Automatic Data Processing (ADP) Enterprise Value (2009 - 2026)
Automatic Data Processing (ADP) posted Enterprise Value of $84.86 billion for fiscal Q4 2026 (quarter ended Jun 30, 2026), down 27.6% from $117.15 billion a year earlier but up 8.6% from the prior quarter.
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Analysis
Automatic Data Processing (ADP) Enterprise Value (2009 - 2026) Analysis & Trends
Since fiscal Q3 2009, Automatic Data Processing has reported Enterprise Value for 70 quarters.
- Annual Enterprise Value shows a five-year compound annual growth rate of 0.8% (FY2021 to FY2026).
- In prior fiscal years, Automatic Data Processing's Enterprise Value was $117.15 billion in FY2025 (+24.5%), $94.11 billion in FY2024 (+6.4%), $88.49 billion in FY2023 (+2.9%) and $85.96 billion in FY2022 (+5.4%).
- Quarterly Enterprise Value has run from a low of $78.17 billion in fiscal Q3 2026 to a high of $121.46 billion in fiscal Q3 2025 over five years.
- On a year-over-year basis, Enterprise Value has declined in each of the last three quarters, with growth averaging 1.0% over the last eight quarters.
- The strongest year-over-year quarter for Enterprise Value in the past five years was fiscal Q1 2022, with growth of 42.0%; the weakest was fiscal Q3 2026, with a decline of 35.6%.
- According to Business Quant data, Enterprise Value for the three prior fiscal quarters was $78.17 billion (Q3 2026), $101.19 billion (Q2 2026) and $110.89 billion (Q1 2026).
Peer Set
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
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 84.86 Bn |
| Mar 31, 2026 | 78.17 Bn |
| Dec 31, 2025 | 101.19 Bn |
| Sep 30, 2025 | 110.89 Bn |
| Jun 30, 2025 | 117.15 Bn |
| Mar 31, 2025 | 121.46 Bn |
| Dec 31, 2024 | 116.90 Bn |
| Sep 30, 2024 | 105.48 Bn |
| Jun 30, 2024 | 94.11 Bn |
| Mar 31, 2024 | 99.05 Bn |
| Dec 31, 2023 | 94.04 Bn |
| Sep 30, 2023 | 97.61 Bn |
| Jun 30, 2023 | 88.49 Bn |
| Mar 31, 2023 | 90.23 Bn |
| Dec 31, 2022 | 97.64 Bn |
| Sep 30, 2022 | 92.71 Bn |
| Jun 30, 2022 | 85.96 Bn |
| Mar 31, 2022 | 93.52 Bn |
| Dec 31, 2021 | 101.92 Bn |
| Sep 30, 2021 | 82.76 Bn |
API Access
Automatic Data Processing Enterprise Value 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=enterprise-value&ticker=ADP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "enterprise-value", "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=enterprise-value&ticker=ADP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();