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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- Statement of Comprehensive Income
- Balance Sheet: Liabilities and Stockholders’ Equity
- Cash Flow Statement
- DuPont Analysis: Disaggregation of ROE, ROA, and Net Profit Margin
- Analysis of Reportable Segments
- Enterprise Value to FCFF (EV/FCFF)
- Return on Equity (ROE) since 2005
- Current Ratio since 2005
- Price to Operating Profit (P/OP) since 2005
- Analysis of Debt
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Short-term Activity Ratios (Summary)
Time Warner Inc., short-term (operating) activity ratios (quarterly data)
Based on: 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), 10-K (reporting date: 2013-12-31), 10-Q (reporting date: 2013-09-30), 10-Q (reporting date: 2013-06-30), 10-Q (reporting date: 2013-03-31).
- Inventory Turnover
- The inventory turnover ratio shows a fluctuating trend across the periods, reaching a peak of 10.52 in June 2015 and generally declining afterward. Beginning from March 2014, the ratio improved steadily from 8 to about 10 but then experienced a downward trend from late 2015 through early 2018, falling to around 7.35 by the end of September 2017. A slight recovery is seen in the following quarters, closing at 8.71 in December 2017 and declining again to 7.35 by March 2018.
- Receivables Turnover
- This ratio, indicating the efficiency in collecting receivables, displays a modest decreasing trend over the analysis period. Starting at 3.79 in March 2014, there is some volatility but the trend gradually slips to 3.07 by March 2018. This downward trend suggests a slightly slower collection process in more recent periods compared to earlier periods.
- Working Capital Turnover
- Working capital turnover shows significant volatility throughout the periods analyzed. Initially, there is a decline from 6.68 in March 2014 down to 4.16 in September 2014, then a recovery, peaking at 7.75 in March 2017. A notable increase occurs in March 2018, reaching 27.38, followed by a decrease to 14.38 in June 2018. This sharp spike and subsequent decline indicate an abnormal or exceptional event impacting working capital efficiency in the final quarters analyzed.
- Average Inventory Processing Period
- The average inventory processing period shows fluctuations largely remaining between 35 and 50 days. After an initial decrease from 46 days in March 2014 to 35 days in June 2015, the period generally increased from 36 days in September 2015 to around 50 days in March 2018. This indicates that on average inventories are held slightly longer in recent periods compared to earlier periods.
- Average Receivable Collection Period
- The average receivable collection period demonstrates a growth trend, starting from 96 days in March 2014 and increasing consistently to 119 days by March 2018. This trend reflects a lengthening of the time taken to collect receivables, which may imply challenges in cash collection or changes in credit policies.
- Operating Cycle
- The operating cycle, which combines inventory processing and receivables collection periods, shows a clear upward trend. It fluctuated between 126 and 160 days but increased overall from 142 days in March 2014 to 161 days in March 2018. This indicates a lengthening in the total time between inventory purchase and cash collection, suggesting reduced operational efficiency in the working capital cycle. The gradual extension of the operating cycle aligns with the increasing trends in both inventory processing and receivable collection periods.
Turnover Ratios
Average No. Days
Inventory Turnover
Time Warner Inc., inventory turnover calculation (quarterly data)
| 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 | Dec 31, 2013 | Sep 30, 2013 | Jun 30, 2013 | Mar 31, 2013 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||||
| Costs of revenues | ||||||||||||||||||||||||||||
| Inventories | ||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||
| Inventory turnover1 | ||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||
| Inventory Turnover, Competitors2 | ||||||||||||||||||||||||||||
| Walt Disney Co. | ||||||||||||||||||||||||||||
Based on: 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), 10-K (reporting date: 2013-12-31), 10-Q (reporting date: 2013-09-30), 10-Q (reporting date: 2013-06-30), 10-Q (reporting date: 2013-03-31).
1 Q1 2018 Calculation
Inventory turnover
= (Costs of revenuesQ1 2018
+ Costs of revenuesQ4 2017
+ Costs of revenuesQ3 2017
+ Costs of revenuesQ2 2017)
÷ Inventories
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The analysis of the quarterly data reveals distinct trends in costs of revenues, inventories, and inventory turnover ratios over the examined period.
- Costs of Revenues
- The cost of revenues figures fluctuate throughout the years, showing a pattern of periodic increases and decreases. Initial values in early 2013 start near 3,750 million USD rising to a peak of 4,776 million USD by the end of 2013. In 2014 and 2015, costs remain relatively stable with some quarters exhibiting slight increases or decreases around the 3,500 to 4,400 million USD range. A notable increase occurs in late 2017, reaching the highest recorded value of approximately 5,181 million USD before slightly decreasing in early 2018. This volatility suggests varying operational or market conditions impacting production or service delivery costs.
- Inventories
- Inventory levels show a generally positive trend with some fluctuations. Starting at 1,987 million USD in March 2013, inventories experienced some declines and rises but overall increased to a peak above 2,400 million USD by late 2017. This growth could indicate accumulation of stock, possibly aligning with expanded business activities or preparation for increased sales. However, periodic declines hint at efforts to reduce holding costs or respond to demand fluctuations.
- Inventory Turnover Ratio
- The inventory turnover ratio, available from mid-2013 onwards, demonstrates variability over the quarters. Early values in 2013 are around 8, increasing to nearly 10 in mid-2015, indicating enhanced efficiency in inventory management or faster inventory movement during that time. Subsequently, the ratio declines gradually from about 10 to below 8 by late 2017, suggesting a slowdown in inventory turnover which may reflect changes in sales velocity or stock control dynamics.
Overall, the data suggest a dynamic operational environment characterized by fluctuating costs and inventory levels alongside a variable inventory turnover rate. Such patterns merit further investigation to understand underlying causal factors and to identify opportunities for improved cost control and inventory management efficiency.
Receivables Turnover
Time Warner Inc., receivables turnover calculation (quarterly data)
| 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 | Dec 31, 2013 | Sep 30, 2013 | Jun 30, 2013 | Mar 31, 2013 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||||
| Revenues | ||||||||||||||||||||||||||||
| Receivables, less allowances | ||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||
| Receivables turnover1 | ||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||
| Receivables Turnover, Competitors2 | ||||||||||||||||||||||||||||
| Alphabet Inc. | ||||||||||||||||||||||||||||
| Comcast Corp. | ||||||||||||||||||||||||||||
| Meta Platforms Inc. | ||||||||||||||||||||||||||||
| Take-Two Interactive Software Inc. | ||||||||||||||||||||||||||||
| Walt Disney Co. | ||||||||||||||||||||||||||||
Based on: 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), 10-K (reporting date: 2013-12-31), 10-Q (reporting date: 2013-09-30), 10-Q (reporting date: 2013-06-30), 10-Q (reporting date: 2013-03-31).
1 Q1 2018 Calculation
Receivables turnover
= (RevenuesQ1 2018
+ RevenuesQ4 2017
+ RevenuesQ3 2017
+ RevenuesQ2 2017)
÷ Receivables, less allowances
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The analysis of the quarterly financial data reveals several notable trends and patterns over the examined periods.
- Revenues
- Revenues exhibit considerable variability across the quarters without a consistently stable upward or downward trend. During the period from March 31, 2013, to December 31, 2014, revenues fluctuate, with a low around 6,243 million USD in September 2014 and a high near 8,565 million USD in December 2013. The data from 2015 to early 2018 reflects a gradual overall increase in revenue, reaching a peak of approximately 8,611 million USD in December 2017 before declining slightly to 7,996 million USD by March 31, 2018. This suggests a generally improving revenue base in the latter years following some inconsistency in earlier periods.
- Receivables, less Allowances
- Accounts receivable, net of allowances, demonstrate a pattern of growth over the analyzed time frame. Starting from 7,095 million USD at the end of the first quarter of 2013, receivables mostly increase with some minor fluctuations, reaching a peak of 10,279 million USD by March 31, 2018. The rising trend in receivables may indicate increased sales on credit or possibly slower collections, which warrants further monitoring to assess cash flow impact. The steady increase highlights growing outstanding customer balances relative to revenues.
- Receivables Turnover Ratio
- The receivables turnover ratio, shown only from the third quarter of 2013 onward, generally declines over the period. The initial value of 3.79 decreases to around 3.07 by the first quarter of 2018. This declining receivables turnover ratio implies that the company is collecting its receivables more slowly over time. The fall in this ratio, combined with the rise in receivables balances, may suggest an elongation in the cash conversion cycle and potential challenges in credit management or collection efficiency.
Overall, the data indicates that while the company achieved revenue growth toward the latter part of the period, the increase in receivables and the declining turnover ratio highlight potential concerns regarding credit policy effectiveness and cash flow timing. These trends suggest the need for cautious management of working capital and attention to customer payment behaviors to optimize liquidity and operational efficiency.
Working Capital Turnover
Time Warner Inc., working capital turnover calculation (quarterly data)
| 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 | Dec 31, 2013 | Sep 30, 2013 | Jun 30, 2013 | Mar 31, 2013 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | ||||||||||||||||||||||||||||
| Current assets | ||||||||||||||||||||||||||||
| Less: Current liabilities | ||||||||||||||||||||||||||||
| Working capital | ||||||||||||||||||||||||||||
| Revenues | ||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||
| Working capital turnover1 | ||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||
| Working Capital Turnover, Competitors2 | ||||||||||||||||||||||||||||
| Alphabet Inc. | ||||||||||||||||||||||||||||
| Comcast Corp. | ||||||||||||||||||||||||||||
| Meta Platforms Inc. | ||||||||||||||||||||||||||||
| Netflix Inc. | ||||||||||||||||||||||||||||
| Take-Two Interactive Software Inc. | ||||||||||||||||||||||||||||
| Walt Disney Co. | ||||||||||||||||||||||||||||
Based on: 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), 10-K (reporting date: 2013-12-31), 10-Q (reporting date: 2013-09-30), 10-Q (reporting date: 2013-06-30), 10-Q (reporting date: 2013-03-31).
1 Q1 2018 Calculation
Working capital turnover
= (RevenuesQ1 2018
+ RevenuesQ4 2017
+ RevenuesQ3 2017
+ RevenuesQ2 2017)
÷ Working capital
= ( + + + )
÷ =
2 Click competitor name to see calculations.
The financial data reveals varying trends over the analyzed periods. Working capital demonstrates fluctuations, with values initially in the range of approximately 3,900 to 7,000 million USD. A notable decrease occurs towards the end of the timeframe, reaching as low as 1,142 million USD. This suggests some volatility or changes in operational funding requirements.
Revenues show consistent fluctuations throughout the periods reviewed. Values oscillate mostly between 6,200 and 8,600 million USD, with some quarters experiencing dips and others rebounds. Despite these fluctuations, there is no clear, continuous upward or downward trend.
The working capital turnover ratio exhibits significant variability. Initially, the ratio ranges between 4.16 and 7.75, indicating relatively stable efficiency in the use of working capital to generate revenues. However, towards the end of the data, there is a marked increase, with ratios jumping to 27.38 and then declining to 14.38, possibly reflecting changes in working capital management or revenue generation patterns.
- Working Capital
- Shows inconsistency with some peaks around mid-period (e.g., 6,976 million USD) and sharp declines notably by the final quarter (1,142 million USD), indicating potential liquidity adjustments or operational shifts.
- Revenues
- Demonstrates cyclical behavior with revenue values going up and down within the 6,200 to 8,600 million USD range. This variability may point to seasonal or market-driven influences on sales.
- Working Capital Turnover
- Generally hovers around 4 to 8 for most of the period, signifying moderate efficiency. Anomalies observed in the last two quarters, with ratios surging substantially, suggest sudden operational changes affecting the turnover rate.
In summary, the dataset indicates a pattern of financial variability with working capital levels and turnover efficiency fluctuating in tandem with revenue changes. The substantial shifts in working capital turnover towards the end of the period warrant further investigation to determine underlying causes and implications for operational performance.
Average Inventory Processing Period
Time Warner Inc., average inventory processing period calculation (quarterly data)
| 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 | Dec 31, 2013 | Sep 30, 2013 | Jun 30, 2013 | Mar 31, 2013 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||
| Inventory turnover | ||||||||||||||||||||||||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||
| Average inventory processing period1 | ||||||||||||||||||||||||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||
| Average Inventory Processing Period, Competitors2 | ||||||||||||||||||||||||||||
| Walt Disney Co. | ||||||||||||||||||||||||||||
Based on: 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), 10-K (reporting date: 2013-12-31), 10-Q (reporting date: 2013-09-30), 10-Q (reporting date: 2013-06-30), 10-Q (reporting date: 2013-03-31).
1 Q1 2018 Calculation
Average inventory processing period = 365 ÷ Inventory turnover
= 365 ÷ =
2 Click competitor name to see calculations.
The inventory turnover ratio demonstrates a fluctuating trend over the observed period from early 2013 through early 2018. Initially, there is no data available for the first four quarters ending in December 2013. Starting from March 2014, the ratio begins at 8 and shows an increasing trend reaching a peak at 10.52 in June 2015. This increase indicates a more efficient inventory management or faster sales turnover during this period.
Following this peak, the inventory turnover ratio decreases to 8.22 by December 2015, suggesting a slowdown in inventory turnover. In subsequent quarters, the ratio shows variability but mostly declines gradually, with figures generally ranging between 7.35 and 8.71 from 2016 onwards. This indicates a general trend of moderation in inventory turnover efficiency, with occasional slight recoveries.
The average inventory processing period, expressed in days, displays an inverse trend relative to the turnover ratio, as expected. Starting at 46 days in March 2014, it improves by decreasing to 35 days around June 2015, reflecting faster inventory turnover and better management within that timeframe.
After June 2015, the processing period generally increases, reaching a maximum of 50 days in March 2018. This lengthening of the processing period corresponds with the decreasing inventory turnover ratio and suggests slower inventory movement and potential accumulation or slower sales in later years.
- Inventory Turnover Ratio
- Shows an initial increase from 8 in early 2014 to a peak of 10.52 by mid-2015, indicating improved inventory turnover efficiency.
- Post-2015, it fluctuates but trends downward, stabilizing between approximately 7.3 and 8.7, reflecting less dynamic inventory movement.
- Average Inventory Processing Period
- Decreases from 46 days in early 2014 to a low of 35 days mid-2015, consistent with higher turnover efficiency.
- Then gradually increases up to 50 days by early 2018, indicating slower inventory turnover and longer holding periods.
In summary, the data suggests that the company experienced improved inventory management and turnover up until mid-2015. After this period, there is a noticeable slowdown with inventory being held for longer periods, which may warrant further investigation into sales performance, supply chain factors, or changes in inventory strategy during the latter years.
Average Receivable Collection Period
Time Warner Inc., average receivable collection period calculation (quarterly data)
| 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 | Dec 31, 2013 | Sep 30, 2013 | Jun 30, 2013 | Mar 31, 2013 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||
| Receivables turnover | ||||||||||||||||||||||||||||
| Short-term Activity Ratio (no. days) | ||||||||||||||||||||||||||||
| Average receivable collection period1 | ||||||||||||||||||||||||||||
| Benchmarks (no. days) | ||||||||||||||||||||||||||||
| Average Receivable Collection Period, Competitors2 | ||||||||||||||||||||||||||||
| Alphabet Inc. | ||||||||||||||||||||||||||||
| Comcast Corp. | ||||||||||||||||||||||||||||
| Meta Platforms Inc. | ||||||||||||||||||||||||||||
| Take-Two Interactive Software Inc. | ||||||||||||||||||||||||||||
| Walt Disney Co. | ||||||||||||||||||||||||||||
Based on: 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), 10-K (reporting date: 2013-12-31), 10-Q (reporting date: 2013-09-30), 10-Q (reporting date: 2013-06-30), 10-Q (reporting date: 2013-03-31).
1 Q1 2018 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ =
2 Click competitor name to see calculations.
The receivables turnover ratio demonstrates a fluctuating trend over the observed periods. Starting from a value of 3.79, it shows a gradual increase, peaking at 4.14 in the third quarter of 2013. Following this peak, the ratio experiences a declining trajectory with minor variations, decreasing to 3.07 by the first quarter of 2018. This indicates a slower rate of receivables being collected over time.
Correspondingly, the average receivable collection period, measured in number of days, exhibits an inverse movement relative to the turnover ratio. Initially at 96 days, it reduces slightly to a low of 88 days by the third quarter of 2013, demonstrating improved efficiency in collection during that timeframe. Subsequently, this period lengthens steadily, reaching 119 days in the first quarter of 2018, suggesting that the time taken to collect receivables has increased.
- Receivables Turnover Ratio
- Increased initially, reaching maximum efficiency in third quarter 2013.
- Followed by a consistent decline through to early 2018, indicating a reduction in turnover speed.
- Average Receivable Collection Period
- Decreased to the lowest point in the third quarter 2013, reflecting quicker collections.
- Increased steadily after that, suggesting a longer collection cycle through early 2018.
In summary, the data reflect a shift towards longer receivable periods and reduced turnover efficiency over the analyzed years. This trend may imply challenges in credit management or customer payment behavior, potentially impacting the company’s cash flow and working capital management.
Operating Cycle
Time Warner Inc., operating cycle calculation (quarterly data)
No. days
| 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 | Dec 31, 2013 | Sep 30, 2013 | Jun 30, 2013 | Mar 31, 2013 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | ||||||||||||||||||||||||||||
| Average inventory processing period | ||||||||||||||||||||||||||||
| Average receivable collection period | ||||||||||||||||||||||||||||
| Short-term Activity Ratio | ||||||||||||||||||||||||||||
| Operating cycle1 | ||||||||||||||||||||||||||||
| Benchmarks | ||||||||||||||||||||||||||||
| Operating Cycle, Competitors2 | ||||||||||||||||||||||||||||
| Walt Disney Co. | ||||||||||||||||||||||||||||
Based on: 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), 10-K (reporting date: 2013-12-31), 10-Q (reporting date: 2013-09-30), 10-Q (reporting date: 2013-06-30), 10-Q (reporting date: 2013-03-31).
1 Q1 2018 Calculation
Operating cycle = Average inventory processing period + Average receivable collection period
= + =
2 Click competitor name to see calculations.
The data reveals the evolution of three key operational efficiency metrics over multiple quarterly periods from March 2013 to March 2018. These metrics are the average inventory processing period, average receivable collection period, and the operating cycle, each measured in number of days.
- Average Inventory Processing Period
- This metric demonstrates variability over the analyzed time horizon. Beginning in the first observed quarter (March 2014), the inventory processing period was 46 days, showing a decreasing trend to a low of 35 days in the second quarter of 2015. Subsequently, the period fluctuated, increasing to 44 days at the end of 2015 before declining again to 36 days in mid-2016. A gradual increase followed, reaching a peak of 50 days in the first quarter of 2018, indicating a lengthening in the amount of time inventory remains before processing in the latest period.
- Average Receivable Collection Period
- The receivable collection period shows a notable upward trend throughout the quarters. Initially, the period was 96 days in March 2014, then it declined to a low around 88 days in the third quarter of 2013. However, from late 2013 onwards, it mostly increased, reaching 103 days by the end of 2014. The period experienced further growth over the subsequent years, peaking at 119 days in the first quarter of 2018. This progression suggests an elongation in the time taken to collect receivables over the period analyzed.
- Operating Cycle
- The operating cycle, which integrates both inventory processing and receivables collection periods, reflects a generally increasing trajectory. Starting at 142 days in March 2014, it experienced some minor fluctuations but overall grew from approximately 130 days to reach a maximum of 161 days by the first quarter of 2018. This trend signals an overall lengthening in the total time taken to convert inventory into cash, which potentially could have implications for working capital management.
In summary, the data indicates that while the inventory processing period exhibited fluctuations with periods of both increase and decrease, the receivable collection period consistently increased over time. Consequently, the operating cycle lengthened steadily. This pattern suggests a growing duration in the conversion of assets into cash, which might be reflective of changes in operational efficiency, credit terms, or market conditions impacting receivables management and inventory turnover.