Stock Analysis on Net

Hewlett Packard Enterprise Co. (NYSE:HPE)

$22.49

This company has been moved to the archive! The financial data has not been updated since June 5, 2024.

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

Microsoft Excel

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Short-term Activity Ratios (Summary)

Hewlett Packard Enterprise Co., short-term (operating) activity ratios (quarterly data)

Microsoft Excel
Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Turnover Ratios
Inventory turnover
Receivables turnover
Payables turnover
Working capital turnover
Average No. Days
Average inventory processing period
Add: Average receivable collection period
Operating cycle
Less: Average payables payment period
Cash conversion cycle

Based on: 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).


The analysis of the financial ratios over the observed periods reveals several key trends in the company’s operational efficiency and liquidity management.

Inventory Turnover
The inventory turnover ratio shows a declining trend, decreasing from 9.25 in early 2019 to 2.51 by April 2024. This indicates a slowing in the rate at which inventory is sold and replaced, suggesting potential issues with inventory management or slowing sales velocity over time.
Receivables Turnover
The receivables turnover ratio has exhibited fluctuations without a clear long-term upward or downward trend. Starting around 9.65 in early 2019, it dipped to lows near 6.95 in late 2021, then recovered somewhat to around 7.37 by April 2024. This pattern indicates varying efficiency in the collection of receivables, with occasional slowdowns followed by modest recoveries.
Payables Turnover
The payables turnover ratio declined from approximately 3.68 in early 2019 to 1.82 in April 2024, with some erratic movements in intermediate periods. A decreasing ratio suggests the company is taking longer to pay its suppliers, potentially reflecting efforts to optimize cash outflows or liquidity constraints.
Average Inventory Processing Period
Consistent with the inventory turnover trend, the average inventory processing period increased significantly from 39 days in early 2019 to a peak exceeding 145 days by April 2024. This lengthening period corroborates slower inventory movement and possible stock buildup.
Average Receivable Collection Period
The average time to collect receivables has shown moderate variability, generally ranging between 35 and 53 days. While fluctuations are present, there is a mild upward drift toward later periods, suggesting slightly extended collection times in recent years.
Operating Cycle
The overall operating cycle, which sums the inventory and receivables processing periods, increased from roughly 77 days in early 2019 to almost 195 days by April 2024. This reflects a significant elongation in the time taken to convert inventory and receivables into cash.
Average Payables Payment Period
The payables payment period has shown an increasing trend, escalating from about 99 days in early 2019 to over 201 days by April 2024. This indicates a substantial extension in payment terms or delays in settling obligations to suppliers, consistent with the declining payables turnover.
Cash Conversion Cycle
The cash conversion cycle displays considerable variability, ranging from negative values (indicating quicker cash recovery than cash payments) in early periods to positive peaks above 30 days in mid-periods, before oscillating again. The recent periods show modest positive values, around 7 days or slightly negative, suggesting fluctuating efficiency in cash flow management relative to operational timing.

In summary, the company is experiencing a protracted inventory turnover and longer collection periods, contributing to an extended operating cycle. Concurrently, the lengthening payables period indicates a strategic or necessary delay in outflows. Overall, operational efficiency in managing working capital components appears to have diminished over time, which may impact liquidity and cash flow stability.


Turnover Ratios


Average No. Days


Inventory Turnover

Hewlett Packard Enterprise Co., inventory turnover calculation (quarterly data)

Microsoft Excel
Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data (US$ in millions)
Cost of revenue
Inventory
Short-term Activity Ratio
Inventory turnover1
Benchmarks
Inventory Turnover, Competitors2
Apple Inc.
Arista Networks Inc.
Cisco Systems Inc.
Dell Technologies Inc.
Super Micro Computer Inc.

Based on: 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q2 2024 Calculation
Inventory turnover = (Cost of revenueQ2 2024 + Cost of revenueQ1 2024 + Cost of revenueQ4 2023 + Cost of revenueQ3 2023) ÷ Inventory
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The quarterly financial data reveals several notable trends regarding cost of revenue, inventory levels, and inventory turnover ratio over the examined periods.

Cost of Revenue
The cost of revenue demonstrates moderate fluctuations throughout the periods. Initially, it shows a general declining trend from early 2019 into mid-2020, dropping from approximately 5,207 million US dollars to around 4,095 million. This is followed by several periods of increases and decreases, with peaks observed in late 2020 and early 2023. The highest points occur in October 2022 and January 2023, reaching above 5,000 million, before declining towards the latest periods. Overall, the cost of revenue displays volatility but without a clear long-term upward or downward trajectory.
Inventory Levels
Inventory levels display a distinct increasing trend over the analyzed timeframe. Starting at 2,300 million US dollars in early 2019, inventory values steadily rise with some acceleration from 2021 onward, peaking notably in 2024 at over 7,300 million. This rise is relatively consistent, although there are occasional minor decreases between quarters. The sustained growth in inventory suggests increasing stock accumulation or potential changes in operational or supply chain strategies.
Inventory Turnover Ratio
The inventory turnover ratio exhibits a significant decline from 2019 through early 2024. Beginning at a high ratio of approximately 9.25 in early 2019, the figure decreases steadily to around 2.51 by the latest quarter. This reduction indicates that inventory is being sold and replaced less frequently than before, aligning with the observed increase in inventory levels. The sharp decline in turnover ratio could indicate slower sales, overstocking, or shifts in inventory management efficiency.

In summary, the data indicates that while the cost of revenue shows variability without a definitive trend, inventory levels have been growing steadily, accompanied by a marked decrease in inventory turnover. This combination suggests increasing stock accumulation with potentially slower movement of goods, which may warrant further examination of the company's operational practices and market conditions.


Receivables Turnover

Hewlett Packard Enterprise Co., receivables turnover calculation (quarterly data)

Microsoft Excel
Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data (US$ in millions)
Net revenue
Accounts receivable, net of allowances
Short-term Activity Ratio
Receivables turnover1
Benchmarks
Receivables Turnover, Competitors2
Apple Inc.
Arista Networks Inc.
Cisco Systems Inc.
Dell Technologies Inc.
Super Micro Computer Inc.

Based on: 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q2 2024 Calculation
Receivables turnover = (Net revenueQ2 2024 + Net revenueQ1 2024 + Net revenueQ4 2023 + Net revenueQ3 2023) ÷ Accounts receivable, net of allowances
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


Net Revenue Trends
The net revenue figures exhibit a pattern of moderate fluctuations over the analyzed quarters. Starting in early 2019, revenue levels were relatively stable around the 7,000 to 7,500 million USD range. A notable decline occurred in early 2020, coinciding with the global pandemic period, where quarterly revenue dropped below 7,000 million USD, reaching a low point in April 2020 at 6,009 million USD. Subsequent quarters showed recovery with values fluctuating but generally trending upwards, peaking at 7,871 million USD in October 2022. However, the more recent quarters witnessed some volatility, with net revenue oscillating around the 7,000 million USD mark, ending at 7,204 million USD in April 2024. Overall, the revenue trend indicates resilience post-pandemic but remains subject to quarter-on-quarter variability.
Accounts Receivable Trends
The net accounts receivable values demonstrate a generally increasing trend through the examined period, with notable rises in late 2021 and 2022. Early values in 2019 ranged between approximately 2,900 to 3,100 million USD. The figures showed moderate growth with some volatility, but from mid-2021 onward, the accounts receivable increased more sharply, reaching a peak of 4,201 million USD in April 2023. This increase suggests a larger amount of sales revenue is outstanding or a lengthening of collection periods. Despite some small declines following peaks, values remained elevated around the 3,800 to 4,000 million USD range in 2023 and early 2024.
Receivables Turnover Ratio
The receivables turnover ratio reflects the efficiency in collecting accounts receivable. Early 2019 figures were relatively high, between roughly 9.6 to 10.1, suggesting efficient collections. During 2020, the ratio experienced a decrease, particularly notable in the October 2020 quarter (7.97), indicating slower receivables collection possibly linked to pandemic-related disruptions. This downward trend intensified through 2021 with a trough at 6.98 in October 2021, pointing to longer collection cycles or higher outstanding receivables relative to sales. Although there was some recovery in subsequent quarters, the ratio did not return to the early 2019 levels, staying mostly between 6.9 to 8.6 in the 2022–2024 timeframe. This sustained lower turnover suggests a continuing challenge in accounts receivable management or changes in credit policies.
Overall Insights
The analysis reveals that while net revenue has shown resilience and recovery following downturns in early 2020, accounts receivable have steadily increased, accompanied by a declining trend in receivables turnover ratio. This combination may signal extended credit terms, slower collections, or increased sales on credit, which can impact cash flow. The company's ability to efficiently convert receivables to cash has reduced compared to pre-pandemic periods, highlighting an area for potential operational focus. The observed trends emphasize the importance of monitoring accounts receivable management alongside revenue performance to sustain financial health.

Payables Turnover

Hewlett Packard Enterprise Co., payables turnover calculation (quarterly data)

Microsoft Excel
Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data (US$ in millions)
Cost of revenue
Accounts payable
Short-term Activity Ratio
Payables turnover1
Benchmarks
Payables Turnover, Competitors2
Apple Inc.
Arista Networks Inc.
Cisco Systems Inc.
Dell Technologies Inc.
Super Micro Computer Inc.

Based on: 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

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 Click competitor name to see calculations.


The financial data reveals several key trends relating to cost of revenue, accounts payable, and payables turnover over the observed quarters.

Cost of Revenue
The cost of revenue generally exhibits a fluctuating but overall stable pattern with periodic declines followed by recoveries. From early 2019 through early 2020, the cost shows a moderate downward trend, reaching a low in April 2020. Subsequently, the value increases again, peaking around October 2020 and January 2021, then stabilizing with minor oscillations through 2022. A noticeable increase is observed in October 2022, followed by a decline in early 2023, and another upward movement in the latter half of 2023 and early 2024. This pattern suggests variability possibly associated with changes in sales volume, production costs, or pricing strategies.
Accounts Payable
Accounts payable displays a general upward trend with significant volatility. Starting in 2019 at levels around 5,000 to 5,700 million USD, it experiences both increases and corrections over time. Notable surges are recorded in late 2021 to early 2022 and again from late 2022 through early 2024, reaching levels exceeding 10,000 million USD by April 2024. These elevations may indicate extended payment terms, increased purchases on credit, or shifts in supplier relationships. Despite fluctuations, the trend suggests growing reliance on payables as a source of short-term financing.
Payables Turnover
The payables turnover ratio declines notably over the period, reflecting a lengthening of the average payment period to suppliers. Initially, the ratio hovers close to 3.7–3.9 in early 2019, indicating roughly 3.5 to 4 full turnovers of payables per year. However, from 2020 onwards, the ratio drops considerably, reaching values near or below 2 by late 2022 and continuing this low trend into 2024. This reduction suggests the company is taking longer to pay its debts, which may be a strategy to preserve cash or could reflect liquidity constraints. The inverse relationship with accounts payable levels underlines this interpretation.

In summary, the company demonstrates a cost structure with some volatility but relative stability in cost of revenue. The increasing accounts payable balances combined with the decreasing payables turnover ratio indicate a strategic or necessary extension in payment terms. This pattern might have implications for supplier relationships and financial liquidity management moving forward.


Working Capital Turnover

Hewlett Packard Enterprise Co., working capital turnover calculation (quarterly data)

Microsoft Excel
Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data (US$ in millions)
Current assets
Less: Current liabilities
Working capital
 
Net revenue
Short-term Activity Ratio
Working capital turnover1
Benchmarks
Working Capital Turnover, Competitors2
Apple Inc.
Arista Networks Inc.
Cisco Systems Inc.
Dell Technologies Inc.
Super Micro Computer Inc.

Based on: 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q2 2024 Calculation
Working capital turnover = (Net revenueQ2 2024 + Net revenueQ1 2024 + Net revenueQ4 2023 + Net revenueQ3 2023) ÷ Working capital
= ( + + + ) ÷ =

2 Click competitor name to see calculations.


The analysis of the quarterly financial data reveals several notable trends in the working capital and net revenue metrics over the examined period.

Working Capital

The working capital consistently shows negative values, indicating that current liabilities exceed current assets throughout the entire timeframe. Initially, the negative balance deepened significantly, reaching a peak deficit in the fourth quarter of 2019 with a value of approximately -4,016 million USD.

Following this peak, the working capital improved somewhat during mid-2020, reducing the deficit to a much lower level (-227 million USD in July 2020), suggesting temporary improvements in liquidity or current asset management. However, this was short-lived as the negative working capital increased again substantially in the subsequent quarters, fluctuating between approximately -1,800 million USD and -2,900 million USD from late 2020 through early 2024.

More recent quarters, particularly from early 2022 onward, display persistent substantial negative working capital, with values generally worsening over time. This sustained negative working capital position could imply ongoing challenges in managing short-term funding or obligations relative to currently available assets.

Net Revenue

Net revenue trends show moderate fluctuations quarter over quarter, without a clear long-term upward or downward trajectory. The revenue figures oscillate mostly between roughly 6,700 million USD and 7,800 million USD across the quarters.

The data display a noticeable dip in net revenue during the early quarters of 2020, coinciding with the onset of the global pandemic situation, dropping as low as approximately 6,000 million USD in April 2020. A recovery stage is evident by the end of 2020 and into 2021, where revenues climbed back up to approximately 7,354 million USD.

From 2021 onward, net revenue demonstrates a relatively stable pattern with some variability but no major sustained growth or collapse. The latest quarter data in April 2024 shows revenue around 7,204 million USD, close to the earlier average, indicating stable sales or operational income levels.

Insights

The coexistence of consistently negative working capital with relatively stable net revenue suggests possible reliance on short-term liability financing or aggressive working capital management strategies such as just-in-time inventory or extended payables. While revenue stability reflects continuous operational activity, the liquidity position indicates potential risks in meeting short-term obligations.

The significant fluctuations in working capital, especially the sharp improvement in mid-2020 followed by a return to higher deficits, may reflect responses to external economic events or internal adjustments in asset and liability management practices.

Overall, the data imply that while sales performance remains consistent, working capital management challenges persist, highlighting the importance of monitoring liquidity and current asset efficiency to support ongoing operations and financial stability.


Average Inventory Processing Period

Hewlett Packard Enterprise Co., average inventory processing period calculation (quarterly data)

Microsoft Excel
Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data
Inventory turnover
Short-term Activity Ratio (no. days)
Average inventory processing period1
Benchmarks (no. days)
Average Inventory Processing Period, Competitors2
Apple Inc.
Arista Networks Inc.
Cisco Systems Inc.
Dell Technologies Inc.
Super Micro Computer Inc.

Based on: 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q2 2024 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =

2 Click competitor name to see calculations.


The analysis of the inventory turnover ratio and the average inventory processing period over the observed quarters indicates notable trends and shifts in operational efficiency.

Inventory Turnover Ratio
The inventory turnover ratio exhibits a declining trend overall from early 2019 to mid-2024. Initially, the ratio was relatively high, fluctuating around 9 to 8 in the first half of 2019. However, from 2020 onwards, there is a clear downward trajectory, with the ratio dropping sharply to around 5 in mid-2020. Although a modest recovery is observed towards late 2022 and early 2023, with the ratio rising above 4, this improvement is short-lived as the ratio declines again, reaching below 3 by the first quarter of 2024. This decreasing trend suggests a reducing frequency at which inventory is sold and replenished, possibly indicating challenges in inventory management or changes in demand patterns.
Average Inventory Processing Period
The average inventory processing period moves inversely to the turnover ratio, presenting an increasing trend from 2019 through mid-2024. Starting at approximately 39 days in early 2019, the period extends progressively, surpassing 100 days from 2021 onwards, and reaching a peak of 145 days by April 2024. This prolonged inventory holding period implies slower movement of inventory, potentially reflecting issues such as overstocking, decreased sales velocity, or supply chain constraints.
Relationship Between Metrics
The inverse relationship between inventory turnover and inventory processing period is consistent with inventory management principles: as turnover decreases, the processing period lengthens. The data underscores a sustained movement toward less efficient inventory turnover, which may impact liquidity and operational costs.
Operational Insights
The sustained decline in turnover ratio alongside a prolonged inventory processing period could signal the need for strategic reassessment of inventory policies. Potential areas of focus include demand forecasting accuracy, inventory replenishment strategies, and supply chain optimization to enhance inventory flow and reduce carrying costs.

Average Receivable Collection Period

Hewlett Packard Enterprise Co., average receivable collection period calculation (quarterly data)

Microsoft Excel
Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data
Receivables turnover
Short-term Activity Ratio (no. days)
Average receivable collection period1
Benchmarks (no. days)
Average Receivable Collection Period, Competitors2
Apple Inc.
Arista Networks Inc.
Cisco Systems Inc.
Dell Technologies Inc.
Super Micro Computer Inc.

Based on: 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q2 2024 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =

2 Click competitor name to see calculations.


Receivables Turnover
The receivables turnover ratio exhibits a fluctuating pattern over the observed periods. Starting at 9.65 in early 2019, the ratio experienced a moderate increase reaching its peak around 10.49 in April 2020. Following this peak, a marked decline is evident, with the ratio dropping to a low of approximately 6.95–6.98 in late 2020 and early 2021. A partial recovery ensued through 2022 and early 2023, with values climbing back toward the 8.6 range, although the turnover remained below the early period highs. The most recent figures from early 2024 show a slight decrease, settling around 7.37.
Average Receivable Collection Period
The average receivable collection period demonstrates an inverse relationship to the receivables turnover ratio, reflecting the expected dynamics. Initially at around 38 days in early 2019, it shortened modestly to a minimum near 35 days by April 2020. This improvement corresponds with the earlier noted peak in receivables turnover. Subsequently, the collection period lengthened significantly, reaching approximately 52–53 days in late 2020 and early 2021, indicating slower collections. During 2022 and into 2023, there was some improvement with the period reducing to the low 40-day range, but a renewed increase is apparent in early 2024, with collection days rising back to around 49–50.
Overall Trends and Insights
The data points to increased efficiency in receivables management up until early 2020, followed by a notable deterioration throughout late 2020 and into early 2021, likely reflecting changing business or economic conditions impacting collections. The partial recovery seen thereafter suggests some restoration of collection discipline or improved credit management; however, the metrics do not return to early period levels, indicating persistent challenges. The recent uptick in the collection period and corresponding dip in receivables turnover in early 2024 may warrant closer monitoring to identify underlying causes and potential risks to cash flow.

Operating Cycle

Hewlett Packard Enterprise Co., operating cycle calculation (quarterly data)

No. days

Microsoft Excel
Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data
Average inventory processing period
Average receivable collection period
Short-term Activity Ratio
Operating cycle1
Benchmarks
Operating Cycle, Competitors2
Apple Inc.
Arista Networks Inc.
Cisco Systems Inc.
Dell Technologies Inc.
Super Micro Computer Inc.

Based on: 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q2 2024 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 displayed a generally increasing trend over the analyzed timeframe. Starting at 39 days in early 2019, there was a gradual and steady rise, peaking at 109 days in January 2022. Following this peak, some fluctuations occurred with slight decreases and increases, reaching a high of 145 days by April 2024. This indicates a lengthening time in inventory turnover, suggesting slower inventory movement or possible stock accumulation over the years.
Average Receivable Collection Period
The average receivable collection period showed relative stability with minor fluctuations. Values largely remained in the 35 to 50-day range, starting at 38 days in early 2019 and ending at 50 days in April 2024. Some periods of increases were observed, such as the rise to 53 days in October 2022, followed by slight decreases and then a small increase again toward the end of the period. Overall, the collection period did not change dramatically but exhibited some volatility.
Operating Cycle
The operating cycle exhibited an upward trend, indicating an elongation in the overall time to convert inventory and receivables into cash. Beginning at 77 days in early 2019, the operating cycle increased steadily, reaching a high of 153 days in January 2023. After a slight decline to 127 days in April 2023, the cycle increased sharply once again to 195 days by April 2024. This trend reflects a deterioration in operational efficiency, suggesting the combined effect of slower inventory processing and stable to slightly increased receivables collection times.

Average Payables Payment Period

Hewlett Packard Enterprise Co., average payables payment period calculation (quarterly data)

Microsoft Excel
Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data
Payables turnover
Short-term Activity Ratio (no. days)
Average payables payment period1
Benchmarks (no. days)
Average Payables Payment Period, Competitors2
Apple Inc.
Arista Networks Inc.
Cisco Systems Inc.
Dell Technologies Inc.
Super Micro Computer Inc.

Based on: 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q2 2024 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ =

2 Click competitor name to see calculations.


Payables Turnover Ratio
The payables turnover ratio exhibits a generally declining trend from early 2019 to mid-2024. Initially, values ranged from around 3.68 to 3.9 but gradually decreased, reaching a low of 1.82 by April 2024. This decline indicates the company is turning over its payables less frequently over time, suggesting slower payments to suppliers or extended credit terms.
Average Payables Payment Period
The average payables payment period shows an opposing upward trend relative to the payables turnover ratio. Starting at approximately 94-99 days in early 2019, the payment period gradually increased, with fluctuations, peaking at 201 days by April 2024. This rise correlates with the reduced payables turnover, indicating the company is taking longer to settle its payables.
Trend Analysis
The inverse relationship between the payables turnover and the average payment period is clear. When the turnover ratio is high, the payment period is shorter, and vice versa. From 2019 through 2020, the company experienced moderate changes in these metrics, but from 2021 onwards, the payment period sharply increased, peaking in 2024. This pattern may reflect strategic decisions to conserve cash or changes in supplier payment agreements.
Implications
The increasing average payment period and decreasing payables turnover ratio could impact supplier relationships, potentially leading to negotiation opportunities or risks of strained relations. It also affects the company's working capital management, possibly indicating a deliberate extension of payment terms to improve liquidity. Monitoring these trends is important to assess financial health and operational efficiency.

Cash Conversion Cycle

Hewlett Packard Enterprise Co., cash conversion cycle calculation (quarterly data)

No. days

Microsoft Excel
Apr 30, 2024 Jan 31, 2024 Oct 31, 2023 Jul 31, 2023 Apr 30, 2023 Jan 31, 2023 Oct 31, 2022 Jul 31, 2022 Apr 30, 2022 Jan 31, 2022 Oct 31, 2021 Jul 31, 2021 Apr 30, 2021 Jan 31, 2021 Oct 31, 2020 Jul 31, 2020 Apr 30, 2020 Jan 31, 2020 Oct 31, 2019 Jul 31, 2019 Apr 30, 2019 Jan 31, 2019
Selected Financial Data
Average inventory processing period
Average receivable collection period
Average payables payment period
Short-term Activity Ratio
Cash conversion cycle1
Benchmarks
Cash Conversion Cycle, Competitors2
Apple Inc.
Arista Networks Inc.
Cisco Systems Inc.
Dell Technologies Inc.
Super Micro Computer Inc.

Based on: 10-Q (reporting date: 2024-04-30), 10-Q (reporting date: 2024-01-31), 10-K (reporting date: 2023-10-31), 10-Q (reporting date: 2023-07-31), 10-Q (reporting date: 2023-04-30), 10-Q (reporting date: 2023-01-31), 10-K (reporting date: 2022-10-31), 10-Q (reporting date: 2022-07-31), 10-Q (reporting date: 2022-04-30), 10-Q (reporting date: 2022-01-31), 10-K (reporting date: 2021-10-31), 10-Q (reporting date: 2021-07-31), 10-Q (reporting date: 2021-04-30), 10-Q (reporting date: 2021-01-31), 10-K (reporting date: 2020-10-31), 10-Q (reporting date: 2020-07-31), 10-Q (reporting date: 2020-04-30), 10-Q (reporting date: 2020-01-31), 10-K (reporting date: 2019-10-31), 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31).

1 Q2 2024 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= + =

2 Click competitor name to see calculations.


Inventory Processing Period
The average inventory processing period shows a generally increasing trend from January 2019 to April 2024. The duration rose from 39 days in early 2019 to a peak of 145 days by April 2024. Notably, there is a significant increase starting in 2020, with values exceeding 100 days from January 2022 onward. This indicates a lengthening time to process inventory, particularly accelerating during the later years observed.
Receivable Collection Period
The average receivable collection period demonstrates moderate fluctuations within a relatively narrow range, primarily between 35 and 53 days. It began at 38 days in January 2019, experienced minor spikes around 46 to 52 days in the years 2020 and 2021, and settled near 49 to 50 days by early 2024. This suggests the company maintained a reasonably consistent and stable collection period over the observed quarterlies, with some variations but no sustained upward or downward trend.
Payables Payment Period
The average payables payment period exhibits a pronounced upward movement over the timeline. Starting at 99 days in early 2019, the period extended substantially, reaching its highest values above 160 days in late 2023 and early 2024. The increase shows some volatility, with intermittent decreases, but the overall pattern points to longer durations before settling payables. This behavior may indicate strategic management of payment terms or potential liquidity considerations.
Cash Conversion Cycle
The cash conversion cycle shifted significantly during the reported period, moving from negative values around -22 days in early 2019 toward positive territory by 2021, peaking at 34 days in April 2022. Following this peak, the cycle exhibits volatility, alternating between positive and near-negative values. By April 2024, the cycle stands slightly negative at -6 days. The initial negative figures reflect a shorter time from cash outflow to cash receipt, which deteriorated around 2021-2022 before partially improving in recent quarters.
Summary Insights
The data reveals that inventory is taking progressively longer to process, possibly indicating challenges in inventory management or shifts in product mix. Receivable collections remain stable, implying consistent credit policies or customer payment behaviors. Payables payment periods have notably extended, which could be a tactic to manage cash flow or reflect supplier negotiations. The cash conversion cycle’s fluctuation, moving from negative to positive and back, suggests dynamic changes in working capital efficiency, influenced largely by the interplay of inventory and payables periods.