Automatic Data Processing (ADP) Other Operating Expenses (2009 - 2026)
Automatic Data Processing (ADP) reported Other Operating Expenses of $2.84 billion for fiscal Q4 2026 (quarter ended Jun 30, 2026), up 5.4% from $2.7 billion a year earlier but down 3.7% from the prior quarter.
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Analysis
Automatic Data Processing (ADP) Other Operating Expenses (2009 - 2026) Analysis & Trends
For FY2026 (ended Jun 30, 2026), Automatic Data Processing posted Other Operating Expenses of $11.27 billion, up 6.2% from FY2025.
- Other Operating Expenses has increased for 13 consecutive fiscal years, with a five-year compound annual growth rate of 6.5% (FY2021 to FY2026).
- By fiscal year, Other Operating Expenses came in at $10.61 billion in FY2025 (+6.1%), $10.01 billion in FY2024 (+5.3%), $9.5 billion in FY2023 (+5.0%) and $9.05 billion in FY2022 (+10.1%).
- Five-year quarterly Other Operating Expenses spans a low of $2.12 billion in fiscal Q1 2022 and a high of $2.95 billion in fiscal Q3 2026.
- Year over year, Other Operating Expenses has now increased in each of the last 23 quarters, with growth averaging 6.1% over the last eight quarters.
- The year-over-year growth in Other Operating Expenses has ranged between 3.9% (fiscal Q4 2023) and 10.9% (fiscal Q2 2022) over the last five years.
- Per Business Quant data, the three fiscal quarters before Q4 2026 came in at $2.95 billion (Q3 2026), $2.77 billion (Q2 2026) and $2.71 billion (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palantir Technologies | 413.65 Bn | 378.59 Bn | 1.93 Bn |
| 2 | Oracle | 374.28 Bn | 246.84 Bn | - |
| 3 | Sap Se | 294.90 Bn | 222.88 Bn | 8.64 Bn |
| 4 | Salesforce | 186.99 Bn | 142.87 Bn | 8.70 Bn |
| 5 | Automatic Data Processing | 120.08 Bn | 106.87 Bn | 2.53 Bn |
| 6 | ServiceNow | 113.02 Bn | 92.28 Bn | 2.90 Bn |
| 7 | Intuit | 95.72 Bn | 75.07 Bn | 3.44 Bn |
| 8 | Relx | 74.73 Bn | 73.84 Bn | - |
| 9 | Strategy | 57.35 Bn | 44.49 Bn | 89.63 Mn |
| 10 | Thomson Reuters | 52.16 Bn | 48.13 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 2.86 Bn |
| Jun 30, 2026 | 2.82 Bn |
| Mar 31, 2026 | 2.90 Bn |
| Dec 31, 2025 | 2.76 Bn |
| Sep 30, 2025 | 2.72 Bn |
| Jun 30, 2025 | 2.66 Bn |
| Mar 31, 2025 | 2.73 Bn |
| Dec 31, 2024 | 2.63 Bn |
| Sep 30, 2024 | 2.54 Bn |
| Jun 30, 2024 | 2.49 Bn |
| Mar 31, 2024 | 2.59 Bn |
| Dec 31, 2023 | 2.44 Bn |
| Sep 30, 2023 | 2.37 Bn |
| Jun 30, 2023 | 2.37 Bn |
| Mar 31, 2023 | 2.45 Bn |
| Dec 31, 2022 | 2.30 Bn |
| Sep 30, 2022 | 2.24 Bn |
| Jun 30, 2022 | 2.41 Bn |
| Mar 31, 2022 | 2.53 Bn |
| Dec 31, 2021 | 2.36 Bn |
API Access
Automatic Data Processing Other Operating 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-operating-expenses&ticker=ADP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-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-operating-expenses&ticker=ADP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();