Bowman Consulting (BWMN) EPS (Diluted) (2020 - 2026)
Bowman Consulting (BWMN) posted EPS (Diluted) of $0.14 for the quarter ended Jun 30, 2026, down 58.2% from $0.34 a year earlier.
Bowman Consulting (BWMN) EPS (Diluted) (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, EPS (Diluted) at Bowman Consulting was $0.41, down 33.6% year-over-year; for the year ended Dec 31, 2025, it was $0.73, up 320.1% from the prior year.
- Annual EPS (Diluted) shows a five-year compound annual growth rate of 33.4% (years ended Dec 2020 to Dec 2025).
- In prior years, Bowman Consulting's EPS (Diluted) was $0.17 in the year ended Dec 31, 2024, -$0.53 in the year ended Dec 31, 2023, $0.36 in the year ended Dec 31, 2022 and $0.03 in the year ended Dec 31, 2021 (-81.6%).
- Quarterly EPS (Diluted) has run from a low of -$0.61 in the quarter ended Dec 31, 2023 to a high of $0.37 in the quarter ended Sep 30, 2025 over five years.
- On a year-over-year basis, EPS (Diluted) increased in 1 of the last four quarters, with growth averaging 151.8%.
- The strongest year-over-year quarter for EPS (Diluted) in the past five years was the quarter ended Sep 30, 2025, with growth of 776.6%; the weakest was the quarter ended Sep 30, 2023, with a decline of 69.4%.
- According to Business Quant data, EPS (Diluted) for the three prior quarters was -$0.22 (quarter ended Mar 31, 2026), $0.11 (quarter ended Dec 31, 2025) and $0.37 (quarter ended Sep 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EPS (Diluted) (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 147.76 Bn | 107.04 Bn | 6.13 Bn | 3.80 |
| 2 | Cintas | 85.98 Bn | 85.06 Bn | 1.55 Bn | 1.36 |
| 3 | Iron Mountain | 34.10 Bn | 33.29 Bn | 1.07 Bn | 0.34 |
| 4 | APi | 17.41 Bn | 14.44 Bn | 703.00 Mn | 0.20 |
| 5 | Rollins | 15.88 Bn | 15.43 Bn | 569.95 Mn | 0.30 |
| 6 | UL Solutions | 14.81 Bn | 13.57 Bn | 417.00 Mn | 1.21 |
| 7 | Aramark | 14.75 Bn | 12.69 Bn | 430.34 Mn | 0.36 |
| 8 | Gartner | 14.48 Bn | 8.17 Bn | 1.19 Bn | 4.14 |
| 9 | Rentokil Initial | 10.77 Bn | 4.29 Bn | - | - |
| 10 | Bowman Consulting | 703.27 Mn | 653.45 Mn | 77.74 Mn | 0.14 |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 0.14 |
| Mar 31, 2026 | -0.22 |
| Dec 31, 2025 | 0.11 |
| Sep 30, 2025 | 0.37 |
| Jun 30, 2025 | 0.34 |
| Mar 31, 2025 | -0.11 |
| Dec 31, 2024 | 0.35 |
| Sep 30, 2024 | 0.04 |
| Jun 30, 2024 | -0.13 |
| Mar 31, 2024 | -0.11 |
| Dec 31, 2023 | -0.61 |
| Sep 30, 2023 | 0.08 |
| Jun 30, 2023 | -0.05 |
| Mar 31, 2023 | 0.04 |
| Dec 31, 2022 | 0.04 |
| Sep 30, 2022 | 0.25 |
| Jun 30, 2022 | -0.03 |
| Mar 31, 2022 | 0.12 |
| Dec 31, 2021 | -0.06 |
| Sep 30, 2021 | 0.03 |
Bowman Consulting EPS (Diluted) 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=eps-diluted&ticker=BWMN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "eps-diluted", "ticker": "BWMN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=eps-diluted&ticker=BWMN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();