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)
Fiserv Inc., short-term (operating) activity ratios (quarterly data)
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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).
The analysis of key financial ratios over multiple quarters reveals distinct patterns in the company's operational efficiency and working capital management.
- Receivables Turnover
- The receivables turnover ratio exhibits fluctuations throughout the observed periods. Initially, there is a gradual decline from 6.54 to 5.55 within the first year, suggesting a slower collection pace of receivables. Midway through 2019, a notable dip occurs, reaching a low of 2.9, indicating a significant slowdown in converting receivables into cash. Subsequently, the ratio recovers steadily, peaking around 6.49 in the third quarter of 2020 before stabilizing near 5.7 in the most recent quarter. This trend implies a temporary weakening in receivables management followed by an improvement and relative stabilization.
- Working Capital Turnover
- This ratio demonstrates high volatility across periods. It starts at a high level of 67.55, then sharply decreases to 0.73 in the mid of 2019, followed by considerable irregular movements including a spike to 321.56 early in the data sequence. The fluctuations suggest episodes of significant changes in working capital relative to sales, potentially reflecting varying investment in current assets or changes in sales volume and operational efficiency. Despite the volatility, there is a general tendency towards moderate values between 18 and 32 in the latest quarters, signaling a more normalized management of working capital.
- Average Receivable Collection Period
- The number of days for average receivable collection starts at 56 and trends upward to a peak of 126 days in the third quarter of 2019, signaling a lengthening in the time to collect receivables. After this peak, there is a consistent decrease and stabilization around the low to mid-60s days in the most recent periods. This indicates an initial challenge in receivables collection timing, later rectified to a steady, more efficient cycle.
Overall, the company experienced some operational challenges in receivables management between 2018 and 2019 with slower turnover and longer collection periods, likely impacting liquidity. Improvements from late 2019 onward suggest enhanced efficiency in credit and collections processes. The working capital turnover's extreme variability indicates fluctuating operational and sales conditions but appears to settle to more sustainable levels in recent quarters. Monitoring these trends will be essential to sustain efficient cash conversion and working capital utilization going forward.
Turnover Ratios
Average No. Days
Receivables Turnover
Fiserv Inc., receivables turnover calculation (quarterly data)
| Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | |||||||||||||||||||||||
| Revenue | 4,138) | 4,257) | 4,163) | 4,051) | 3,755) | 3,832) | 3,786) | 3,465) | 3,769) | 4,045) | 3,128) | 1,512) | 1,502) | 1,551) | 1,412) | 1,420) | 1,440) | ||||||
| Trade accounts receivable, less allowance for doubtful accounts | 2,911) | 2,860) | 2,793) | 2,663) | 2,617) | 2,482) | 2,323) | 2,512) | 2,582) | 2,782) | 2,653) | 989) | 1,044) | 1,049) | 949) | 932) | 878) | ||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Receivables turnover1 | 5.71 | 5.67 | 5.66 | 5.79 | 5.67 | 5.98 | 6.49 | 5.74 | 4.82 | 3.66 | 2.90 | 6.04 | 5.64 | 5.55 | 6.10 | 6.20 | 6.54 | ||||||
| Benchmarks | |||||||||||||||||||||||
| Receivables Turnover, Competitors2 | |||||||||||||||||||||||
| Adobe Inc. | 9.58 | 8.41 | 9.77 | 9.74 | 9.00 | 9.20 | 9.44 | 8.82 | 8.40 | — | — | — | — | — | — | — | — | ||||||
| AppLovin Corp. | 4.11 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Cadence Design Systems Inc. | 8.72 | 8.85 | 9.09 | 7.41 | 7.21 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| CrowdStrike Holdings Inc. | 4.73 | 3.66 | 4.41 | 4.38 | 3.91 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Datadog Inc. | 4.33 | 3.83 | 3.92 | 4.06 | 4.35 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| International Business Machines Corp. | 9.79 | 8.49 | 9.23 | 9.57 | 10.72 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Intuit Inc. | 25.10 | 24.64 | 16.04 | 16.60 | 79.16 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Microsoft Corp. | 6.44 | 4.42 | 6.08 | 5.61 | 6.44 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Oracle Corp. | 9.11 | 7.48 | 8.56 | 8.91 | 8.57 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Palantir Technologies Inc. | 6.42 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Palo Alto Networks Inc. | 5.61 | 3.43 | 5.20 | 5.65 | 5.30 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Salesforce Inc. | 7.04 | 2.73 | 6.12 | 5.63 | 5.93 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| ServiceNow Inc. | 7.59 | 4.24 | 7.13 | 6.62 | 7.49 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Synopsys Inc. | 4.34 | 7.40 | 7.06 | 6.51 | 4.84 | 4.72 | 5.50 | 5.36 | 4.22 | — | — | — | — | — | — | — | — | ||||||
| Workday Inc. | 6.91 | 4.18 | 5.60 | 5.75 | 6.54 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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).
1 Q1 2022 Calculation
Receivables turnover
= (RevenueQ1 2022
+ RevenueQ4 2021
+ RevenueQ3 2021
+ RevenueQ2 2021)
÷ Trade accounts receivable, less allowance for doubtful accounts
= (4,138 + 4,257 + 4,163 + 4,051)
÷ 2,911 = 5.71
2 Click competitor name to see calculations.
The financial data reveals several noteworthy trends across the periods analyzed. Revenue demonstrates a general upward trajectory over the long term, with some marked fluctuations. Beginning at approximately $1.44 billion in the first quarter of 2018, revenue remains relatively stable through early 2019 before experiencing a significant spike, particularly in the third and fourth quarters of 2019, reaching over $4 billion. This surge is followed by some volatility through 2020 and 2021, culminating in revenues exceeding $4.2 billion by the first quarter of 2022. This pattern suggests possible structural changes or significant events impacting sales volumes or contract values during 2019, with a stabilization trend in more recent quarters.
Trade accounts receivable, net of doubtful accounts, also display an increasing trend consistent with revenue movements but with some distinct characteristics. Initial values near $878 million rise slightly through 2018 and early 2019 before a pronounced increase in mid to late 2019, peaking close to $2.8 billion by the end of 2019. Post-peak, the receivables amounts show relative stability with minor incremental growth, reaching $2.9 billion in early 2022. The sharp increase in receivables during late 2019 mirrors the revenue spike, indicating higher credit sales or extended receivable periods.
The receivables turnover ratio, an efficiency indicator representing how effectively receivables are collected, exhibits an inverse relationship to the changes in receivables and revenue during this period. Initially fluctuating between 5.55 and 6.54 in 2018 and early 2019, the ratio drops sharply to as low as 2.9 and 3.66 in mid to late 2019, coinciding with the spike in accounts receivable. This decline implies slower collection efforts or longer payment terms during this timeframe. Subsequently, the turnover ratio recovers progressively through 2020, reaching values near 6.49, then slightly declines and stabilizes in the mid-5 range through early 2022. This recovery and stabilization suggest an improvement in collection practices or contract terms following the abnormal 2019 period.
In summary, the data reveals a significant event or transition around 2019 that led to a considerable increase in both revenue and receivables, accompanied by a temporary decrease in receivables turnover, signaling slower cash collections. The subsequent period shows efforts to normalize collection efficiency while revenues stabilize at a higher level than pre-2019. Monitoring these metrics moving forward will be important to assess ongoing operational effectiveness and liquidity management.
Working Capital Turnover
Fiserv Inc., working capital turnover calculation (quarterly data)
| Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data (US$ in millions) | |||||||||||||||||||||||
| Current assets | 18,443) | 18,870) | 18,425) | 17,727) | 16,440) | 16,219) | 14,025) | 17,482) | 12,933) | 17,046) | 17,991) | 10,209) | 2,275) | 2,224) | 2,338) | 1,804) | 1,768) | ||||||
| Less: Current liabilities | 17,730) | 18,295) | 17,562) | 17,251) | 15,905) | 15,637) | 13,263) | 16,760) | 12,119) | 15,727) | 16,661) | 2,054) | 2,120) | 2,010) | 2,320) | 1,655) | 1,683) | ||||||
| Working capital | 713) | 575) | 863) | 476) | 535) | 582) | 762) | 722) | 814) | 1,319) | 1,330) | 8,155) | 155) | 214) | 18) | 149) | 85) | ||||||
| Revenue | 4,138) | 4,257) | 4,163) | 4,051) | 3,755) | 3,832) | 3,786) | 3,465) | 3,769) | 4,045) | 3,128) | 1,512) | 1,502) | 1,551) | 1,412) | 1,420) | 1,440) | ||||||
| Short-term Activity Ratio | |||||||||||||||||||||||
| Working capital turnover1 | 23.29 | 28.22 | 18.31 | 32.40 | 27.73 | 25.52 | 19.77 | 19.95 | 15.30 | 7.72 | 5.78 | 0.73 | 37.97 | 27.21 | 321.56 | 38.77 | 67.55 | ||||||
| Benchmarks | |||||||||||||||||||||||
| Working Capital Turnover, Competitors2 | |||||||||||||||||||||||
| Accenture PLC | 15.85 | 12.77 | 7.71 | 8.35 | 7.70 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Adobe Inc. | 57.86 | 9.09 | 6.22 | 7.44 | 8.67 | 4.89 | 5.51 | 8.11 | 9.50 | — | — | — | — | — | — | — | — | ||||||
| AppLovin Corp. | 1.86 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Cadence Design Systems Inc. | 4.07 | 4.01 | 4.68 | 5.45 | 5.03 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| CrowdStrike Holdings Inc. | 0.95 | 0.61 | 1.19 | 0.92 | 0.81 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Datadog Inc. | 0.85 | 0.77 | 0.68 | 0.61 | 0.47 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| International Business Machines Corp. | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Intuit Inc. | 4.39 | 3.85 | 3.40 | 5.45 | 1.74 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Microsoft Corp. | 1.88 | 1.76 | 1.71 | 1.44 | 1.37 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Oracle Corp. | 1.70 | 1.29 | 1.69 | 1.58 | 1.26 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Palantir Technologies Inc. | 0.73 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Palo Alto Networks Inc. | — | — | 3.52 | — | 2.15 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Salesforce Inc. | 4.36 | 5.11 | 7.48 | 10.29 | 9.75 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| ServiceNow Inc. | 10.61 | 21.76 | 11.15 | 16.31 | 5.62 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Synopsys Inc. | 9.47 | 10.65 | 9.50 | 9.18 | 16.88 | 9.00 | 27.06 | — | — | — | — | — | — | — | — | — | — | ||||||
| Workday Inc. | — | 8.31 | 12.50 | 3.44 | 5.62 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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).
1 Q1 2022 Calculation
Working capital turnover
= (RevenueQ1 2022
+ RevenueQ4 2021
+ RevenueQ3 2021
+ RevenueQ2 2021)
÷ Working capital
= (4,138 + 4,257 + 4,163 + 4,051)
÷ 713 = 23.29
2 Click competitor name to see calculations.
The financial data reveals several noteworthy trends in working capital, revenue, and working capital turnover over the examined periods.
- Working Capital
- The working capital figures exhibit substantial volatility, with values fluctuating from modest levels in early periods to a pronounced spike in June 2019. Specifically, working capital surged dramatically to 8,155 million US dollars in June 2019, an outlier compared to the preceding and following quarters where the figures generally ranged between 18 million and 1,330 million US dollars. After this peak, working capital levels declined sharply, stabilizing to a range roughly between 500 million and 860 million US dollars in subsequent periods. This volatility suggests an unusual transaction or event impacting liquidity during mid-2019, followed by a return to more normalized working capital management.
- Revenue
- The revenue trajectory illustrates an overall upward trend with some fluctuations. Initial quarters from 2018 show relatively stable revenue around the 1,400 to 1,550 million US dollars range. A noticeable increase occurs in the second half of 2019, with revenue jumping above 3,000 million and peaking at 4,045 million US dollars by the end of that year. This elevated revenue level remains broadly sustained through 2020 and into 2021, fluctuating between approximately 3,400 and 4,200 million US dollars. By early 2022, revenue shows a slight decrease below the previous highs, landing at about 4,138 million US dollars. The data may suggest periods of growth potentially driven by acquisitions, expansion, or seasonality.
- Working Capital Turnover
- Working capital turnover, calculated as the ratio of revenue to working capital, displays significant variability aligned with the fluctuations of working capital and revenue. Early readings in 2018 show extremely high turnover ratios, notably 321.56 in September 2018, indicating either very low working capital or temporarily high revenue. Post mid-2019, as working capital normalized to higher levels, the turnover ratio declined to single digits but eventually rebounded, fluctuating between 15 and 32 in subsequent quarters. The variability in turnover ratios suggests changing efficiency in using working capital to generate revenue, with some quarters reflecting highly efficient capital use and others indicating more conservative or less efficient utilization.
In summary, the data reflects a period marked by significant working capital fluctuations, a general upward movement in revenue with intermittent peaks, and a volatile working capital turnover ratio indicative of shifting operational dynamics or strategic financial management. These observations may warrant further investigation into specific events affecting liquidity and revenue generation during the highlighted periods.
Average Receivable Collection Period
Fiserv Inc., average receivable collection period calculation (quarterly data)
| Mar 31, 2022 | Dec 31, 2021 | Sep 30, 2021 | Jun 30, 2021 | Mar 31, 2021 | Dec 31, 2020 | Sep 30, 2020 | Jun 30, 2020 | Mar 31, 2020 | Dec 31, 2019 | Sep 30, 2019 | Jun 30, 2019 | Mar 31, 2019 | Dec 31, 2018 | Sep 30, 2018 | Jun 30, 2018 | Mar 31, 2018 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Selected Financial Data | |||||||||||||||||||||||
| Receivables turnover | 5.71 | 5.67 | 5.66 | 5.79 | 5.67 | 5.98 | 6.49 | 5.74 | 4.82 | 3.66 | 2.90 | 6.04 | 5.64 | 5.55 | 6.10 | 6.20 | 6.54 | ||||||
| Short-term Activity Ratio (no. days) | |||||||||||||||||||||||
| Average receivable collection period1 | 64 | 64 | 65 | 63 | 64 | 61 | 56 | 64 | 76 | 100 | 126 | 60 | 65 | 66 | 60 | 59 | 56 | ||||||
| Benchmarks (no. days) | |||||||||||||||||||||||
| Average Receivable Collection Period, Competitors2 | |||||||||||||||||||||||
| Adobe Inc. | 38 | 43 | 37 | 37 | 41 | 40 | 39 | 41 | 43 | — | — | — | — | — | — | — | — | ||||||
| AppLovin Corp. | 89 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Cadence Design Systems Inc. | 42 | 41 | 40 | 49 | 51 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| CrowdStrike Holdings Inc. | 77 | 100 | 83 | 83 | 93 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Datadog Inc. | 84 | 95 | 93 | 90 | 84 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| International Business Machines Corp. | 37 | 43 | 40 | 38 | 34 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Intuit Inc. | 15 | 15 | 23 | 22 | 5 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Microsoft Corp. | 57 | 83 | 60 | 65 | 57 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Oracle Corp. | 40 | 49 | 43 | 41 | 43 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Palantir Technologies Inc. | 57 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Palo Alto Networks Inc. | 65 | 106 | 70 | 65 | 69 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Salesforce Inc. | 52 | 134 | 60 | 65 | 62 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| ServiceNow Inc. | 48 | 86 | 51 | 55 | 49 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
| Synopsys Inc. | 84 | 49 | 52 | 56 | 75 | 77 | 66 | 68 | 86 | — | — | — | — | — | — | — | — | ||||||
| Workday Inc. | 53 | 87 | 65 | 63 | 56 | — | — | — | — | — | — | — | — | — | — | — | — | ||||||
Based on: 10-Q (reporting date: 2022-03-31), 10-K (reporting date: 2021-12-31), 10-Q (reporting date: 2021-09-30), 10-Q (reporting date: 2021-06-30), 10-Q (reporting date: 2021-03-31), 10-K (reporting date: 2020-12-31), 10-Q (reporting date: 2020-09-30), 10-Q (reporting date: 2020-06-30), 10-Q (reporting date: 2020-03-31), 10-K (reporting date: 2019-12-31), 10-Q (reporting date: 2019-09-30), 10-Q (reporting date: 2019-06-30), 10-Q (reporting date: 2019-03-31), 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).
1 Q1 2022 Calculation
Average receivable collection period = 365 ÷ Receivables turnover
= 365 ÷ 5.71 = 64
2 Click competitor name to see calculations.
The analysis of the quarterly receivables turnover and average receivable collection period reveals distinct patterns over the observed timeline.
- Receivables Turnover
- Throughout the initial quarters, the receivables turnover ratio demonstrated a general decline from 6.54 to a low point near 2.9, indicating a slowdown in the frequency of receivables collection. A notable dip occurred in the third quarter of 2019, reaching the minimum value during the period. Subsequently, the ratio exhibited recovery and stabilization, ascending back to values around 5.6 to 5.7 by the early quarters of 2022. This recovery suggests an improvement in the efficiency of converting receivables into cash after the marked downturn.
- Average Receivable Collection Period
- The average collection period inversely mirrored the receivables turnover trend, increasing from 56 days to a peak of 126 days in the third quarter of 2019. This elongation reflects slower collection of receivables, possibly indicating cash flow challenges or changes in credit terms during that interval. After peaking, the collection period decreased steadily and stabilized in the range of approximately 60 to 65 days in the later quarters, signifying improved collection efficiency.
In summary, the data depict a period of deteriorating receivables performance culminating around late 2019, followed by a phase of recovery and normalization through to early 2022. The fluctuations suggest operational or external factors adversely affecting receivables management in 2019, with subsequent corrective measures or market improvements contributing to a return to more typical collection dynamics.