecting potential challenges in sales volume, pricing, or market demand.
- Working Capital Turnover Ratio
- The working capital turnover ratio, which measures the efficiency of using working capital to generate revenue, has shown a generally increasing trend. Early data from mid-2018 showed values around 3.3 to 3.6, increasing gradually through the periods. This ratio peaked significantly in late 2022, reaching values above 6.0, before retreating somewhat by the end of 2023 to 3.58. The surge implies improved efficiency in capital use or a reduction in working capital relative to revenue. However, the decrease near the end points to some possible rebalancing or operational changes.
In summary, while revenue and working capital have generally decreased over the timeline, the improvement in the working capital turnover ratio suggests a heightened focus on optimizing the use of available capital to support revenue generation. The data points to tighter capital management possibly driven by market conditions or internal policy adjustments, emphasizing efficient operational control amid revenue pressures.
Average Inventory Processing Period
Western Digital Corp., average inventory processing period calculation (quarterly data)
| Dec 29, 2023 | Sep 29, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 30, 2022 | Sep 30, 2022 | Jul 1, 2022 | Apr 1, 2022 | Dec 31, 2021 | Oct 1, 2021 | Jul 2, 2021 | Apr 2, 2021 | Jan 1, 2021 | Oct 2, 2020 | Jul 3, 2020 | Apr 3, 2020 | Jan 3, 2020 | Oct 4, 2019 | Jun 28, 2019 | Mar 29, 2019 | Dec 28, 2018 | Sep 28, 2018 | Jun 29, 2018 | Mar 30, 2018 | Dec 29, 2017 | Sep 29, 2017 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||||||||
| Inventory turnover | 3.20 | 2.95 | 2.82 | 2.75 | 3.08 | 3.18 | 3.55 | 3.60 | 3.57 | 3.60 | 3.43 | 3.33 | 3.46 | 3.78 | 4.22 | 4.18 | 4.11 | 3.87 | 3.90 | 3.75 | 3.77 | 4.18 | 4.40 | — | — | — | ||||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||||||||
| Average inventory processing period1 | 114 | 124 | 129 | 133 | 119 | 115 | 103 | 101 | 102 | 101 | 106 | 110 | 105 | 96 | 86 | 87 | 89 | 94 | 93 | 97 | 97 | 87 | 83 | — | — | — | ||||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||||||||
| Average Inventory Processing Period, Competitors2 | ||||||||||||||||||||||||||||||||||
| Apple Inc. | 11 | 11 | 11 | 12 | 12 | 11 | 8 | 9 | 9 | 10 | 11 | 9 | 10 | 10 | 9 | 9 | 7 | 9 | 9 | — | — | — | — | — | — | — | ||||||||
| Arista Networks Inc. | 298 | 328 | 318 | 315 | 325 | 318 | 276 | 268 | 239 | 221 | 222 | 210 | 209 | 197 | 210 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Cisco Systems Inc. | 57 | 58 | 63 | 61 | 57 | 49 | 49 | 43 | 40 | 36 | 32 | 33 | 30 | 28 | 27 | 25 | 27 | 26 | 26 | — | — | — | — | — | — | — | ||||||||
| Dell Technologies Inc. | 18 | 19 | 22 | 27 | 25 | 28 | 27 | 27 | 22 | 21 | 19 | 20 | 21 | 21 | 19 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Super Micro Computer Inc. | 116 | 123 | 90 | 105 | 95 | 127 | 128 | 146 | 141 | 132 | 126 | 115 | 108 | 102 | 110 | 114 | 93 | 89 | 81 | — | — | — | — | — | — | — | ||||||||
Based on: 10-Q (reporting date: 2023-12-29), 10-Q (reporting date: 2023-09-29), 10-K (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-Q (reporting date: 2022-12-30), 10-Q (reporting date: 2022-09-30), 10-K (reporting date: 2022-07-01), 10-Q (reporting date: 2022-04-01), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-10-01), 10-K (reporting date: 2021-07-02), 10-Q (reporting date: 2021-04-02), 10-Q (reporting date: 2021-01-01), 10-Q (reporting date: 2020-10-02), 10-K (reporting date: 2020-07-03), 10-Q (reporting date: 2020-04-03), 10-Q (reporting date: 2020-01-03), 10-Q (reporting date: 2019-10-04), 10-K (reporting date: 2019-06-28), 10-Q (reporting date: 2019-03-29), 10-Q (reporting date: 2018-12-28), 10-Q (reporting date: 2018-09-28), 10-K (reporting date: 2018-06-29), 10-Q (reporting date: 2018-03-30), 10-Q (reporting date: 2017-12-29), 10-Q (reporting date: 2017-09-29).
1 Q2 2024 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ 3.20 = 114
2 Click competitor name to see calculations.
The inventory turnover ratio and the average inventory processing period exhibit notable trends over the analyzed quarterly periods. Initially, from the period ending September 29, 2017, to early 2018, data is not available; however, starting in June 2018, the inventory turnover ratio fluctuates moderately between approximately 3.75 and 4.22 until early 2021. During this timeframe, the ratio shows a general mild decline from a peak around 4.22 to a low near 3.33, indicating a gradual slowdown in inventory turnover frequency.
Concurrently, the average inventory processing period, measured in days, inversely mirrors this trend. Beginning at 83 days in June 2018, the period gradually increases, reaching a high of 110 days by April 2021. This suggests that the company took longer to move its inventory during this interval, corresponding with the decreasing turnover ratio.
From mid-2021 onwards, the inventory turnover ratio demonstrates a further decline, dropping below 3.5 and reaching levels as low as 2.75 by December 2022, before showing a modest recovery to 3.20 by December 2023. In parallel, the average inventory processing period extends significantly, rising from around 106 days in mid-2021 to a peak of 133 days by March 2023. Toward the end of 2023, there is a slight reduction in the processing period to 114 days.
Overall, the dataset reveals a sustained weakening in inventory efficiency over the observed periods, marked by decreasing inventory turnover ratios and lengthening inventory processing periods. The recent slight improvements in the turnover ratio and corresponding decreases in processing time suggest potential operational adjustments or market factors influencing inventory management toward the end of the timeframe.
- Inventory Turnover Ratio
- Shows a downward trend from approximately 4.22 in early 2020 to a low near 2.75 by late 2022, with a mild recovery to 3.20 by the end of 2023.
- Average Inventory Processing Period
- Increases from about 83 days in mid-2018 to a peak of 133 days in early 2023, then decreases slightly to 114 days by the last period.
- Insight
- The inverse relationship between the two metrics reflects deteriorating inventory turnover efficiency for a sustained period, potentially due to operational or market challenges, with recent data indicating partial improvement.
Average Receivable Collection Period
Western Digital Corp., average receivable collection period calculation (quarterly data)
| Dec 29, 2023 | Sep 29, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 30, 2022 | Sep 30, 2022 | Jul 1, 2022 | Apr 1, 2022 | Dec 31, 2021 | Oct 1, 2021 | Jul 2, 2021 | Apr 2, 2021 | Jan 1, 2021 | Oct 2, 2020 | Jul 3, 2020 | Apr 3, 2020 | Jan 3, 2020 | Oct 4, 2019 | Jun 28, 2019 | Mar 29, 2019 | Dec 28, 2018 | Sep 28, 2018 | Jun 29, 2018 | Mar 30, 2018 | Dec 29, 2017 | Sep 29, 2017 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||||||||
| Receivables turnover | 7.39 | 7.81 | 7.71 | 8.91 | 8.27 | 7.22 | 6.70 | 8.15 | 6.91 | 7.38 | 7.50 | 8.55 | 8.91 | 7.92 | 7.03 | 8.13 | 8.70 | 10.76 | 13.76 | 14.76 | 11.31 | 9.24 | 9.40 | — | — | — | ||||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||||||||
| Average receivable collection period1 | 49 | 47 | 47 | 41 | 44 | 51 | 54 | 45 | 53 | 49 | 49 | 43 | 41 | 46 | 52 | 45 | 42 | 34 | 27 | 25 | 32 | 40 | 39 | — | — | — | ||||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||||||||
| Average Receivable Collection Period, Competitors2 | ||||||||||||||||||||||||||||||||||
| Apple Inc. | 21 | 22 | 28 | 19 | 17 | 22 | 26 | 21 | 20 | 29 | 26 | 18 | 21 | 34 | 21 | 24 | 21 | 29 | 32 | — | — | — | — | — | — | — | ||||||||
| Arista Networks Inc. | 71 | 65 | 64 | 54 | 54 | 65 | 77 | 61 | 61 | 75 | 64 | 52 | 51 | 56 | 61 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Cisco Systems Inc. | 31 | 30 | 37 | 34 | 36 | 38 | 47 | 41 | 43 | 38 | 42 | 33 | 33 | 30 | 41 | 33 | 31 | 34 | 39 | — | — | — | — | — | — | — | ||||||||
| Dell Technologies Inc. | 40 | 35 | 45 | 40 | 46 | 41 | 47 | 52 | 49 | 42 | 50 | 45 | 46 | 43 | 49 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Super Micro Computer Inc. | 59 | 42 | 59 | 37 | 42 | 45 | 59 | 54 | 44 | 44 | 48 | 44 | 36 | 36 | 44 | 37 | 40 | 39 | 41 | — | — | — | — | — | — | — | ||||||||
Based on: 10-Q (reporting date: 2023-12-29), 10-Q (reporting date: 2023-09-29), 10-K (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-Q (reporting date: 2022-12-30), 10-Q (reporting date: 2022-09-30), 10-K (reporting date: 2022-07-01), 10-Q (reporting date: 2022-04-01), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-10-01), 10-K (reporting date: 2021-07-02), 10-Q (reporting date: 2021-04-02), 10-Q (reporting date: 2021-01-01), 10-Q (reporting date: 2020-10-02), 10-K (reporting date: 2020-07-03), 10-Q (reporting date: 2020-04-03), 10-Q (reporting date: 2020-01-03), 10-Q (reporting date: 2019-10-04), 10-K (reporting date: 2019-06-28), 10-Q (reporting date: 2019-03-29), 10-Q (reporting date: 2018-12-28), 10-Q (reporting date: 2018-09-28), 10-K (reporting date: 2018-06-29), 10-Q (reporting date: 2018-03-30), 10-Q (reporting date: 2017-12-29), 10-Q (reporting date: 2017-09-29).
1 Q2 2024 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ 7.39 = 49
2 Click competitor name to see calculations.
The analysis of the receivables turnover ratio and average receivable collection period over the observed quarters reveals notable fluctuations and certain trends in working capital management related to accounts receivable.
- Receivables Turnover Ratio
- The receivables turnover ratio exhibits significant variability over the periods. Starting from a low of approximately 7.03 in April 2020, it reached a peak at 14.76 in June 2018. Subsequently, the ratio followed a generally downward trajectory with minor recoveries. The ratio dropped markedly from the peak level to around 6.7 in April 2022. After this decline, some oscillation is visible with values ranging mostly between 7.1 and 8.9 from mid-2022 through the end of 2023. This suggests periods of both improved and reduced efficiency in collecting receivables, with the highest efficiency notably recorded mid-2018 and less efficient collections in recent quarters.
- Average Receivable Collection Period
- Correspondingly, the average receivable collection period inversely mirrors the turnover ratio trends. Initially, there is a low collection period around 25 days in June 2018, indicating rapid receivable conversion. Over time, this period lengthened considerably, peaking around 54 days in early 2022. More recently, the collection period decreased slightly but remained elevated relative to earlier years, fluctuating mostly between 41 and 49 days. This increase in collection days suggests a slower receivable turnover and potentially less effective credit management or changes in customer payment behaviors.
Overall, the data portray an initial phase of strong receivables management with quick collections around mid-2018, followed by a general decline in efficiency through 2020 and early 2022. The modest improvement since then indicates some stabilization but at levels that are less optimal than the earlier peak. This pattern could reflect underlying shifts in sales dynamics, customer credit terms, or economic conditions affecting payment patterns. Continuous monitoring and targeted improvements in receivables management may be necessary to enhance liquidity and operational efficiency.
Operating Cycle
Western Digital Corp., operating cycle calculation (quarterly data)
No. days
| Dec 29, 2023 | Sep 29, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 30, 2022 | Sep 30, 2022 | Jul 1, 2022 | Apr 1, 2022 | Dec 31, 2021 | Oct 1, 2021 | Jul 2, 2021 | Apr 2, 2021 | Jan 1, 2021 | Oct 2, 2020 | Jul 3, 2020 | Apr 3, 2020 | Jan 3, 2020 | Oct 4, 2019 | Jun 28, 2019 | Mar 29, 2019 | Dec 28, 2018 | Sep 28, 2018 | Jun 29, 2018 | Mar 30, 2018 | Dec 29, 2017 | Sep 29, 2017 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||||||||
| Average inventory processing period | 114 | 124 | 129 | 133 | 119 | 115 | 103 | 101 | 102 | 101 | 106 | 110 | 105 | 96 | 86 | 87 | 89 | 94 | 93 | 97 | 97 | 87 | 83 | — | — | — | ||||||||
| Average receivable collection period | 49 | 47 | 47 | 41 | 44 | 51 | 54 | 45 | 53 | 49 | 49 | 43 | 41 | 46 | 52 | 45 | 42 | 34 | 27 | 25 | 32 | 40 | 39 | — | — | — | ||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||||||
| Operating cycle1 | 163 | 171 | 176 | 174 | 163 | 166 | 157 | 146 | 155 | 150 | 155 | 153 | 146 | 142 | 138 | 132 | 131 | 128 | 120 | 122 | 129 | 127 | 122 | — | — | — | ||||||||
| Benchmarks | ||||||||||||||||||||||||||||||||||
| Operating Cycle, Competitors2 | ||||||||||||||||||||||||||||||||||
| Apple Inc. | 32 | 33 | 39 | 31 | 29 | 33 | 34 | 30 | 29 | 39 | 37 | 27 | 31 | 44 | 30 | 33 | 28 | 38 | 41 | — | — | — | — | — | — | — | ||||||||
| Arista Networks Inc. | 369 | 393 | 382 | 369 | 379 | 383 | 353 | 329 | 300 | 296 | 286 | 262 | 260 | 253 | 271 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Cisco Systems Inc. | 88 | 88 | 100 | 95 | 93 | 87 | 96 | 84 | 83 | 74 | 74 | 66 | 63 | 58 | 68 | 58 | 58 | 60 | 65 | — | — | — | — | — | — | — | ||||||||
| Dell Technologies Inc. | 58 | 54 | 67 | 67 | 71 | 69 | 74 | 79 | 71 | 63 | 69 | 65 | 67 | 64 | 68 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Super Micro Computer Inc. | 175 | 165 | 149 | 142 | 137 | 172 | 187 | 200 | 185 | 176 | 174 | 159 | 144 | 138 | 154 | 151 | 133 | 128 | 122 | — | — | — | — | — | — | — | ||||||||
Based on: 10-Q (reporting date: 2023-12-29), 10-Q (reporting date: 2023-09-29), 10-K (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-Q (reporting date: 2022-12-30), 10-Q (reporting date: 2022-09-30), 10-K (reporting date: 2022-07-01), 10-Q (reporting date: 2022-04-01), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-10-01), 10-K (reporting date: 2021-07-02), 10-Q (reporting date: 2021-04-02), 10-Q (reporting date: 2021-01-01), 10-Q (reporting date: 2020-10-02), 10-K (reporting date: 2020-07-03), 10-Q (reporting date: 2020-04-03), 10-Q (reporting date: 2020-01-03), 10-Q (reporting date: 2019-10-04), 10-K (reporting date: 2019-06-28), 10-Q (reporting date: 2019-03-29), 10-Q (reporting date: 2018-12-28), 10-Q (reporting date: 2018-09-28), 10-K (reporting date: 2018-06-29), 10-Q (reporting date: 2018-03-30), 10-Q (reporting date: 2017-12-29), 10-Q (reporting date: 2017-09-29).
1 Q2 2024 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= 114 + 49 = 163
2 Click competitor name to see calculations.
The analysis of the quarterly financial indicators reveals several notable trends across the periods covered.
- Average Inventory Processing Period
- The average inventory processing period exhibits a general upward trend with fluctuations. Starting from 83 days in late 2017, it increases steadily to peak around 133 days in the third quarter of 2022. Following this peak, there is a moderate decline to 114 days by the end of 2023. This trend indicates that the company has faced gradually lengthening inventory turnover times over the years, reaching a high point before showing signs of improvement in more recent quarters.
- Average Receivable Collection Period
- The average receivable collection period displays more variability without a clear consistent trend. Initially, it decreases from 39 days to 25 days by mid-2018, suggesting improved efficiency in collecting receivables. Subsequently, the period extends again, peaking at 54 days in late 2021, and then oscillates between low 40s and high 40s into 2023. This pattern suggests fluctuations in credit management or customer payment behavior, with occasional deterioration in collection efficiency.
- Operating Cycle
- The operating cycle, derived from the sum of the inventory processing and receivable collection periods, demonstrates a gradual increase over time. It rises from 122 days in late 2017, reaching a maximum of 176 days towards the end of 2022, before reducing slightly to 163 days by the close of 2023. The increasing operating cycle corresponds with the lengthening inventory and receivables periods, indicating a slowing overall cash conversion process. The slight reduction in late 2023 may reflect operational improvements or adjustments in working capital management.
Overall, the data indicates that the company experienced increasing durations in inventory turnover and cash collection processes over several years, contributing to a longer operating cycle. However, improvements toward the end of the latest periods suggest some recovery or enhanced operational efficiency in managing working capital.
Average Payables Payment Period
Western Digital Corp., average payables payment period calculation (quarterly data)
| Dec 29, 2023 | Sep 29, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 30, 2022 | Sep 30, 2022 | Jul 1, 2022 | Apr 1, 2022 | Dec 31, 2021 | Oct 1, 2021 | Jul 2, 2021 | Apr 2, 2021 | Jan 1, 2021 | Oct 2, 2020 | Jul 3, 2020 | Apr 3, 2020 | Jan 3, 2020 | Oct 4, 2019 | Jun 28, 2019 | Mar 29, 2019 | Dec 28, 2018 | Sep 28, 2018 | Jun 29, 2018 | Mar 30, 2018 | Dec 29, 2017 | Sep 29, 2017 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||||||||
| Payables turnover | 6.84 | 7.98 | 8.07 | 8.37 | 9.74 | 7.29 | 6.79 | 7.18 | 6.45 | 6.73 | 6.41 | 6.78 | 6.38 | 6.51 | 6.66 | 7.23 | 7.40 | 7.39 | 8.18 | 8.19 | 6.70 | 6.27 | 5.71 | — | — | — | ||||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||||||||
| Average payables payment period1 | 53 | 46 | 45 | 44 | 37 | 50 | 54 | 51 | 57 | 54 | 57 | 54 | 57 | 56 | 55 | 50 | 49 | 49 | 45 | 45 | 54 | 58 | 64 | — | — | — | ||||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||||||||
| Average Payables Payment Period, Competitors2 | ||||||||||||||||||||||||||||||||||
| Apple Inc. | 80 | 100 | 107 | 79 | 72 | 96 | 105 | 80 | 88 | 126 | 94 | 72 | 75 | 129 | 91 | 76 | 71 | 99 | 104 | — | — | — | — | — | — | — | ||||||||
| Arista Networks Inc. | 48 | 36 | 71 | 45 | 61 | 62 | 50 | 68 | 77 | 65 | 69 | 49 | 56 | 56 | 59 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Cisco Systems Inc. | 33 | 36 | 40 | 43 | 42 | 43 | 43 | 44 | 41 | 45 | 48 | 51 | 40 | 48 | 46 | 49 | 38 | 39 | 39 | — | — | — | — | — | — | — | ||||||||
| Dell Technologies Inc. | 102 | 86 | 85 | 99 | 109 | 113 | 125 | 130 | 120 | 117 | 122 | 114 | 114 | 107 | 116 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Super Micro Computer Inc. | 60 | 65 | 49 | 44 | 37 | 57 | 54 | 72 | 70 | 63 | 74 | 59 | 53 | 44 | 54 | 61 | 52 | 43 | 44 | — | — | — | — | — | — | — | ||||||||
Based on: 10-Q (reporting date: 2023-12-29), 10-Q (reporting date: 2023-09-29), 10-K (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-Q (reporting date: 2022-12-30), 10-Q (reporting date: 2022-09-30), 10-K (reporting date: 2022-07-01), 10-Q (reporting date: 2022-04-01), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-10-01), 10-K (reporting date: 2021-07-02), 10-Q (reporting date: 2021-04-02), 10-Q (reporting date: 2021-01-01), 10-Q (reporting date: 2020-10-02), 10-K (reporting date: 2020-07-03), 10-Q (reporting date: 2020-04-03), 10-Q (reporting date: 2020-01-03), 10-Q (reporting date: 2019-10-04), 10-K (reporting date: 2019-06-28), 10-Q (reporting date: 2019-03-29), 10-Q (reporting date: 2018-12-28), 10-Q (reporting date: 2018-09-28), 10-K (reporting date: 2018-06-29), 10-Q (reporting date: 2018-03-30), 10-Q (reporting date: 2017-12-29), 10-Q (reporting date: 2017-09-29).
1 Q2 2024 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ 6.84 = 53
2 Click competitor name to see calculations.
The payables turnover ratio exhibits a generally increasing trend from the period starting September 28, 2018, through December 30, 2022, with some fluctuations towards the end of the series. Initially, the ratio increases steadily from 5.71 to a peak around 9.74 in December 2022. However, following this peak, the ratio declines gradually to 6.84 by the end of December 2023. This suggests that the company was paying its payables more frequently, particularly until late 2022, but then started to slow down the frequency of payments towards the end of the examined period.
Correspondingly, the average payables payment period inversely mirrors the trend in payables turnover. Starting at 64 days around September 28, 2018, the average payment period decreases steadily, hitting a low of 37 days by March 31, 2023. This downward trend indicates an improvement in the efficiency of payments over these years, potentially reflecting better liquidity or payment policies. In the last few quarters, this trend reverses slightly, with the average payment period increasing again to 53 days by the end of December 2023, reinforcing the observation of slower payment frequency in the latest periods.
The inverse relationship between the payables turnover and average payment period is consistent throughout the dataset, as expected because a higher turnover ratio means quicker payments, resulting in a shorter payment period. The fluctuations observed towards the end of the period suggest some changes in working capital management, possibly influenced by external conditions or strategic adjustments.
Cash Conversion Cycle
Western Digital Corp., cash conversion cycle calculation (quarterly data)
No. days
| Dec 29, 2023 | Sep 29, 2023 | Jun 30, 2023 | Mar 31, 2023 | Dec 30, 2022 | Sep 30, 2022 | Jul 1, 2022 | Apr 1, 2022 | Dec 31, 2021 | Oct 1, 2021 | Jul 2, 2021 | Apr 2, 2021 | Jan 1, 2021 | Oct 2, 2020 | Jul 3, 2020 | Apr 3, 2020 | Jan 3, 2020 | Oct 4, 2019 | Jun 28, 2019 | Mar 29, 2019 | Dec 28, 2018 | Sep 28, 2018 | Jun 29, 2018 | Mar 30, 2018 | Dec 29, 2017 | Sep 29, 2017 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||||||||
| Average inventory processing period | 114 | 124 | 129 | 133 | 119 | 115 | 103 | 101 | 102 | 101 | 106 | 110 | 105 | 96 | 86 | 87 | 89 | 94 | 93 | 97 | 97 | 87 | 83 | — | — | — | ||||||||
| Average receivable collection period | 49 | 47 | 47 | 41 | 44 | 51 | 54 | 45 | 53 | 49 | 49 | 43 | 41 | 46 | 52 | 45 | 42 | 34 | 27 | 25 | 32 | 40 | 39 | — | — | — | ||||||||
| Average payables payment period | 53 | 46 | 45 | 44 | 37 | 50 | 54 | 51 | 57 | 54 | 57 | 54 | 57 | 56 | 55 | 50 | 49 | 49 | 45 | 45 | 54 | 58 | 64 | — | — | — | ||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||||||||
| Cash conversion cycle1 | 110 | 125 | 131 | 130 | 126 | 116 | 103 | 95 | 98 | 96 | 98 | 99 | 89 | 86 | 83 | 82 | 82 | 79 | 75 | 77 | 75 | 69 | 58 | — | — | — | ||||||||
| Benchmarks | ||||||||||||||||||||||||||||||||||
| Cash Conversion Cycle, Competitors2 | ||||||||||||||||||||||||||||||||||
| Apple Inc. | -48 | -67 | -68 | -48 | -43 | -63 | -71 | -50 | -59 | -87 | -57 | -45 | -44 | -85 | -61 | -43 | -43 | -61 | -63 | — | — | — | — | — | — | — | ||||||||
| Arista Networks Inc. | 321 | 357 | 311 | 324 | 318 | 321 | 303 | 261 | 223 | 231 | 217 | 213 | 204 | 197 | 212 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Cisco Systems Inc. | 55 | 52 | 60 | 52 | 51 | 44 | 53 | 40 | 42 | 29 | 26 | 15 | 23 | 10 | 22 | 9 | 20 | 21 | 26 | — | — | — | — | — | — | — | ||||||||
| Dell Technologies Inc. | -44 | -32 | -18 | -32 | -38 | -44 | -51 | -51 | -49 | -54 | -53 | -49 | -47 | -43 | -48 | — | — | — | — | — | — | — | — | — | — | — | ||||||||
| Super Micro Computer Inc. | 115 | 100 | 100 | 98 | 100 | 115 | 133 | 128 | 115 | 113 | 100 | 100 | 91 | 94 | 100 | 90 | 81 | 85 | 78 | — | — | — | — | — | — | — | ||||||||
Based on: 10-Q (reporting date: 2023-12-29), 10-Q (reporting date: 2023-09-29), 10-K (reporting date: 2023-06-30), 10-Q (reporting date: 2023-03-31), 10-Q (reporting date: 2022-12-30), 10-Q (reporting date: 2022-09-30), 10-K (reporting date: 2022-07-01), 10-Q (reporting date: 2022-04-01), 10-Q (reporting date: 2021-12-31), 10-Q (reporting date: 2021-10-01), 10-K (reporting date: 2021-07-02), 10-Q (reporting date: 2021-04-02), 10-Q (reporting date: 2021-01-01), 10-Q (reporting date: 2020-10-02), 10-K (reporting date: 2020-07-03), 10-Q (reporting date: 2020-04-03), 10-Q (reporting date: 2020-01-03), 10-Q (reporting date: 2019-10-04), 10-K (reporting date: 2019-06-28), 10-Q (reporting date: 2019-03-29), 10-Q (reporting date: 2018-12-28), 10-Q (reporting date: 2018-09-28), 10-K (reporting date: 2018-06-29), 10-Q (reporting date: 2018-03-30), 10-Q (reporting date: 2017-12-29), 10-Q (reporting date: 2017-09-29).
1 Q2 2024 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= 114 + 49 – 53 = 110
2 Click competitor name to see calculations.
The analysis of the quarterly financial data reveals several noteworthy trends in the company's operational efficiency, particularly in inventory management, receivables collection, payables payment, and overall cash conversion cycle over the observed periods.
- Average Inventory Processing Period
- This metric shows a general upward trend from 83 days in the earlier reported periods to a peak of 133 days in late 2022, before declining to 114 days by the end of 2023. The increase indicates a lengthening duration in inventory turnover, suggesting either accumulation of stock or slower sales fulfillment during these periods. The subsequent decline might reflect efforts to optimize inventory levels or improved sales performance.
- Average Receivable Collection Period
- The receivable collection period exhibits variability, initially decreasing from 40 days to a low of 25 days around mid-2018, followed by a steady increase reaching 54 days by late 2021. Afterward, it fluctuates around the mid-40 days range towards the end of 2023. These fluctuations indicate changes in credit policies or customer payment behaviors, with periods of faster collection possibly improving cash flow, and longer collection periods potentially stressing liquidity.
- Average Payables Payment Period
- The payables payment period generally trends downward from 64 days early on, reaching a minimum of 37 days by mid-2023, before rising again to 53 days by the end of 2023. The initial decrease suggests an accelerated payment cycle to suppliers, possibly reflecting improved liquidity or strategic supplier relationships. The latter increase could indicate a shift toward extending payment terms to conserve cash.
- Cash Conversion Cycle
- The cash conversion cycle, representing the net time between cash outlay and recovery, displays an overall increasing trend from 58 days to a peak of 131 days in late 2022. This increase suggests that the company’s funds remain tied up longer in inventory and receivables relative to payables, potentially indicating declining operational efficiency or changes in business conditions. A slight reduction to 110 days by the end of 2023 may signal initiatives to enhance working capital management.
In summary, the data reflect a period of growing operational cycle durations, with inventory processing and cash conversion ciclos experiencing the most significant lengthening. The variations in receivables and payables periods suggest dynamic adjustments in credit policies and supplier terms. Recent trends toward reducing these intervals may indicate management efforts to strengthen overall liquidity and optimize working capital efficiency.