Donnelley Financial Solutions (DFIN) Return on Sales [ROS] (2015 - 2026)
Donnelley Financial Solutions' Return on Sales [ROS] was 17.62% in Q3 2026, up 1.53 percentage points from 16.09% a year earlier but down 7.36 percentage points from the prior quarter.
Donnelley Financial Solutions (DFIN) Return on Sales [ROS] (2015 - 2026) Analysis & Trends
On a trailing twelve-month basis, Donnelley Financial Solutions' Return on Sales [ROS] was 19.23% through Sep 30, 2026, up 1.11 percentage points year-over-year; for FY2025, it came in at 18.40%, up 0.93 percentage points from FY2024.
- Return on Sales [ROS] shows a five-year change of +17.99 percentage points (FY2020 to FY2025).
- In earlier years, Return on Sales [ROS] was 17.47% in FY2024 (+3.67 pp), 13.80% in FY2023 (-3.60 pp), 17.39% in FY2022 (-4.68 pp) and 22.08% in FY2021 (+21.68 pp).
- Quarterly Return on Sales [ROS] has moved between 5.55% (Q4 2023) and 26.58% (Q2 2024) over five years.
- Compared with a year earlier, Return on Sales [ROS] has increased for five straight quarters, with an average year-over-year change of +1.29 percentage points over the last eight quarters.
- The best year-over-year quarter for Return on Sales [ROS] over five years was Q4 2021 (a gain of 30.81 percentage points); the worst was Q3 2022 (a drop of 12.09 percentage points).
- Per Business Quant data, DFIN's Return on Sales [ROS] in the three quarters before Q3 2026 was 24.98% (Q2 2026), 23.60% (Q1 2026) and 8.29% (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 408.11 Bn | 372.93 Bn | 1.93 Bn | 46.89% |
| 2 | Oracle | 355.62 Bn | 227.75 Bn | - | 34.78% |
| 3 | Sap Se | 276.79 Bn | 204.18 Bn | 8.64 Bn | 28.53% |
| 4 | Salesforce | 175.88 Bn | 131.75 Bn | 8.70 Bn | 20.55% |
| 5 | Automatic Data Processing | 121.54 Bn | 108.34 Bn | 2.53 Bn | -30.06% |
| 6 | ServiceNow | 106.68 Bn | 85.94 Bn | 2.90 Bn | 9.38% |
| 7 | Intuit | 93.48 Bn | 72.83 Bn | 3.44 Bn | 10.91% |
| 8 | Relx | 73.38 Bn | 72.47 Bn | - | - |
| 9 | Strategy | 50.44 Bn | 37.58 Bn | 89.63 Mn | 16,670.89% |
| 10 | Donnelley Financial Solutions | 1.67 Bn | 1.57 Bn | 119.80 Mn | 17.62% |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 17.62% |
| Jun 30, 2026 | 24.98% |
| Mar 31, 2026 | 23.60% |
| Dec 31, 2025 | 8.29% |
| Sep 30, 2025 | 16.09% |
| Jun 30, 2025 | 24.21% |
| Mar 31, 2025 | 22.77% |
| Dec 31, 2024 | 5.95% |
| Sep 30, 2024 | 10.14% |
| Jun 30, 2024 | 26.58% |
| Mar 31, 2024 | 21.93% |
| Dec 31, 2023 | 5.55% |
| Sep 30, 2023 | 16.56% |
| Jun 30, 2023 | 22.97% |
| Mar 31, 2023 | 7.45% |
| Dec 31, 2022 | 10.20% |
| Sep 30, 2022 | 14.15% |
| Jun 30, 2022 | 24.76% |
| Mar 31, 2022 | 16.73% |
| Dec 31, 2021 | 17.78% |
Donnelley Financial Solutions Return on Sales [ROS] 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=return-on-sales-%5Bros%5D&ticker=DFIN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "DFIN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=return-on-sales-%5Bros%5D&ticker=DFIN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();