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.
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Short-term Activity Ratios (Summary)
Halliburton Co., short-term (operating) activity ratios (quarterly data)
Based on: 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-09-30), 10-Q (reporting date: 2016-06-30), 10-Q (reporting date: 2016-03-31), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-30), 10-Q (reporting date: 2015-06-30), 10-Q (reporting date: 2015-03-31), 10-K (reporting date: 2014-12-31), 10-Q (reporting date: 2014-09-30), 10-Q (reporting date: 2014-06-30), 10-Q (reporting date: 2014-03-31).
The analysis of the financial ratios and periods shows notable trends over the examined intervals.
- Inventory Turnover
- The inventory turnover ratio exhibited a general decline from its initial values near 9 in 2014 and early 2015, decreasing to a low around 6.4 in late 2016 and 2018. Values somewhat recovered to just under 8 by late 2017 and mid-2018. This suggests a slowing in inventory efficiency over the period with intermittent improvements.
- Receivables Turnover
- The receivables turnover ratio showed a gradual decline from a peak above 5.4 in late 2014 to values around 3.85-4.58 by the end of 2018. This trend implies that the company was collecting receivables less quickly over time, reflecting potential elongation in credit terms or slower customer payments.
- Payables Turnover
- The payables turnover ratio decreased significantly from highs above 11 between mid-2014 and early 2015 to approximately 6.6-7.2 by late 2017 and 2018, indicating the company took longer to pay its suppliers as time progressed.
- Working Capital Turnover
- Working capital turnover dropped sharply from near 3.7 in mid-2014 to a low below 1.5 in early 2016, signifying reduced efficiency in generating sales from working capital. After 2016, there was a steady improvement reaching approximately 3.7-3.8 by late 2018, indicating enhanced working capital efficiency possibly due to better management or operational adjustments.
- Average Inventory Processing Period
- The average number of days to process inventory remained relatively stable, fluctuating slightly around 40 to 55 days throughout the period. Longer periods occurred in 2016-2018, suggesting slower inventory turnover consistent with the decreased inventory turnover ratio.
- Average Receivable Collection Period
- The average receivable collection period increased from around 68-72 days in 2014 to over 90 days by late 2016 and remained near that level through 2017 and early 2018 before improving to about 80 days by the end of 2018. This pattern corroborates the decrease in receivables turnover, indicating slower collections.
- Operating Cycle
- The operating cycle initially shortened from about 132 days early on to around 108 days in late 2014 but trended upwards reaching roughly 150 days by late 2016, then gradually declining to about 133 days by the end of 2018. This suggests the overall period needed to turn inventory and receivables into sales and cash lengthened before improving again.
- Average Payables Payment Period
- The average payables payment period increased steadily from around 31-32 days in 2014 to peaks above 50 days in 2017 and remained elevated near 52-55 days through 2018. This trend indicates longer payment delays to suppliers, possibly reflecting changes in credit terms or cash management priorities.
- Cash Conversion Cycle
- The cash conversion cycle lengthened from approximately 77 days in late 2014 to over 116 days in late 2016, before decreasing to near 80 days by the end of 2018. The initial rise points to a period of reduced cash efficiency, followed by a recovery indicating improved management of cash flows and working capital.
Overall, the data reveals a period of operational stress and inefficiencies between 2015 and 2016, especially noticeable in slower inventory movement, longer receivable collections, and extended payables periods. Following this period, incremental improvements in working capital turnover and cash conversion suggest efforts were made to restore operational efficiency and cash flow management.
Turnover Ratios
Average No. Days
Inventory Turnover
Halliburton Co., inventory turnover calculation (quarterly data)
| Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | Dec 31, 2016 | Sep 30, 2016 | Jun 30, 2016 | Mar 31, 2016 | Dec 31, 2015 | Sep 30, 2015 | Jun 30, 2015 | Mar 31, 2015 | Dec 31, 2014 | Sep 30, 2014 | Jun 30, 2014 | Mar 31, 2014 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||
| Cost of services and product sales | ||||||||||||||||||||||||||
| Inventories | ||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||
| Inventory turnover1 | ||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||
| Inventory Turnover, Competitors2 | ||||||||||||||||||||||||||
| Schlumberger Ltd. | ||||||||||||||||||||||||||
Based on: 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-09-30), 10-Q (reporting date: 2016-06-30), 10-Q (reporting date: 2016-03-31), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-30), 10-Q (reporting date: 2015-06-30), 10-Q (reporting date: 2015-03-31), 10-K (reporting date: 2014-12-31), 10-Q (reporting date: 2014-09-30), 10-Q (reporting date: 2014-06-30), 10-Q (reporting date: 2014-03-31).
1 Q4 2018 Calculation
Inventory turnover
= (Cost of services and product salesQ4 2018
+ Cost of services and product salesQ3 2018
+ Cost of services and product salesQ2 2018
+ Cost of services and product salesQ1 2018)
÷ Inventories
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The quarterly financial data reveal several notable trends in the company's operational efficiency and inventory management over the observed periods.
- Cost of Services and Product Sales
- The cost of services and product sales displays a general decreasing trend from March 31, 2014, through December 31, 2015. It starts at 6,303 million US dollars and declines to 4,556 million by the end of 2015, indicating a substantial reduction in cost outlays. After this period, the cost values remain relatively stable with minor fluctuations, staying in the range of approximately 3,662 to 5,384 million US dollars, without a clear upward or downward trend as of the last reported quarter in December 31, 2018.
- Inventories
- The inventory levels generally show a declining pattern from the beginning of the timeline through the end of 2015, dropping from 3,415 million to 2,417 million US dollars. Following this, inventories stabilize somewhat with minor increases and decreases around the 2,300 to 3,000 million range, ultimately trending slightly upward toward the end of the series, reaching 3,028 million in December 2018.
- Inventory Turnover Ratio
- The inventory turnover ratio, available from March 31, 2015, onwards, exhibits variability across quarters. It peaks above 9 in mid-2015, indicating high efficiency in inventory management during that period. Following this peak, the ratio falls gradually and stabilizes in the mid-6 to 7 range over the years, indicating moderate inventory efficiency. There is a slight upward movement of turnover starting mid-2017, with values approaching and slightly exceeding 7, which suggests improving inventory utilization during these later periods.
Overall, the data suggest a concerted effort to reduce both cost of sales and inventory levels until late 2015, followed by a period of stabilization with moderate fluctuations. The inventory turnover ratio supports this observation by reflecting an initial period of high efficiency that moderates but slightly improves toward the end of the timeline. These patterns may indicate adjustments in supply chain management and operational strategies aiming at cost control and improved asset utilization.
Receivables Turnover
Halliburton Co., receivables turnover calculation (quarterly data)
| Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | Dec 31, 2016 | Sep 30, 2016 | Jun 30, 2016 | Mar 31, 2016 | Dec 31, 2015 | Sep 30, 2015 | Jun 30, 2015 | Mar 31, 2015 | Dec 31, 2014 | Sep 30, 2014 | Jun 30, 2014 | Mar 31, 2014 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||
| Revenue | ||||||||||||||||||||||||||
| Receivables, net of allowances for bad debts | ||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||
| Receivables turnover1 | ||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||
| Receivables Turnover, Competitors2 | ||||||||||||||||||||||||||
| Schlumberger Ltd. | ||||||||||||||||||||||||||
Based on: 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-09-30), 10-Q (reporting date: 2016-06-30), 10-Q (reporting date: 2016-03-31), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-30), 10-Q (reporting date: 2015-06-30), 10-Q (reporting date: 2015-03-31), 10-K (reporting date: 2014-12-31), 10-Q (reporting date: 2014-09-30), 10-Q (reporting date: 2014-06-30), 10-Q (reporting date: 2014-03-31).
1 Q4 2018 Calculation
Receivables turnover
= (RevenueQ4 2018
+ RevenueQ3 2018
+ RevenueQ2 2018
+ RevenueQ1 2018)
÷ Receivables, net of allowances for bad debts
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The financial data reveals fluctuations and trends across multiple quarters from March 2014 to December 2018, with specific focus on revenue, receivables, and receivables turnover ratios.
- Revenue Trends
- Revenue exhibited a rising trend during 2014, peaking at 8,770 million USD in the fourth quarter. However, from 2015 onwards, there was a notable decline, reaching a low point of 3,833 million USD in the third quarter of 2016. After this trough, revenue gradually recovered throughout 2017 and into 2018, stabilizing near the 6,000 million USD mark by the end of 2018. This pattern indicates an initial growth phase followed by significant contraction and then a gradual recovery phase.
- Receivables, net of allowances for bad debts
- The net receivables mirrored the decline in revenue, showing an overall downward trajectory from early 2014 through to late 2016, falling from 7,555 million USD in the third quarter of 2014 to 3,922 million USD by the end of 2016. However, unlike revenue, receivables stabilized and began a moderate increase starting in 2017, ending 2018 at approximately 5,234 million USD. This suggests improved collection or billing management after a period of contraction.
- Receivables Turnover Ratio
- The receivables turnover ratio showed variability without a consistent increasing or decreasing trend. It initially ranged around 4.35 in early 2015, climbed to a peak of 5.4 in the third quarter of 2015, which may indicate enhanced efficiency in collections at that time. Following this peak, it decreased gradually to lower points near 3.85 in late 2017, then showed a moderate upward trend again toward the end of the period, climbing to 4.58 by the last quarter of 2018. This fluctuation implies changes in credit policy or collection efficiency impacting how quickly receivables were converted into cash.
Overall, the data illustrates a cyclical pattern with an initial growth phase, followed by significant decline and subsequent recovery across revenue and receivables. Efficiency in receivables management, as evidenced by the turnover ratio, experienced volatility, suggesting adjustments in operational or credit control strategies during this period.
Payables Turnover
Halliburton Co., payables turnover calculation (quarterly data)
Based on: 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-09-30), 10-Q (reporting date: 2016-06-30), 10-Q (reporting date: 2016-03-31), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-30), 10-Q (reporting date: 2015-06-30), 10-Q (reporting date: 2015-03-31), 10-K (reporting date: 2014-12-31), 10-Q (reporting date: 2014-09-30), 10-Q (reporting date: 2014-06-30), 10-Q (reporting date: 2014-03-31).
1 Q4 2018 Calculation
Payables turnover
= (Cost of services and product salesQ4 2018
+ Cost of services and product salesQ3 2018
+ Cost of services and product salesQ2 2018
+ Cost of services and product salesQ1 2018)
÷ Accounts payable
= ( + + + )
÷ =
The financial data reveals notable trends in cost management and payables efficiency over the specified periods.
- Cost of Services and Product Sales
- Over the examined quarters, the cost of services and product sales exhibits a general declining trend from early 2014 through 2016. Costs decrease from approximately $6.3 billion in March 2014 to a low near $3.7 billion in mid-2016, indicating effective cost control or reduced business activity. However, starting in early 2017, costs begin to rise steadily, reaching above $5.1 billion by the end of 2017 and maintaining near that level through 2018. This reversal suggests increased operational expenditure or growth in sales volume.
- Accounts Payable
- Accounts payable follow a similar pattern to costs, decreasing from over $2.5 billion in early 2014 to around $1.5 billion mid-2016. Post-2016, there is a consistent increase, peaking at approximately $3.1 billion by late 2018. This indicates that the company is extending its payment terms or experiencing increasing purchases on credit, possibly linked to the rising operational expenses observed in costs.
- Payables Turnover Ratio
- The payables turnover ratio, which measures how quickly the company pays its suppliers, starts at 9.71 in early 2015 and improves to a high of 11.82 in late 2015, showing faster payments during that period. From 2016 onward, the ratio declines steadily to around 6.63 by late 2018, indicating a lengthening of payment cycles. This trend aligns with the increase in accounts payable, suggesting more extended credit usage or timing shifts in payables management.
In summary, the data demonstrates an initial period of decreasing costs and payables coupled with faster payment to suppliers, followed by a phase of rising costs and payables with slower payment turnover. These patterns may reflect changes in operational scale and payment strategies over the examined timeframe.
Working Capital Turnover
Halliburton Co., working capital turnover calculation (quarterly data)
| Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | Dec 31, 2016 | Sep 30, 2016 | Jun 30, 2016 | Mar 31, 2016 | Dec 31, 2015 | Sep 30, 2015 | Jun 30, 2015 | Mar 31, 2015 | Dec 31, 2014 | Sep 30, 2014 | Jun 30, 2014 | Mar 31, 2014 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||
| Current assets | ||||||||||||||||||||||||||
| Less: Current liabilities | ||||||||||||||||||||||||||
| Working capital | ||||||||||||||||||||||||||
| Revenue | ||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||
| Working capital turnover1 | ||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||
| Working Capital Turnover, Competitors2 | ||||||||||||||||||||||||||
| Schlumberger Ltd. | ||||||||||||||||||||||||||
Based on: 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-09-30), 10-Q (reporting date: 2016-06-30), 10-Q (reporting date: 2016-03-31), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-30), 10-Q (reporting date: 2015-06-30), 10-Q (reporting date: 2015-03-31), 10-K (reporting date: 2014-12-31), 10-Q (reporting date: 2014-09-30), 10-Q (reporting date: 2014-06-30), 10-Q (reporting date: 2014-03-31).
1 Q4 2018 Calculation
Working capital turnover
= (RevenueQ4 2018
+ RevenueQ3 2018
+ RevenueQ2 2018
+ RevenueQ1 2018)
÷ Working capital
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The financial data reveals several observable trends related to working capital, revenue, and working capital turnover over the examined periods.
- Working Capital
- The working capital exhibited fluctuations throughout the periods. Initially, it showed a gradual increase from $8,554 million at the end of March 2014 to a peak of $16,250 million by December 31, 2015. This peak represents a significant increase compared to previous quarters. Following this peak, there was a notable decline reaching as low as approximately $5,543 million by September 30, 2017. Subsequently, from late 2017 through 2018, working capital displayed mild fluctuations but remained relatively stable, oscillating around $6,000 to $6,500 million.
- Revenue
- Revenue followed a generally downward trajectory starting at $7,348 million in March 2014 and declining to its lowest point of approximately $3,833 million around September 30, 2016. After this period, the revenue began to recover gradually, reaching approximately $5,940 million by December 31, 2017. However, toward the end of 2018, revenue showed signs of tapering off slightly, ending at about $5,936 million in December 2018.
- Working Capital Turnover
- Working capital turnover ratios, available from the period ending March 31, 2014, exhibit an inverse relationship compared to working capital levels. The turnover ratio initially declined sharply from 3.58 at the end of March 2014 to a low of 1.45 by March 31, 2016—aligning with the peak and subsequent decline of working capital and revenue. Following this low, turnover gradually increased over the subsequent quarters, reaching 3.78 by the end of December 2018. This indicates improved efficiency in the use of working capital to generate revenue over the latter part of the timeline.
Overall, the data underscores a period of significant volatility, particularly marked by sharply contrasting movements in working capital and revenue between 2014 and 2016. The low turnover ratios during 2015 and early 2016 coincide with high working capital and low revenue levels, suggesting potential inefficiency in asset utilization during this period. Conversely, post-2016 periods demonstrate a recovery in revenue and an improvement in working capital turnover, signifying enhanced operational efficiency and more effective management of current assets relative to revenue generation.
Average Inventory Processing Period
Halliburton Co., average inventory processing period calculation (quarterly data)
| Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | Dec 31, 2016 | Sep 30, 2016 | Jun 30, 2016 | Mar 31, 2016 | Dec 31, 2015 | Sep 30, 2015 | Jun 30, 2015 | Mar 31, 2015 | Dec 31, 2014 | Sep 30, 2014 | Jun 30, 2014 | Mar 31, 2014 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||
| Inventory turnover | ||||||||||||||||||||||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||
| Average inventory processing period1 | ||||||||||||||||||||||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||
| Average Inventory Processing Period, Competitors2 | ||||||||||||||||||||||||||
| Schlumberger Ltd. | ||||||||||||||||||||||||||
Based on: 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-09-30), 10-Q (reporting date: 2016-06-30), 10-Q (reporting date: 2016-03-31), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-30), 10-Q (reporting date: 2015-06-30), 10-Q (reporting date: 2015-03-31), 10-K (reporting date: 2014-12-31), 10-Q (reporting date: 2014-09-30), 10-Q (reporting date: 2014-06-30), 10-Q (reporting date: 2014-03-31).
1 Q4 2018 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =
2 Click competitor name to see calculations.
- Inventory Turnover
- Beginning from the first available quarter, the inventory turnover ratio started at 7.65 and showed a slight increase to a peak of 9.11 by the third quarter of 2014. Subsequently, the ratio experienced a moderate decline towards the end of 2015, reaching approximately 8.74. Throughout 2016, a noticeable decrease is observed with the turnover falling to about 6.41, remaining relatively stable around this lower level through 2017. During 2018, the ratio showed a gradual recovery, increasing from 6.94 in the first quarter to a high of 7.89 in the middle of the year, before trending slightly downwards again by the last quarter.
- Average Inventory Processing Period
- This metric inversely correlates with inventory turnover and begins, where data is first available, at 48 days in early 2014. There is an improvement in inventory efficiency as this period shortens to 40 days by the third quarter of 2014. However, starting in 2015, there is a reversal, with the processing period increasing to an elevated average of around 56-57 days during most of 2016. The period stabilizes somewhat during 2017, dropping to near 48-53 days, indicating some improvement in inventory management. In 2018, the processing period fluctuates moderately, ending the year marginally higher at 53 days compared to the start of the year.
- General Observations
- The data indicates that inventory management efficiency improved initially up to late 2014, but faced challenges afterward with a decline in turnover and longer processing periods through 2016. Partial recovery is apparent in subsequent years, though the company did not reach the peak efficiency levels observed in 2014. Fluctuations in 2018 suggest variability in operational factors affecting inventory handling. These patterns may warrant further investigation to identify underlying causes and improve inventory control.
Average Receivable Collection Period
Halliburton Co., average receivable collection period calculation (quarterly data)
| Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | Dec 31, 2016 | Sep 30, 2016 | Jun 30, 2016 | Mar 31, 2016 | Dec 31, 2015 | Sep 30, 2015 | Jun 30, 2015 | Mar 31, 2015 | Dec 31, 2014 | Sep 30, 2014 | Jun 30, 2014 | Mar 31, 2014 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||
| Receivables turnover | ||||||||||||||||||||||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||
| Average receivable collection period1 | ||||||||||||||||||||||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||
| Average Receivable Collection Period, Competitors2 | ||||||||||||||||||||||||||
| Schlumberger Ltd. | ||||||||||||||||||||||||||
Based on: 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-09-30), 10-Q (reporting date: 2016-06-30), 10-Q (reporting date: 2016-03-31), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-30), 10-Q (reporting date: 2015-06-30), 10-Q (reporting date: 2015-03-31), 10-K (reporting date: 2014-12-31), 10-Q (reporting date: 2014-09-30), 10-Q (reporting date: 2014-06-30), 10-Q (reporting date: 2014-03-31).
1 Q4 2018 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =
2 Click competitor name to see calculations.
- Receivables Turnover
- The receivables turnover ratio data begins from the first quarter of 2015, showing an initial increasing trend from 4.35 to a peak of 5.40 by the third quarter of 2015. Following this peak, there is a gradual decline through late 2015 and into 2016, reaching a low of 3.89 by the fourth quarter of 2016. The ratio then experiences minor fluctuations around the 4.00 mark during 2017, with a slight upward trend starting late 2017 and continuing through 2018, ending at 4.58 in the final reported quarter. This pattern suggests an initial improvement in efficiency in collecting receivables, followed by a period of reduced efficiency, and a moderate recovery in collection management towards the end of the period.
- Average Receivable Collection Period
- The average receivable collection period shows an inverse relationship with receivables turnover, as expected. Starting at 84 days in the first quarter of 2015, it shortens to a minimum of 68 days by the third quarter of 2015, indicating an improvement in the speed of collecting receivables. After this low point, the collection period lengthens steadily, peaking at 95 days during the third quarter of 2017. Following this peak, there is a gradual reduction in the collection period across 2018, ending at 80 days in the last quarter. The fluctuations in the collection period confirm the changes observed in turnover, reflecting the variation in the company's efficiency in managing credit and collections over the analyzed timeframe.
Operating Cycle
Halliburton Co., operating cycle calculation (quarterly data)
No. days
| Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | Dec 31, 2017 | Sep 30, 2017 | Jun 30, 2017 | Mar 31, 2017 | Dec 31, 2016 | Sep 30, 2016 | Jun 30, 2016 | Mar 31, 2016 | Dec 31, 2015 | Sep 30, 2015 | Jun 30, 2015 | Mar 31, 2015 | Dec 31, 2014 | Sep 30, 2014 | Jun 30, 2014 | Mar 31, 2014 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||
| Average inventory processing period | ||||||||||||||||||||||||||
| Average receivable collection period | ||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||
| Operating cycle1 | ||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||
| Operating Cycle, Competitors2 | ||||||||||||||||||||||||||
| Schlumberger Ltd. | ||||||||||||||||||||||||||
Based on: 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-09-30), 10-Q (reporting date: 2016-06-30), 10-Q (reporting date: 2016-03-31), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-30), 10-Q (reporting date: 2015-06-30), 10-Q (reporting date: 2015-03-31), 10-K (reporting date: 2014-12-31), 10-Q (reporting date: 2014-09-30), 10-Q (reporting date: 2014-06-30), 10-Q (reporting date: 2014-03-31).
1 Q4 2018 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 experienced a decline from 48 days in March 2015 to 40 days by September 2015, indicating improved efficiency in inventory management during this time. However, starting from the fourth quarter of 2015, this period began to increase steadily, reaching a peak of 57 days in the third quarter of 2016. Subsequently, the period gradually decreased and stabilized around the mid-50s range from late 2016 to early 2018, finishing at 53 days at the end of 2018. This pattern suggests a temporary slowdown in inventory turnover followed by a return to more moderate processing times.
- Average Receivable Collection Period
- The average receivable collection period demonstrated a downward trend from 84 days in March 2015 to a low of 68 days by September 2015, reflecting an improved collection efficiency. However, this was short-lived, as the period then increased consistently, reaching approximately 95 days by December 2017, indicating a lengthening in the time taken to collect receivables. From the beginning of 2018, there was a notable improvement, with days decreasing back to 80 by the end of the same year. This indicates volatility in collection performance, with a notable peak in collection delays during 2016 and 2017 followed by recovery in 2018.
- Operating Cycle
- The operating cycle, combining inventory processing and receivables collection periods, mirrors the trends observed in the two components. It decreased between March 2015 and September 2015 from 132 days to 108 days, reflecting enhanced overall operational efficiency. From late 2015 to late 2016, the operating cycle lengthened significantly to about 151 days, signaling slower operational throughput. Thereafter, the cycle remained relatively stable, fluctuating around the 145 to 150 day mark until the end of 2017. During 2018, the cycle slightly shortened, finishing the year at 133 days. This suggests improvements in working capital management toward the end of the period observed.
Average Payables Payment Period
Halliburton Co., average payables payment period calculation (quarterly data)
Based on: 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-09-30), 10-Q (reporting date: 2016-06-30), 10-Q (reporting date: 2016-03-31), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-30), 10-Q (reporting date: 2015-06-30), 10-Q (reporting date: 2015-03-31), 10-K (reporting date: 2014-12-31), 10-Q (reporting date: 2014-09-30), 10-Q (reporting date: 2014-06-30), 10-Q (reporting date: 2014-03-31).
1 Q4 2018 Calculation
Average payables payment period = 365 ÷ Payables turnover
= 365 ÷ =
- Payables Turnover Ratio
- The payables turnover ratio experienced a marked decline from the initial recorded value of 9.71 in March 2015 to a low of 6.63 in the third quarter of 2018. Initially, this ratio increased to 11.82 in September 2015, indicating faster payments to suppliers during that period. However, from this peak, there was a consistent downward trend through to the end of 2018, suggesting that the company was taking longer to pay its payables over time. The ratio dipped below 7 starting in the first quarter of 2017 and remained generally stable but low around this range through 2018.
- Average Payables Payment Period (Days)
- The average payables payment period exhibited an upward movement, indicating lengthening payment cycles. Starting at 38 days in March 2015, the period shortened notably to 31 days in September 2015, which corresponds inversely to the peak in the payables turnover ratio. Beyond this point, the payment period steadily increased, reaching a peak of 55 days in the third and fourth quarters of 2018. This pattern confirms a trend toward longer payment durations with suppliers. The increase was gradual but consistent, rising from the mid-30s in 2015 to the mid-50s in 2018.
- Overall Observations
- There is a clear inverse relationship between the payables turnover ratio and the average days payable outstanding, which aligns with typical financial behavior. The data suggests a strategic shift or necessity for the company to extend its accounts payable duration over the analyzed period. This could imply improved cash flow management, negotiating longer payment terms, or potential liquidity constraints requiring the company to slow down payments. The gradual change over several quarters indicates a sustained adjustment rather than short-term fluctuations.
Cash Conversion Cycle
Halliburton Co., cash conversion cycle calculation (quarterly data)
No. days
Based on: 10-K (reporting date: 2018-12-31), 10-Q (reporting date: 2018-09-30), 10-Q (reporting date: 2018-06-30), 10-Q (reporting date: 2018-03-31), 10-K (reporting date: 2017-12-31), 10-Q (reporting date: 2017-09-30), 10-Q (reporting date: 2017-06-30), 10-Q (reporting date: 2017-03-31), 10-K (reporting date: 2016-12-31), 10-Q (reporting date: 2016-09-30), 10-Q (reporting date: 2016-06-30), 10-Q (reporting date: 2016-03-31), 10-K (reporting date: 2015-12-31), 10-Q (reporting date: 2015-09-30), 10-Q (reporting date: 2015-06-30), 10-Q (reporting date: 2015-03-31), 10-K (reporting date: 2014-12-31), 10-Q (reporting date: 2014-09-30), 10-Q (reporting date: 2014-06-30), 10-Q (reporting date: 2014-03-31).
1 Q4 2018 Calculation
Cash conversion cycle = Average inventory processing period + Average receivable collection period – Average payables payment period
= + – =
The analysis of the financial efficiency metrics over the examined periods reveals several notable trends.
- Average Inventory Processing Period
- This metric displays a general decline from 48 days in the first observed quarter to 40 days by September 2014, indicating improved inventory turnover efficiency initially. However, from late 2014 onward, the period increases again, peaking at 57 days by December 2016. The subsequent years show a modest reduction and stabilization around the low 50s, with some fluctuations toward the end of 2018. The trend suggests inventory management became less efficient between 2015 and 2016 but showed signs of improvement and stabilization afterward.
- Average Receivable Collection Period
- There is a downward trend from 84 days in March 2015 to a low of 68 days in September 2014, indicating better receivables collection earlier on. However, from late 2014 through 2017, the collection period gradually increased to a peak of 95 days by the third quarter of 2017, suggesting slower collections and potentially weakening credit controls. Toward the end of 2018, the period decreases modestly to 80 days, which shows some recovery in collection efficiency but still higher than the earliest data points.
- Average Payables Payment Period
- The payable period started at 38 days in early 2015 and generally increased over time, reaching a peak of 55 days by mid to late 2018. This lengthening indicates the company extended its payment terms to suppliers over time, possibly as a cash management strategy. The gradual upward trend suggests a deliberate approach to managing outflows over the analyzed quarters.
- Cash Conversion Cycle
- The cash conversion cycle (CCC) trends upward from 94 days in March 2015 to a high of 116 days in the latter part of 2016, indicating a deterioration in the overall efficiency of converting investments in inventory and receivables into cash. Post-2016, the CCC decreases steadily to around 78-81 days by late 2018, reflecting improved working capital management in the more recent periods. The reduction in CCC suggests better synchronization among inventory turnover, receivables, and payables after the peak inefficiency phase.
In summary, the data depict fluctuations in the company's operational efficiency with an initial improvement in inventory and receivables management followed by a phase of declining efficiency, notably in 2015-2016. The extension in payables payment period was consistent and may have mitigated cash flow pressures contributing to the elevated cash conversion cycle during that time. Recent trends indicate a recovery with improved management of working capital, leading to a more favorable cash conversion cycle approaching 2018.