Automatic Data Processing (ADP) Other Operating Expenses (2009 - 2026)
Automatic Data Processing (ADP) posted Other Operating Expenses of $2.82 billion for fiscal Q4 2026 (quarter ended Jun 30, 2026), up 5.9% from $2.66 billion a year earlier but down 2.7% from the prior quarter.
Automatic Data Processing (ADP) Other Operating Expenses (2009 - 2026) Analysis & Trends
For FY2026 (ended Jun 30, 2026), Automatic Data Processing's Other Operating Expenses came in at $11.19 billion, up 5.9% from FY2025.
- Annual Other Operating Expenses has increased for 13 consecutive fiscal years, with a five-year compound annual growth rate of 5.2% (FY2021 to FY2026).
- In prior fiscal years, Automatic Data Processing's Other Operating Expenses was $10.56 billion in FY2025 (+6.9%), $9.88 billion in FY2024 (+5.6%), $9.36 billion in FY2023 (+7.1%) and $8.75 billion in FY2022 (+0.5%).
- Quarterly Other Operating Expenses has run from a low of $2.24 billion in fiscal Q1 2023 to a high of $2.9 billion in fiscal Q3 2026 over five years.
- On a year-over-year basis, Other Operating Expenses has increased in each of the last 12 quarters, with growth averaging 6.4% over the last eight quarters.
- The strongest year-over-year quarter for Other Operating Expenses in the past five years was fiscal Q2 2022, with growth of 10.5%; the weakest was fiscal Q3 2023, with a decline of 3.0%.
- According to Business Quant data, Other Operating Expenses for the three prior fiscal quarters was $2.9 billion (Q3 2026), $2.76 billion (Q2 2026) and $2.72 billion (Q1 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palantir Technologies | 480.73 Bn | 449.68 Bn | 1.64 Bn |
| 2 | Oracle | 399.91 Bn | 272.04 Bn | - |
| 3 | Sap Se | 262.30 Bn | 190.08 Bn | 8.40 Bn |
| 4 | Salesforce | 202.26 Bn | 158.13 Bn | 8.70 Bn |
| 5 | ServiceNow | 153.84 Bn | 132.30 Bn | 2.82 Bn |
| 6 | Automatic Data Processing | 114.84 Bn | 96.97 Bn | 2.51 Bn |
| 7 | Intuit | 91.04 Bn | 70.38 Bn | 3.44 Bn |
| 8 | Relx | 70.51 Bn | 69.60 Bn | - |
| 9 | Strategy | 53.24 Bn | 46.23 Bn | 81.55 Mn |
| 10 | Thomson Reuters | 48.40 Bn | 45.18 Bn | - |
Historic Data
| Date | Value |
|---|---|
| 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 |
| Sep 30, 2021 | 2.24 Bn |
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_KEY
import 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();