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)
HP Inc., short-term (operating) activity ratios (quarterly data)
Based on: 10-Q (reporting date: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31), 10-K (reporting date: 2018-10-31), 10-Q (reporting date: 2018-07-31), 10-Q (reporting date: 2018-04-30), 10-Q (reporting date: 2018-01-31), 10-K (reporting date: 2017-10-31), 10-Q (reporting date: 2017-07-31), 10-Q (reporting date: 2017-04-30), 10-Q (reporting date: 2017-01-31), 10-K (reporting date: 2016-10-31), 10-Q (reporting date: 2016-07-31), 10-Q (reporting date: 2016-04-30), 10-Q (reporting date: 2016-01-31), 10-K (reporting date: 2015-10-31), 10-Q (reporting date: 2015-07-31), 10-Q (reporting date: 2015-04-30), 10-Q (reporting date: 2015-01-31), 10-K (reporting date: 2014-10-31), 10-Q (reporting date: 2014-07-31), 10-Q (reporting date: 2014-04-30), 10-Q (reporting date: 2014-01-31), 10-K (reporting date: 2013-10-31), 10-Q (reporting date: 2013-07-31), 10-Q (reporting date: 2013-04-30), 10-Q (reporting date: 2013-01-31).
The financial data reveals several notable trends in the turnover ratios and operating cycle metrics over the observed periods.
- Inventory Turnover
- The inventory turnover ratio generally decreased from approximately 14 in early 2013 to around 8–9 by mid-2019. This declining trend suggests that the company is taking longer to sell its inventory, indicating a slower inventory movement or possibly increased stock levels relative to sales.
- Receivables Turnover
- The receivables turnover ratio showed some volatility but a noticeable decline overall. Starting near 7 in early 2013, it peaked significantly above 19 during 2015–2016 but then declined to around 10–12 in subsequent years. This implies a lengthening of the collection period or slower turnover of accounts receivable in the later periods.
- Payables Turnover
- The payables turnover ratio fell markedly from about 6–7 in 2013–2014 to roughly 3–3.5 by 2018–2019, indicating the company is taking longer to pay its suppliers. This trend may reflect more extended payment terms or cash management strategies to defer outflows.
- Working Capital Turnover
- Data for working capital turnover is limited, but the values fluctuate considerably, with peaks such as 35.77 in late 2015 and lower values around 10–20 in other periods. The irregular pattern suggests variability in how efficiently working capital is managed over the periods reported.
- Average Inventory Processing Period
- The number of days to process inventory increased significantly from mid-20s days in early periods to around 42–50 days during 2016–2018, before slightly declining towards 41–44 days in 2019. This increase aligns with the reduced inventory turnover, indicating slower inventory movement and possible buildup of stock.
- Average Receivable Collection Period
- The collection period shows a general increase from the low 40s of days in early periods to a peak nearing 30–34 days in recent years. Notably, there were periods of very low collection days (around 17–19 days) in 2015–2016, but these were not sustained. The longer collection periods in later years imply slower cash collection from customers.
- Operating Cycle
- The operating cycle, representing the total time between inventory acquisition and collection of receivables, fluctuated over the observed intervals but generally increased from mid-70s days to mid-80s days by 2017–2018 before settling near 75–78 days. This indicates a lengthening time to convert resources into cash.
- Average Payables Payment Period
- The average period to pay suppliers lengthened substantially, rising from about 59 days in early 2013 to over 100 days by 2016, and remaining elevated near 105–112 days through 2019. This longer payment cycle points to extended credit utilization from suppliers or delayed payments as a working capital strategy.
- Cash Conversion Cycle
- The cash conversion cycle (inventory processing plus receivables collection minus payables payment period) decreased steadily, turning negative starting in 2015 and reaching approximately -30 to -35 days through to 2019. A negative cash conversion cycle indicates that the company, on average, receives cash from sales before it has to pay its suppliers, effectively financing its operations through its suppliers' credit.
In summary, the data suggests the company has experienced slower inventory movement and receivables collection over the years, accompanied by significantly extended supplier payment periods. This combination has resulted in a negative cash conversion cycle, reflecting an operational model that leverages supplier credit to manage cash flows effectively. However, the longer processing and collection times may imply challenges in inventory management and customer collection efficiency, potentially increasing operational risk.
Turnover Ratios
Average No. Days
Inventory Turnover
HP Inc., inventory turnover calculation (quarterly data)
| Jul 31, 2019 | Apr 30, 2019 | Jan 31, 2019 | Oct 31, 2018 | Jul 31, 2018 | Apr 30, 2018 | Jan 31, 2018 | Oct 31, 2017 | Jul 31, 2017 | Apr 30, 2017 | Jan 31, 2017 | Oct 31, 2016 | Jul 31, 2016 | Apr 30, 2016 | Jan 31, 2016 | Oct 31, 2015 | Jul 31, 2015 | Apr 30, 2015 | Jan 31, 2015 | Oct 31, 2014 | Jul 31, 2014 | Apr 30, 2014 | Jan 31, 2014 | Oct 31, 2013 | Jul 31, 2013 | Apr 30, 2013 | Jan 31, 2013 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | |||||||||||||||||||||||||||||||||||
| Cost of revenue | 11,698) | 11,307) | 12,098) | 12,669) | 11,898) | 11,301) | 11,935) | 11,407) | 10,633) | 10,002) | 10,436) | 10,221) | 9,720) | 9,338) | 9,961) | 19,363) | 19,317) | 19,345) | 20,571) | 21,425) | 20,974) | 20,704) | 21,736) | 22,437) | 20,859) | 21,055) | 22,029) | ||||||||
| Inventory | 5,716) | 5,394) | 5,649) | 6,062) | 6,091) | 5,557) | 5,655) | 5,786) | 5,184) | 4,756) | 4,555) | 4,484) | 3,961) | 3,547) | 4,052) | 6,485) | 6,700) | 6,227) | 6,575) | 6,415) | 6,249) | 5,840) | 6,004) | 6,046) | 6,540) | 5,999) | 6,374) | ||||||||
| Short-term Activity Ratio | |||||||||||||||||||||||||||||||||||
| Inventory turnover1 | 8.36 | 8.89 | 8.49 | 7.89 | 7.64 | 8.15 | 7.78 | 7.34 | 7.97 | 8.49 | 8.72 | 8.75 | 12.21 | 16.35 | 16.78 | 12.12 | 12.04 | 13.22 | 12.73 | 13.23 | 13.74 | 14.68 | 14.34 | 14.29 | — | — | — | ||||||||
| 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: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31), 10-K (reporting date: 2018-10-31), 10-Q (reporting date: 2018-07-31), 10-Q (reporting date: 2018-04-30), 10-Q (reporting date: 2018-01-31), 10-K (reporting date: 2017-10-31), 10-Q (reporting date: 2017-07-31), 10-Q (reporting date: 2017-04-30), 10-Q (reporting date: 2017-01-31), 10-K (reporting date: 2016-10-31), 10-Q (reporting date: 2016-07-31), 10-Q (reporting date: 2016-04-30), 10-Q (reporting date: 2016-01-31), 10-K (reporting date: 2015-10-31), 10-Q (reporting date: 2015-07-31), 10-Q (reporting date: 2015-04-30), 10-Q (reporting date: 2015-01-31), 10-K (reporting date: 2014-10-31), 10-Q (reporting date: 2014-07-31), 10-Q (reporting date: 2014-04-30), 10-Q (reporting date: 2014-01-31), 10-K (reporting date: 2013-10-31), 10-Q (reporting date: 2013-07-31), 10-Q (reporting date: 2013-04-30), 10-Q (reporting date: 2013-01-31).
1 Q3 2019 Calculation
Inventory turnover
= (Cost of revenueQ3 2019
+ Cost of revenueQ2 2019
+ Cost of revenueQ1 2019
+ Cost of revenueQ4 2018)
÷ Inventory
= (11,698 + 11,307 + 12,098 + 12,669)
÷ 5,716 = 8.36
2 Click competitor name to see calculations.
An analysis of the quarterly financial data reveals several notable trends in cost of revenue, inventory levels, and inventory turnover ratios over the periods presented.
- Cost of Revenue
- The cost of revenue exhibits a cyclical pattern with some fluctuations across the quarters. Initially, from early 2013 through 2015, the cost generally trends downward, reaching a low point in April 2016 at 9,338 million US dollars, which is roughly half of the amounts seen in 2013. After this significant decline, there is a gradual upward movement from mid-2016 onwards, with values climbing back above 11,000 million US dollars by mid-2018 and early 2019. The trend shows some volatility but reflects an overall pattern of sharp decline followed by moderate recovery.
- Inventory
- Inventory values also demonstrate variability but are somewhat correlated with the cost of revenue trend. Initially, inventory shows a declining trend from early 2013 to April 2014, stabilizing around the 5,800 to 6,500 million US dollars range through 2015. From January 2016, inventory decreases sharply to a low of 3,547 million US dollars in April 2016, mirroring the cost of revenue drop. Subsequently, a recovery phase occurs with inventory values rising steadily, reaching approximately 6,000 million US dollars by late 2018. This suggests inventory management adjustments aligned with revenue costs.
- Inventory Turnover Ratio
- The inventory turnover ratio, which measures how many times inventory is sold and replaced over a period, shows a downward trend from high levels in late 2013 and early 2014 (around 14 to 16) to significantly lower levels in the later years. Starting at approximately 16.78 in January 2016, the ratio steadily declines to below 8 by early 2018, indicating slower turnover rates. This decline could imply either inventory accumulation or reduced sales efficiency relative to inventory levels. A slight improvement is seen towards mid-2019 with ratios increasing moderately to about 8.89 but remaining much lower than earlier in the dataset period.
Overall, the data suggests that the company experienced a period of cost reductions and inventory downsizing around 2015-2016, followed by a phase of gradual recovery in both cost of revenue and inventory levels. The decline in inventory turnover ratio over time points to a slowdown in inventory movement relative to sales, which may warrant attention regarding operational efficiency or changes in demand patterns.
Receivables Turnover
HP Inc., receivables turnover calculation (quarterly data)
| Jul 31, 2019 | Apr 30, 2019 | Jan 31, 2019 | Oct 31, 2018 | Jul 31, 2018 | Apr 30, 2018 | Jan 31, 2018 | Oct 31, 2017 | Jul 31, 2017 | Apr 30, 2017 | Jan 31, 2017 | Oct 31, 2016 | Jul 31, 2016 | Apr 30, 2016 | Jan 31, 2016 | Oct 31, 2015 | Jul 31, 2015 | Apr 30, 2015 | Jan 31, 2015 | Oct 31, 2014 | Jul 31, 2014 | Apr 30, 2014 | Jan 31, 2014 | Oct 31, 2013 | Jul 31, 2013 | Apr 30, 2013 | Jan 31, 2013 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | |||||||||||||||||||||||||||||||||||
| Net revenue | 14,603) | 14,036) | 14,710) | 15,366) | 14,586) | 14,003) | 14,517) | 13,927) | 13,060) | 12,385) | 12,684) | 12,512) | 11,892) | 11,588) | 12,246) | 25,714) | 25,349) | 25,453) | 26,839) | 28,406) | 27,585) | 27,309) | 28,154) | 29,131) | 27,226) | 27,582) | 28,359) | ||||||||
| Accounts receivable, net | 5,295) | 5,414) | 5,113) | 5,113) | 4,615) | 4,605) | 4,396) | 4,414) | 4,233) | 3,771) | 3,478) | 4,114) | 4,008) | 3,884) | 4,114) | 13,363) | 12,753) | 12,320) | 12,295) | 13,832) | 14,198) | 14,288) | 13,492) | 15,876) | 14,336) | 14,606) | 14,236) | ||||||||
| Short-term Activity Ratio | |||||||||||||||||||||||||||||||||||
| Receivables turnover1 | 11.09 | 10.84 | 11.47 | 11.44 | 12.36 | 12.05 | 12.26 | 11.79 | 11.96 | 13.12 | 14.00 | 11.73 | 15.33 | 19.28 | 21.58 | 7.73 | 8.32 | 8.79 | 8.96 | 8.06 | 7.90 | 7.83 | 8.31 | 7.07 | — | — | — | ||||||||
| 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: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31), 10-K (reporting date: 2018-10-31), 10-Q (reporting date: 2018-07-31), 10-Q (reporting date: 2018-04-30), 10-Q (reporting date: 2018-01-31), 10-K (reporting date: 2017-10-31), 10-Q (reporting date: 2017-07-31), 10-Q (reporting date: 2017-04-30), 10-Q (reporting date: 2017-01-31), 10-K (reporting date: 2016-10-31), 10-Q (reporting date: 2016-07-31), 10-Q (reporting date: 2016-04-30), 10-Q (reporting date: 2016-01-31), 10-K (reporting date: 2015-10-31), 10-Q (reporting date: 2015-07-31), 10-Q (reporting date: 2015-04-30), 10-Q (reporting date: 2015-01-31), 10-K (reporting date: 2014-10-31), 10-Q (reporting date: 2014-07-31), 10-Q (reporting date: 2014-04-30), 10-Q (reporting date: 2014-01-31), 10-K (reporting date: 2013-10-31), 10-Q (reporting date: 2013-07-31), 10-Q (reporting date: 2013-04-30), 10-Q (reporting date: 2013-01-31).
1 Q3 2019 Calculation
Receivables turnover
= (Net revenueQ3 2019
+ Net revenueQ2 2019
+ Net revenueQ1 2019
+ Net revenueQ4 2018)
÷ Accounts receivable, net
= (14,603 + 14,036 + 14,710 + 15,366)
÷ 5,295 = 11.09
2 Click competitor name to see calculations.
The data reveals several noteworthy trends in the quarterly financial performance and operational metrics over the periods analyzed.
- Net Revenue
- Net revenue demonstrates fluctuations with an initial range between approximately 27 billion and 29 billion US dollars in 2013 and 2014. Subsequently, a decline is observed in 2015, with quarterly revenues dropping to the range of roughly 25 billion to 26 billion US dollars. This decline is pronounced in early 2016, where revenues roughly halve, but this is likely reflective of a change in reporting or a restatement rather than an actual decline in business activity. From 2016 onwards, net revenue appears lower in absolute terms but shows a gradual increase indicative of recovery or growth until the end of the last period, reaching values around 14 to 15 billion US dollars.
- Accounts Receivable, Net
- Accounts receivable mirror the trend seen in net revenue. Initial values range around 13 to 16 billion US dollars from 2013 to 2015, followed by a significant drop in early 2016, consistent with the change seen in revenues. After this drop, receivables show a general upward trend through the subsequent years, increasing from roughly 3.9 billion to just above 5.4 billion US dollars by mid-2019. This trend points to increased credit sales or extended collection periods in recent periods.
- Receivables Turnover Ratio
- The receivables turnover ratio, available from 2013 onward, exhibits declining efficiency in collecting receivables up until early 2016, where it decreases from approximately 8.3 to 7.7. Post-2016, the ratio undergoes higher volatility with unusually elevated early 2016 values likely caused by data adjustments. Generally, after these outlying points, the turnover ratio stabilizes around 11 to 12 times annually, reflecting moderate efficiency in receivables collection. The slight decline towards latter periods to about 10.8 to 11.1 suggests a marginally slower collection process over time.
In summary, these data indicate an overall contraction in reported revenue and receivables mid-period, followed by stabilization and modest growth from 2016 onwards. The receivables turnover ratio also suggests some fluctuations in collection effectiveness, with some weakening collection efficiency in the most recent quarters. The noted drop in absolute values in 2016 likely reflects an accounting or reporting change rather than mere operational performance shifts.
Payables Turnover
HP Inc., payables turnover calculation (quarterly data)
| Jul 31, 2019 | Apr 30, 2019 | Jan 31, 2019 | Oct 31, 2018 | Jul 31, 2018 | Apr 30, 2018 | Jan 31, 2018 | Oct 31, 2017 | Jul 31, 2017 | Apr 30, 2017 | Jan 31, 2017 | Oct 31, 2016 | Jul 31, 2016 | Apr 30, 2016 | Jan 31, 2016 | Oct 31, 2015 | Jul 31, 2015 | Apr 30, 2015 | Jan 31, 2015 | Oct 31, 2014 | Jul 31, 2014 | Apr 30, 2014 | Jan 31, 2014 | Oct 31, 2013 | Jul 31, 2013 | Apr 30, 2013 | Jan 31, 2013 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | |||||||||||||||||||||||||||||||||||
| Cost of revenue | 11,698) | 11,307) | 12,098) | 12,669) | 11,898) | 11,301) | 11,935) | 11,407) | 10,633) | 10,002) | 10,436) | 10,221) | 9,720) | 9,338) | 9,961) | 19,363) | 19,317) | 19,345) | 20,571) | 21,425) | 20,974) | 20,704) | 21,736) | 22,437) | 20,859) | 21,055) | 22,029) | ||||||||
| Accounts payable | 14,648) | 13,839) | 14,572) | 14,816) | 14,245) | 13,054) | 12,848) | 13,279) | 12,804) | 11,079) | 10,951) | 11,103) | 10,402) | 9,099) | 9,041) | 15,956) | 15,549) | 14,923) | 14,873) | 15,903) | 15,141) | 13,521) | 12,640) | 14,019) | 13,293) | 12,313) | 11,660) | ||||||||
| Short-term Activity Ratio | |||||||||||||||||||||||||||||||||||
| Payables turnover1 | 3.26 | 3.47 | 3.29 | 3.23 | 3.27 | 3.47 | 3.42 | 3.20 | 3.22 | 3.64 | 3.63 | 3.53 | 4.65 | 6.37 | 7.52 | 4.93 | 5.19 | 5.52 | 5.63 | 5.33 | 5.67 | 6.34 | 6.81 | 6.16 | — | — | — | ||||||||
| 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: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31), 10-K (reporting date: 2018-10-31), 10-Q (reporting date: 2018-07-31), 10-Q (reporting date: 2018-04-30), 10-Q (reporting date: 2018-01-31), 10-K (reporting date: 2017-10-31), 10-Q (reporting date: 2017-07-31), 10-Q (reporting date: 2017-04-30), 10-Q (reporting date: 2017-01-31), 10-K (reporting date: 2016-10-31), 10-Q (reporting date: 2016-07-31), 10-Q (reporting date: 2016-04-30), 10-Q (reporting date: 2016-01-31), 10-K (reporting date: 2015-10-31), 10-Q (reporting date: 2015-07-31), 10-Q (reporting date: 2015-04-30), 10-Q (reporting date: 2015-01-31), 10-K (reporting date: 2014-10-31), 10-Q (reporting date: 2014-07-31), 10-Q (reporting date: 2014-04-30), 10-Q (reporting date: 2014-01-31), 10-K (reporting date: 2013-10-31), 10-Q (reporting date: 2013-07-31), 10-Q (reporting date: 2013-04-30), 10-Q (reporting date: 2013-01-31).
1 Q3 2019 Calculation
Payables turnover
= (Cost of revenueQ3 2019
+ Cost of revenueQ2 2019
+ Cost of revenueQ1 2019
+ Cost of revenueQ4 2018)
÷ Accounts payable
= (11,698 + 11,307 + 12,098 + 12,669)
÷ 14,648 = 3.26
2 Click competitor name to see calculations.
The cost of revenue demonstrates an overall declining trend from January 2013 through mid-2016, decreasing from approximately 22,029 million USD to a low near 9,338 million USD in April 2016. After this trough, the values exhibit a gradual upward movement, reaching around 12,698 million USD by October 2018, followed by a moderate decline toward mid-2019, ending near 11,698 million USD. This pattern suggests a significant reduction in cost structure over the initial years with stabilization and slight fluctuations thereafter.
Accounts payable exhibits a general increasing trajectory throughout the period analyzed, starting at roughly 11,660 million USD in January 2013 and rising to a peak exceeding 15,956 million USD by October 2015. A sharp drop is observed in the first quarter of 2016, coinciding with the nadir in cost of revenue, falling to approximately 9,041 million USD. Subsequently, accounts payable steadily increases again, reaching about 14,816 million USD by April 2019, with minor fluctuations towards the end of the period. This behavior indicates an expansion in credit utilization or supplier financing except for the brief contraction in early 2016.
The payables turnover ratio, available from July 2013 onward, reveals a declining trend indicative of slower payment cycles over time. Initially, the ratio was high at around 6.16 to 6.81 in the mid-2013 to early-2014 period, gradually decreasing to values near 3.2 to 3.6 in 2017 and remaining relatively stable through to mid-2019. This downward trend suggests that the company is taking longer to settle its payables or that accounts payable is increasing at a faster pace relative to the cost of revenue, aligning with the observed rise in accounts payable levels.
Overall, the financial data indicate a significant contraction in cost of revenue up to 2016, accompanied by fluctuations in accounts payable that mirror this trend but with a delayed rebound. The declining payables turnover ratio throughout the period points to extended payment terms or slower payments to suppliers. These trends could reflect strategic supply chain and working capital management adjustments impacting the liquidity and operational cash flow dynamics over the analyzed quarters.
Working Capital Turnover
HP Inc., working capital turnover calculation (quarterly data)
| Jul 31, 2019 | Apr 30, 2019 | Jan 31, 2019 | Oct 31, 2018 | Jul 31, 2018 | Apr 30, 2018 | Jan 31, 2018 | Oct 31, 2017 | Jul 31, 2017 | Apr 30, 2017 | Jan 31, 2017 | Oct 31, 2016 | Jul 31, 2016 | Apr 30, 2016 | Jan 31, 2016 | Oct 31, 2015 | Jul 31, 2015 | Apr 30, 2015 | Jan 31, 2015 | Oct 31, 2014 | Jul 31, 2014 | Apr 30, 2014 | Jan 31, 2014 | Oct 31, 2013 | Jul 31, 2013 | Apr 30, 2013 | Jan 31, 2013 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | |||||||||||||||||||||||||||||||||||
| Current assets | 19,683) | 18,285) | 18,936) | 21,387) | 21,776) | 19,433) | 21,217) | 22,318) | 21,443) | 18,302) | 17,775) | 18,468) | 17,402) | 15,385) | 15,155) | 51,787) | 51,998) | 48,883) | 48,198) | 50,145) | 49,287) | 49,883) | 50,684) | 50,364) | 49,958) | 49,571) | 49,552) | ||||||||
| Less: Current liabilities | 24,579) | 23,203) | 24,199) | 25,131) | 25,506) | 23,127) | 23,349) | 22,412) | 22,060) | 18,604) | 18,587) | 18,808) | 18,114) | 16,862) | 16,761) | 42,191) | 49,033) | 43,186) | 42,529) | 43,735) | 42,476) | 43,280) | 43,611) | 45,521) | 46,012) | 44,658) | 44,386) | ||||||||
| Working capital | (4,896) | (4,918) | (5,263) | (3,744) | (3,730) | (3,694) | (2,132) | (94) | (617) | (302) | (812) | (340) | (712) | (1,477) | (1,606) | 9,596) | 2,965) | 5,697) | 5,669) | 6,410) | 6,811) | 6,603) | 7,073) | 4,843) | 3,946) | 4,913) | 5,166) | ||||||||
| Net revenue | 14,603) | 14,036) | 14,710) | 15,366) | 14,586) | 14,003) | 14,517) | 13,927) | 13,060) | 12,385) | 12,684) | 12,512) | 11,892) | 11,588) | 12,246) | 25,714) | 25,349) | 25,453) | 26,839) | 28,406) | 27,585) | 27,309) | 28,154) | 29,131) | 27,226) | 27,582) | 28,359) | ||||||||
| Short-term Activity Ratio | |||||||||||||||||||||||||||||||||||
| Working capital turnover1 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 10.77 | 35.77 | 19.01 | 19.43 | 17.39 | 16.47 | 16.93 | 15.85 | 23.19 | — | — | — | ||||||||
| 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: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31), 10-K (reporting date: 2018-10-31), 10-Q (reporting date: 2018-07-31), 10-Q (reporting date: 2018-04-30), 10-Q (reporting date: 2018-01-31), 10-K (reporting date: 2017-10-31), 10-Q (reporting date: 2017-07-31), 10-Q (reporting date: 2017-04-30), 10-Q (reporting date: 2017-01-31), 10-K (reporting date: 2016-10-31), 10-Q (reporting date: 2016-07-31), 10-Q (reporting date: 2016-04-30), 10-Q (reporting date: 2016-01-31), 10-K (reporting date: 2015-10-31), 10-Q (reporting date: 2015-07-31), 10-Q (reporting date: 2015-04-30), 10-Q (reporting date: 2015-01-31), 10-K (reporting date: 2014-10-31), 10-Q (reporting date: 2014-07-31), 10-Q (reporting date: 2014-04-30), 10-Q (reporting date: 2014-01-31), 10-K (reporting date: 2013-10-31), 10-Q (reporting date: 2013-07-31), 10-Q (reporting date: 2013-04-30), 10-Q (reporting date: 2013-01-31).
1 Q3 2019 Calculation
Working capital turnover
= (Net revenueQ3 2019
+ Net revenueQ2 2019
+ Net revenueQ1 2019
+ Net revenueQ4 2018)
÷ Working capital
= (14,603 + 14,036 + 14,710 + 15,366)
÷ -4,896 = —
2 Click competitor name to see calculations.
- Working Capital
- The working capital figures demonstrate considerable volatility over the periods under review. Initial quarters show positive working capital values, peaking at 7,073 million US dollars in January 2014. However, from early 2016 onwards, working capital shifts prominently into negative territory, reaching a low of -5,263 million US dollars by January 2019. This decline suggests increasing liquidity pressures or possible shifts in current asset and liability management strategies.
- Net Revenue
- Net revenue exhibits a somewhat cyclical pattern with overall moderate fluctuations. Starting from 28,359 million US dollars in the first quarter of 2013, revenues fluctuate within a range generally between approximately 25,000 million and 29,000 million US dollars through 2015. In the period from 2016 to 2019, net revenue data appears segmented, but the trend shows a gradual increase toward the later quarters, peaking around 15,366 million US dollars in October 2018. Seasonal effects or market demand variations may influence these patterns.
- Working Capital Turnover
- Limited data is available for working capital turnover ratios, with some quarters missing values entirely. Among the provided figures, there is a notable peak of 35.77 during one quarter, indicating a significant increase in efficiency relating to working capital utilization in converting it to sales. However, other recorded turnover ratios, such as 10.77 or those around 15 to 20, suggest variability in operational efficiency or perhaps the impact of fluctuating working capital levels on turnover calculations.
- Overall Analysis
- The analysis reflects a company experiencing unstable working capital conditions, particularly trending negative after 2015, which could indicate potential liquidity management challenges despite relatively stable or slightly growing net revenues. The erratic nature of the working capital turnover ratio further highlights fluctuating operational efficiency in relation to working capital deployment. This combination underscores the importance of focusing on working capital optimization to support sustainable revenue generation and financial stability.
Average Inventory Processing Period
HP Inc., average inventory processing period calculation (quarterly data)
| Jul 31, 2019 | Apr 30, 2019 | Jan 31, 2019 | Oct 31, 2018 | Jul 31, 2018 | Apr 30, 2018 | Jan 31, 2018 | Oct 31, 2017 | Jul 31, 2017 | Apr 30, 2017 | Jan 31, 2017 | Oct 31, 2016 | Jul 31, 2016 | Apr 30, 2016 | Jan 31, 2016 | Oct 31, 2015 | Jul 31, 2015 | Apr 30, 2015 | Jan 31, 2015 | Oct 31, 2014 | Jul 31, 2014 | Apr 30, 2014 | Jan 31, 2014 | Oct 31, 2013 | Jul 31, 2013 | Apr 30, 2013 | Jan 31, 2013 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | |||||||||||||||||||||||||||||||||||
| Inventory turnover | 8.36 | 8.89 | 8.49 | 7.89 | 7.64 | 8.15 | 7.78 | 7.34 | 7.97 | 8.49 | 8.72 | 8.75 | 12.21 | 16.35 | 16.78 | 12.12 | 12.04 | 13.22 | 12.73 | 13.23 | 13.74 | 14.68 | 14.34 | 14.29 | — | — | — | ||||||||
| Short-term Activity Ratio (no. days) | |||||||||||||||||||||||||||||||||||
| Average inventory processing period1 | 44 | 41 | 43 | 46 | 48 | 45 | 47 | 50 | 46 | 43 | 42 | 42 | 30 | 22 | 22 | 30 | 30 | 28 | 29 | 28 | 27 | 25 | 25 | 26 | — | — | — | ||||||||
| 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: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31), 10-K (reporting date: 2018-10-31), 10-Q (reporting date: 2018-07-31), 10-Q (reporting date: 2018-04-30), 10-Q (reporting date: 2018-01-31), 10-K (reporting date: 2017-10-31), 10-Q (reporting date: 2017-07-31), 10-Q (reporting date: 2017-04-30), 10-Q (reporting date: 2017-01-31), 10-K (reporting date: 2016-10-31), 10-Q (reporting date: 2016-07-31), 10-Q (reporting date: 2016-04-30), 10-Q (reporting date: 2016-01-31), 10-K (reporting date: 2015-10-31), 10-Q (reporting date: 2015-07-31), 10-Q (reporting date: 2015-04-30), 10-Q (reporting date: 2015-01-31), 10-K (reporting date: 2014-10-31), 10-Q (reporting date: 2014-07-31), 10-Q (reporting date: 2014-04-30), 10-Q (reporting date: 2014-01-31), 10-K (reporting date: 2013-10-31), 10-Q (reporting date: 2013-07-31), 10-Q (reporting date: 2013-04-30), 10-Q (reporting date: 2013-01-31).
1 Q3 2019 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ 8.36 = 44
2 Click competitor name to see calculations.
- Inventory Turnover
- The inventory turnover ratio begins at 14.29 in January 2014 and exhibits a generally declining trend over the observed periods. It decreases gradually through 2014 and 2015, with some fluctuations, reaching a low of 7.34 by January 2018. The ratio slightly recovers afterward but remains below earlier levels, ending at 8.36 by July 2019. This decline suggests that the frequency of inventory replacement has reduced over time, indicative of either slower sales or higher inventory levels relative to cost of goods sold.
- Average Inventory Processing Period
- The average inventory processing period, measured in days, inversely mirrors the inventory turnover ratio. Starting at 26 days in January 2014, this metric fluctuates moderately through 2014 and 2015. From 2016 onward, there is a clear upward trend, peaking at 50 days in January 2018. This indicates that inventory is being held for increasingly longer periods before sale, suggesting decreased sales velocity or increased inventory accumulation. There is a moderate reduction after this peak, with the processing period decreasing to 44 days by July 2019, although it remains significantly higher than the initial period.
- Overall Insights
- The inverse relationship between the inventory turnover ratio and the average inventory processing period is consistent with standard inventory management principles. The declining turnover alongside increasing days of inventory on hand indicates a shift toward slower inventory movement across these years. Such a trend could suggest challenges in demand forecasting, changes in product mix, or operational inefficiencies. The stabilization and slight improvement in the latter periods may reflect adjustments made to address these issues, but overall inventory management efficiency appears to have diminished compared to the starting period.
Average Receivable Collection Period
HP Inc., average receivable collection period calculation (quarterly data)
| Jul 31, 2019 | Apr 30, 2019 | Jan 31, 2019 | Oct 31, 2018 | Jul 31, 2018 | Apr 30, 2018 | Jan 31, 2018 | Oct 31, 2017 | Jul 31, 2017 | Apr 30, 2017 | Jan 31, 2017 | Oct 31, 2016 | Jul 31, 2016 | Apr 30, 2016 | Jan 31, 2016 | Oct 31, 2015 | Jul 31, 2015 | Apr 30, 2015 | Jan 31, 2015 | Oct 31, 2014 | Jul 31, 2014 | Apr 30, 2014 | Jan 31, 2014 | Oct 31, 2013 | Jul 31, 2013 | Apr 30, 2013 | Jan 31, 2013 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | |||||||||||||||||||||||||||||||||||
| Receivables turnover | 11.09 | 10.84 | 11.47 | 11.44 | 12.36 | 12.05 | 12.26 | 11.79 | 11.96 | 13.12 | 14.00 | 11.73 | 15.33 | 19.28 | 21.58 | 7.73 | 8.32 | 8.79 | 8.96 | 8.06 | 7.90 | 7.83 | 8.31 | 7.07 | — | — | — | ||||||||
| Short-term Activity Ratio (no. days) | |||||||||||||||||||||||||||||||||||
| Average receivable collection period1 | 33 | 34 | 32 | 32 | 30 | 30 | 30 | 31 | 31 | 28 | 26 | 31 | 24 | 19 | 17 | 47 | 44 | 42 | 41 | 45 | 46 | 47 | 44 | 52 | — | — | — | ||||||||
| 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: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31), 10-K (reporting date: 2018-10-31), 10-Q (reporting date: 2018-07-31), 10-Q (reporting date: 2018-04-30), 10-Q (reporting date: 2018-01-31), 10-K (reporting date: 2017-10-31), 10-Q (reporting date: 2017-07-31), 10-Q (reporting date: 2017-04-30), 10-Q (reporting date: 2017-01-31), 10-K (reporting date: 2016-10-31), 10-Q (reporting date: 2016-07-31), 10-Q (reporting date: 2016-04-30), 10-Q (reporting date: 2016-01-31), 10-K (reporting date: 2015-10-31), 10-Q (reporting date: 2015-07-31), 10-Q (reporting date: 2015-04-30), 10-Q (reporting date: 2015-01-31), 10-K (reporting date: 2014-10-31), 10-Q (reporting date: 2014-07-31), 10-Q (reporting date: 2014-04-30), 10-Q (reporting date: 2014-01-31), 10-K (reporting date: 2013-10-31), 10-Q (reporting date: 2013-07-31), 10-Q (reporting date: 2013-04-30), 10-Q (reporting date: 2013-01-31).
1 Q3 2019 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ 11.09 = 33
2 Click competitor name to see calculations.
- Receivables Turnover Ratio
- The receivables turnover ratio demonstrates considerable fluctuations over the observed periods. Initially, from January 2014 through October 2015, the ratio remained relatively stable, ranging mostly between 7.07 and 8.96. A sharp surge occurs in early 2016, where the ratio spikes significantly to 21.58, followed by a gradual and steady decline across subsequent quarters to a level around 11 by mid-2017. This ratio then stabilizes near the 11 to 12 range through to mid-2019, with minor variations but no return to the earlier spike.
- Average Receivable Collection Period
- This metric shows an inverse relationship to the receivables turnover, as expected. In the early part of the data, from January 2014 through October 2015, the average collection period mostly ranges between 41 and 52 days, indicating a moderately consistent collection time. Starting in January 2016, a marked reduction occurs, with the average collection period dropping sharply to as low as 17 days. Subsequently, the average days slowly increase again to around 31 days by the end of 2017 and remain fairly consistent at approximately 30 to 34 days through mid-2019.
- Overall Trend and Insights
- The data indicates a period of relatively steady receivables turnover and collection times in the early years followed by a significant improvement in turnover and collection efficiency around early 2016. The sudden increase in turnover coupled with the decreased collection period suggests enhanced receivables management or possible changes in credit policy during this time. After this sharp improvement, performance metrics stabilized at a higher turnover and quicker collection pace compared to initial periods, indicating sustained efficiency gains. The modest rise in average collection days after the initial improvement might indicate a return to more normalized collection practices or business conditions.
Operating Cycle
HP Inc., operating cycle calculation (quarterly data)
No. days
| Jul 31, 2019 | Apr 30, 2019 | Jan 31, 2019 | Oct 31, 2018 | Jul 31, 2018 | Apr 30, 2018 | Jan 31, 2018 | Oct 31, 2017 | Jul 31, 2017 | Apr 30, 2017 | Jan 31, 2017 | Oct 31, 2016 | Jul 31, 2016 | Apr 30, 2016 | Jan 31, 2016 | Oct 31, 2015 | Jul 31, 2015 | Apr 30, 2015 | Jan 31, 2015 | Oct 31, 2014 | Jul 31, 2014 | Apr 30, 2014 | Jan 31, 2014 | Oct 31, 2013 | Jul 31, 2013 | Apr 30, 2013 | Jan 31, 2013 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | |||||||||||||||||||||||||||||||||||
| Average inventory processing period | 44 | 41 | 43 | 46 | 48 | 45 | 47 | 50 | 46 | 43 | 42 | 42 | 30 | 22 | 22 | 30 | 30 | 28 | 29 | 28 | 27 | 25 | 25 | 26 | — | — | — | ||||||||
| Average receivable collection period | 33 | 34 | 32 | 32 | 30 | 30 | 30 | 31 | 31 | 28 | 26 | 31 | 24 | 19 | 17 | 47 | 44 | 42 | 41 | 45 | 46 | 47 | 44 | 52 | — | — | — | ||||||||
| Short-term Activity Ratio | |||||||||||||||||||||||||||||||||||
| Operating cycle1 | 77 | 75 | 75 | 78 | 78 | 75 | 77 | 81 | 77 | 71 | 68 | 73 | 54 | 41 | 39 | 77 | 74 | 70 | 70 | 73 | 73 | 72 | 69 | 78 | — | — | — | ||||||||
| 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: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31), 10-K (reporting date: 2018-10-31), 10-Q (reporting date: 2018-07-31), 10-Q (reporting date: 2018-04-30), 10-Q (reporting date: 2018-01-31), 10-K (reporting date: 2017-10-31), 10-Q (reporting date: 2017-07-31), 10-Q (reporting date: 2017-04-30), 10-Q (reporting date: 2017-01-31), 10-K (reporting date: 2016-10-31), 10-Q (reporting date: 2016-07-31), 10-Q (reporting date: 2016-04-30), 10-Q (reporting date: 2016-01-31), 10-K (reporting date: 2015-10-31), 10-Q (reporting date: 2015-07-31), 10-Q (reporting date: 2015-04-30), 10-Q (reporting date: 2015-01-31), 10-K (reporting date: 2014-10-31), 10-Q (reporting date: 2014-07-31), 10-Q (reporting date: 2014-04-30), 10-Q (reporting date: 2014-01-31), 10-K (reporting date: 2013-10-31), 10-Q (reporting date: 2013-07-31), 10-Q (reporting date: 2013-04-30), 10-Q (reporting date: 2013-01-31).
1 Q3 2019 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= 44 + 33 = 77
2 Click competitor name to see calculations.
The average inventory processing period displays notable variability across the observed quarters. Initial data points from early 2014 show a relatively stable range around 25 to 30 days. However, starting from early 2016, the period increases significantly, peaking at 50 days in early 2018, followed by a slight decline but remaining elevated around the mid-40 days mark toward mid-2019. This suggests a gradual lengthening of the inventory processing duration over time, indicating potential changes in inventory management or supply chain dynamics.
The average receivable collection period shows a decreasing trend from early 2014, starting at around 52 days and dropping to approximately 41 days by early 2015, reflecting an improvement in receivable collection efficiency. However, there is a sharp decline to 17 days in early 2016, followed by a gradual increase again reaching approximately mid-30s days by mid-2019. This pattern could indicate short-term improvements in credit management followed by a return to longer collection cycles, possibly due to shifting credit policies or customer payment behaviors.
The operating cycle, which combines the inventory processing and receivable collection periods, mirrors these trends with some lag. It starts around 78 days in early 2014 and decreases significantly to the high 30s by early 2016, then gradually increases again to the high 70s by late 2018, stabilizing around the mid to high 70s days in 2019. The decline until 2016 reflects an overall efficiency gain in managing inventory and receivables, whereas the subsequent increase points to elongating working capital cycles, possibly signaling operational or market challenges impacting cash conversion efficiency.
- Inventory Processing Period
- Generally stable around 25 to 30 days until early 2016, followed by a pronounced increase to 50 days in early 2018, with moderate decreases thereafter.
- Receivable Collection Period
- Initial improvement reducing days from low 50s to around 41 by early 2015, a sharp dip to 17 days in early 2016, then a gradual rise to mid-30s by mid-2019.
- Operating Cycle
- Declined from high 70s in early 2014 to high 30s by early 2016, then increased again to stabilize around mid-high 70s by 2019.
Overall, the data reflect periods of operational efficiency improvements particularly around early 2016, followed by a trend of elongating cycles that may warrant further investigation into underlying causes such as inventory management practices or changes in customer payment terms.
Average Payables Payment Period
HP Inc., average payables payment period calculation (quarterly data)
| Jul 31, 2019 | Apr 30, 2019 | Jan 31, 2019 | Oct 31, 2018 | Jul 31, 2018 | Apr 30, 2018 | Jan 31, 2018 | Oct 31, 2017 | Jul 31, 2017 | Apr 30, 2017 | Jan 31, 2017 | Oct 31, 2016 | Jul 31, 2016 | Apr 30, 2016 | Jan 31, 2016 | Oct 31, 2015 | Jul 31, 2015 | Apr 30, 2015 | Jan 31, 2015 | Oct 31, 2014 | Jul 31, 2014 | Apr 30, 2014 | Jan 31, 2014 | Oct 31, 2013 | Jul 31, 2013 | Apr 30, 2013 | Jan 31, 2013 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | |||||||||||||||||||||||||||||||||||
| Payables turnover | 3.26 | 3.47 | 3.29 | 3.23 | 3.27 | 3.47 | 3.42 | 3.20 | 3.22 | 3.64 | 3.63 | 3.53 | 4.65 | 6.37 | 7.52 | 4.93 | 5.19 | 5.52 | 5.63 | 5.33 | 5.67 | 6.34 | 6.81 | 6.16 | — | — | — | ||||||||
| Short-term Activity Ratio (no. days) | |||||||||||||||||||||||||||||||||||
| Average payables payment period1 | 112 | 105 | 111 | 113 | 112 | 105 | 107 | 114 | 113 | 100 | 101 | 103 | 78 | 57 | 49 | 74 | 70 | 66 | 65 | 68 | 64 | 58 | 54 | 59 | — | — | — | ||||||||
| 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: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31), 10-K (reporting date: 2018-10-31), 10-Q (reporting date: 2018-07-31), 10-Q (reporting date: 2018-04-30), 10-Q (reporting date: 2018-01-31), 10-K (reporting date: 2017-10-31), 10-Q (reporting date: 2017-07-31), 10-Q (reporting date: 2017-04-30), 10-Q (reporting date: 2017-01-31), 10-K (reporting date: 2016-10-31), 10-Q (reporting date: 2016-07-31), 10-Q (reporting date: 2016-04-30), 10-Q (reporting date: 2016-01-31), 10-K (reporting date: 2015-10-31), 10-Q (reporting date: 2015-07-31), 10-Q (reporting date: 2015-04-30), 10-Q (reporting date: 2015-01-31), 10-K (reporting date: 2014-10-31), 10-Q (reporting date: 2014-07-31), 10-Q (reporting date: 2014-04-30), 10-Q (reporting date: 2014-01-31), 10-K (reporting date: 2013-10-31), 10-Q (reporting date: 2013-07-31), 10-Q (reporting date: 2013-04-30), 10-Q (reporting date: 2013-01-31).
1 Q3 2019 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ 3.26 = 112
2 Click competitor name to see calculations.
The analysis of the payables turnover ratio and the average payables payment period over the reported quarters reveals distinct trends indicating changing payment behaviors and operational conditions.
- Payables Turnover Ratio
- The payables turnover ratio shows a notable decline over time. Starting at 6.16 in January 2014, it reached a lower range around 3.2 to 3.6 from early 2017 through 2019. The highest value recorded was 7.52 in April 2016, which appears as an outlier within the observed period. Overall, the ratio decreased substantially from the initial values, indicating that the company is paying its suppliers less frequently within the period or that the payables balance is increasing relative to cost of goods sold.
- Average Payables Payment Period
- This metric corresponds inversely to the payables turnover and shows an increasing trend over the periods examined. From an initial 59 days in January 2014, the payment period extended to over 100 days consistently from January 2017 onward, peaking at 114 days in October 2017. This lengthening of the payment period suggests that the company is taking longer to settle its accounts payable, reflecting either a strategic extension of payment terms or potential liquidity management practices.
- Interrelation and Implications
- The inverse correlation between the payables turnover ratio and the average payment period is consistent across the data. A lower turnover ratio (fewer times payables are turned over) aligns with an increased number of days to pay. This trend may indicate shifting supplier credit terms, changes in cash flow management, or efforts to optimize working capital. However, prolonged payment periods could also strain supplier relationships and impact the company's creditworthiness if extended beyond industry norms.
- Volatility and Outliers
- The significant spike in the payables turnover ratio in April 2016 contrasts sharply with surrounding periods, accompanied by a sudden drop in the payment period to 49 days. This deviation may reflect one-time operational or accounting changes, seasonal effects, or adjustments in financial policies that temporarily improved turnover and shortened payment duration.
In summary, the company exhibits a trend of increasingly extended payment periods coupled with reduced turnover ratios over the observation period, indicating a strategic shift towards longer payables durations. The fluctuations and outliers observed suggest episodes of variation in financial management or external conditions impacting accounts payable dynamics.
Cash Conversion Cycle
HP Inc., cash conversion cycle calculation (quarterly data)
No. days
| Jul 31, 2019 | Apr 30, 2019 | Jan 31, 2019 | Oct 31, 2018 | Jul 31, 2018 | Apr 30, 2018 | Jan 31, 2018 | Oct 31, 2017 | Jul 31, 2017 | Apr 30, 2017 | Jan 31, 2017 | Oct 31, 2016 | Jul 31, 2016 | Apr 30, 2016 | Jan 31, 2016 | Oct 31, 2015 | Jul 31, 2015 | Apr 30, 2015 | Jan 31, 2015 | Oct 31, 2014 | Jul 31, 2014 | Apr 30, 2014 | Jan 31, 2014 | Oct 31, 2013 | Jul 31, 2013 | Apr 30, 2013 | Jan 31, 2013 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | |||||||||||||||||||||||||||||||||||
| Average inventory processing period | 44 | 41 | 43 | 46 | 48 | 45 | 47 | 50 | 46 | 43 | 42 | 42 | 30 | 22 | 22 | 30 | 30 | 28 | 29 | 28 | 27 | 25 | 25 | 26 | — | — | — | ||||||||
| Average receivable collection period | 33 | 34 | 32 | 32 | 30 | 30 | 30 | 31 | 31 | 28 | 26 | 31 | 24 | 19 | 17 | 47 | 44 | 42 | 41 | 45 | 46 | 47 | 44 | 52 | — | — | — | ||||||||
| Average payables payment period | 112 | 105 | 111 | 113 | 112 | 105 | 107 | 114 | 113 | 100 | 101 | 103 | 78 | 57 | 49 | 74 | 70 | 66 | 65 | 68 | 64 | 58 | 54 | 59 | — | — | — | ||||||||
| Short-term Activity Ratio | |||||||||||||||||||||||||||||||||||
| Cash conversion cycle1 | -35 | -30 | -36 | -35 | -34 | -30 | -30 | -33 | -36 | -29 | -33 | -30 | -24 | -16 | -10 | 3 | 4 | 4 | 5 | 5 | 9 | 14 | 15 | 19 | — | — | — | ||||||||
| 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: 2019-07-31), 10-Q (reporting date: 2019-04-30), 10-Q (reporting date: 2019-01-31), 10-K (reporting date: 2018-10-31), 10-Q (reporting date: 2018-07-31), 10-Q (reporting date: 2018-04-30), 10-Q (reporting date: 2018-01-31), 10-K (reporting date: 2017-10-31), 10-Q (reporting date: 2017-07-31), 10-Q (reporting date: 2017-04-30), 10-Q (reporting date: 2017-01-31), 10-K (reporting date: 2016-10-31), 10-Q (reporting date: 2016-07-31), 10-Q (reporting date: 2016-04-30), 10-Q (reporting date: 2016-01-31), 10-K (reporting date: 2015-10-31), 10-Q (reporting date: 2015-07-31), 10-Q (reporting date: 2015-04-30), 10-Q (reporting date: 2015-01-31), 10-K (reporting date: 2014-10-31), 10-Q (reporting date: 2014-07-31), 10-Q (reporting date: 2014-04-30), 10-Q (reporting date: 2014-01-31), 10-K (reporting date: 2013-10-31), 10-Q (reporting date: 2013-07-31), 10-Q (reporting date: 2013-04-30), 10-Q (reporting date: 2013-01-31).
1 Q3 2019 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= 44 + 33 – 112 = -35
2 Click competitor name to see calculations.
- Average Inventory Processing Period
- The inventory processing period exhibits some fluctuations over the observed quarters, beginning with values in the mid-20s range around 2013 and 2014, then showing a declining trend reaching as low as 22 days in early 2016. Subsequently, the period increases significantly, peaking at 50 days in early 2018 before gradually declining again to around 44 days towards mid-2019. This pattern indicates variability in inventory turnover efficiency, with notable lengthening during 2017 and early 2018.
- Average Receivable Collection Period
- The receivable collection period demonstrates a general downward trend, starting from mid-40s around 2013-2014, decreasing sharply to the late teens and low twenties by early 2016. Thereafter, it fluctuates between 26 and 34 days through 2017 to 2019, suggesting some stabilization but with slightly higher values than the trough in early 2016. This suggests improvement in the speed of receivable collection up to 2016, followed by a period of moderate consistency with minor increases.
- Average Payables Payment Period
- The payables payment period fluctuates considerably across the timeline. It begins around the mid-60s in 2013-2014, peaks at over 100 days between late 2016 and early 2018, and then slightly decreases but remains elevated above 100 days by mid-2019. The extended payment period indicates that the company pushed to delay outflows to suppliers more aggressively starting from 2016, maintaining longer payment cycles thereafter.
- Cash Conversion Cycle
- The cash conversion cycle (CCC) reflects significant improvement over time, transitioning from positive values around 19 days in 2013-2014 to progressively negative values from late 2015 through mid-2019, reaching lows near -36 days. The negative CCC indicates the company successfully managed to convert resources into cash faster, benefiting from quicker receivables collection and/or longer payables periods relative to inventory turnover. This trend is supportive of improved liquidity and enhanced working capital efficiency.