Automatic Data Processing (ADP) Other Accumulated Expenses (2009 - 2016)
Automatic Data Processing (ADP) posted Other Accumulated Expenses of $238.4 million for fiscal Q4 2016 (quarter ended Jun 30, 2016), up 5.3% from $226.4 million a year earlier.
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Analysis
Automatic Data Processing (ADP) Other Accumulated Expenses (2009 - 2016) Analysis & Trends
Since fiscal Q4 2009, Automatic Data Processing has reported Other Accumulated Expenses for 26 quarters.
- Annual Other Accumulated Expenses shows a five-year compound annual growth rate of 6.5% (FY2011 to FY2016).
- In prior fiscal years, Automatic Data Processing's Other Accumulated Expenses was $226.4 million in FY2015 (-0.2%), $226.9 million in FY2014 (+9.8%), $206.7 million in FY2013 (+9.7%) and $188.4 million in FY2012 (+8.2%).
- The fiscal Q4 2016 figure stands as the highest quarterly Other Accumulated Expenses in data going back to fiscal Q4 2009.
- On a year-over-year basis, Other Accumulated Expenses increased in four of the last five quarters, with growth averaging 3.9%.
- The strongest year-over-year quarter for Other Accumulated Expenses in the past five years was fiscal Q1 2015, with growth of 11.2%; the weakest was fiscal Q4 2015, with a decline of 0.2%.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palantir Technologies | 450.50 Bn | 419.56 Bn | 1.64 Bn |
| 2 | Oracle | 401.01 Bn | 273.57 Bn | - |
| 3 | Sap Se | 257.03 Bn | 178.11 Bn | 8.40 Bn |
| 4 | Salesforce | 187.04 Bn | 142.92 Bn | 8.70 Bn |
| 5 | ServiceNow | 135.91 Bn | 114.37 Bn | 2.82 Bn |
| 6 | Automatic Data Processing | 104.14 Bn | 86.27 Bn | 2.51 Bn |
| 7 | Intuit | 72.30 Bn | 51.65 Bn | 3.44 Bn |
| 8 | Relx | 60.17 Bn | 57.14 Bn | - |
| 9 | Strategy | 55.31 Bn | 48.30 Bn | 81.55 Mn |
| 10 | Workday | 45.49 Bn | 21.61 Bn | 2.00 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2016 | 238.40 Mn |
| Jun 30, 2015 | 226.40 Mn |
| Mar 31, 2015 | 228.80 Mn |
| Dec 31, 2014 | 232.00 Mn |
| Sep 30, 2014 | 228.60 Mn |
| Jun 30, 2014 | 226.90 Mn |
| Mar 31, 2014 | 227.00 Mn |
| Dec 31, 2013 | 226.70 Mn |
| Sep 30, 2013 | 205.60 Mn |
| Jun 30, 2013 | 206.70 Mn |
| Mar 31, 2013 | 207.20 Mn |
| Dec 31, 2012 | 206.50 Mn |
| Sep 30, 2012 | 187.90 Mn |
| Jun 30, 2012 | 188.40 Mn |
| Mar 31, 2012 | 190.10 Mn |
| Dec 31, 2011 | 189.20 Mn |
| Sep 30, 2011 | 172.30 Mn |
| Jun 30, 2011 | 174.20 Mn |
| Mar 31, 2011 | 176.10 Mn |
| Dec 31, 2010 | 174.30 Mn |
API Access
Automatic Data Processing Other Accumulated Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=other-accumulated-expenses&ticker=ADP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-accumulated-expenses", "ticker": "ADP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=other-accumulated-expenses&ticker=ADP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();