Automatic Data Processing (ADP) EV to CFO (2009 - 2026)
Automatic Data Processing's (ADP) quarterly EV to CFO came in at 59.42 in Q2 2026, down 27.0% year-over-year from 81.4 in Q2 2025, and up 70.14% quarter-over-quarter from 34.93 in Q1 2026.
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Analysis
Automatic Data Processing (ADP) EV to CFO (2009 - 2026) Analysis & Trends
Automatic Data Processing (ADP) has reported EV to CFO for 18 consecutive years, with 59.42 the latest figure, recorded in Q2 2026.
- On a quarterly basis, EV to CFO fell 27.0% year-over-year to 59.42 in Q2 2026; TTM through Jun 2026 was 15.6, a 34.24% decrease from a year earlier, with the FY2026 full-year figure at 15.6, down 34.24% from the prior year.
- EV to CFO was 59.42 for Q2 2026 at Automatic Data Processing, up from 34.93 in the prior quarter.
- Over five years, EV to CFO peaked at 298.94 in Q3 2023 and troughed at 34.93 in Q1 2026.
- A 5-year average of 102.36 and a median of 90.21 in 2025 frame the typical range for EV to CFO.
- Across the five-year window, EV to CFO slumped 80.99% in 2022 and jumped 131.56% in 2023, its largest moves.
- Over 5 years, EV to CFO stood at 108.52 in 2022, then decreased by 16.07% to 91.09 in 2023, then climbed by 11.56% to 101.62 in 2024, then retreated by 12.1% to 89.32 in 2025, then plunged by 33.47% to 59.42 in 2026.
- The last three EV to CFO figures came in at 59.42 (Q2 2026), 34.93 (Q1 2026), and 89.32 (Q4 2025), per Business Quant data.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palantir Technologies | 460.85 Bn | 451.55 Bn | 1.64 Bn |
| 2 | Oracle | 437.09 Bn | 400.44 Bn | - |
| 3 | Sap Se | 258.74 Bn | 237.66 Bn | 8.40 Bn |
| 4 | Salesforce | 195.52 Bn | 184.12 Bn | 8.70 Bn |
| 5 | ServiceNow | 145.61 Bn | 140.94 Bn | 2.82 Bn |
| 6 | Automatic Data Processing | 104.89 Bn | 100.66 Bn | 2.51 Bn |
| 7 | Intuit | 76.97 Bn | 69.77 Bn | 3.46 Bn |
| 8 | Relx | 60.41 Bn | 60.04 Bn | - |
| 9 | Strategy | 57.09 Bn | 54.64 Bn | 81.55 Mn |
| 10 | Workday | 46.40 Bn | 42.99 Bn | 2.21 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 15.60 |
| Mar 31, 2026 | 14.34 |
| Dec 31, 2025 | 21.35 |
| Sep 30, 2025 | 23.31 |
| Jun 30, 2025 | 23.72 |
| Mar 31, 2025 | 25.30 |
| Dec 31, 2024 | 24.49 |
| Sep 30, 2024 | 22.66 |
| Jun 30, 2024 | 22.64 |
| Mar 31, 2024 | 24.50 |
| Dec 31, 2023 | 23.82 |
| Sep 30, 2023 | 25.58 |
| Jun 30, 2023 | 21.03 |
| Mar 31, 2023 | 22.93 |
| Dec 31, 2022 | 27.88 |
| Sep 30, 2022 | 25.08 |
| Jun 30, 2022 | 27.73 |
| Mar 31, 2022 | 32.94 |
| Dec 31, 2021 | 32.66 |
| Sep 30, 2021 | 30.28 |
API Access
Automatic Data Processing EV to CFO 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=ev-to-cfo&ticker=ADP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ev-to-cfo", "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=ev-to-cfo&ticker=ADP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();