Automatic Data Processing (ADP) Dividends payables (2015 - 2026)
Automatic Data Processing's Dividends payables came in at $671.9 million for fiscal Q4 2026 (quarter ended Jun 30, 2026), up 8.3% from $620.6 million a year earlier but down 0.7% from the prior quarter.
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Analysis
Automatic Data Processing (ADP) Dividends payables (2015 - 2026) Analysis & Trends
Going back to fiscal Q4 2015, Automatic Data Processing's Dividends payables data covers 45 quarters.
- Dividends payables has increased in each of the last 11 fiscal years, with a five-year compound annual growth rate of 11.4% (FY2021 to FY2026).
- Going back by fiscal year, Dividends payables was $620.6 million in FY2025 (+9.6%), $566.4 million in FY2024 (+11.1%), $510 million in FY2023 (+18.7%) and $429.6 million in FY2022 (+9.9%).
- The five-year range for quarterly Dividends payables is $389.5 million (fiscal Q1 2022) to $680.5 million (fiscal Q2 2026).
- Year-over-year, Dividends payables has increased for 41 consecutive quarters, with growth averaging 9.4% over the last eight quarters.
- Across the past five years, year-over-year growth in Dividends payables ran from 0.6% in fiscal Q1 2022 to 18.9% in fiscal Q1 2024.
- Business Quant data shows ADP's Dividends payables at $676.8 million (Q3 2026), $680.5 million (Q2 2026) and $618.9 million (Q1 2026) in the three fiscal quarters before Q4 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Dividends payables (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 | 671.90 Mn |
| 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 | 155.16 Mn |
| 10 | Workday | 45.49 Bn | 21.61 Bn | 2.00 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 671.90 Mn |
| Mar 31, 2026 | 676.80 Mn |
| Dec 31, 2025 | 680.50 Mn |
| Sep 30, 2025 | 618.90 Mn |
| Jun 30, 2025 | 620.60 Mn |
| Mar 31, 2025 | 620.70 Mn |
| Dec 31, 2024 | 621.60 Mn |
| Sep 30, 2024 | 565.90 Mn |
| Jun 30, 2024 | 566.40 Mn |
| Mar 31, 2024 | 568.90 Mn |
| Dec 31, 2023 | 569.70 Mn |
| Sep 30, 2023 | 509.90 Mn |
| Jun 30, 2023 | 510.00 Mn |
| Mar 31, 2023 | 511.60 Mn |
| Dec 31, 2022 | 514.60 Mn |
| Sep 30, 2022 | 428.80 Mn |
| Jun 30, 2022 | 429.60 Mn |
| Mar 31, 2022 | 431.70 Mn |
| Dec 31, 2021 | 433.60 Mn |
| Sep 30, 2021 | 389.50 Mn |
API Access
Automatic Data Processing Dividends payables 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=dividends-payables&ticker=ADP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "dividends-payables", "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=dividends-payables&ticker=ADP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();