Quanta Services (PWR) Operating Expenses (2009 - 2026)
Quanta Services' Operating Expenses was $698.49 million in Q2 2026, up 32.2% from $528.36 million a year earlier and up 12.5% from the prior quarter.
Quanta Services (PWR) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Quanta Services' Operating Expenses was $2.49 billion through Jun 30, 2026, up 23.5% year-over-year; for FY2025, it came in at $2.19 billion, up 20.0% from FY2024.
- Operating Expenses has now increased for ten consecutive years, with a five-year compound annual growth rate of 17.6% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $1.82 billion in FY2024 (+17.3%), $1.56 billion in FY2023 (+16.3%), $1.34 billion in FY2022 (+15.6%) and $1.16 billion in FY2021 (+18.6%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q1 2009.
- Compared with a year earlier, Operating Expenses has increased for 14 straight quarters, with growth averaging 23.8% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2021 (growth of 38.3%); the worst was Q4 2022 (a decline of 7.2%).
- Per Business Quant data, PWR's Operating Expenses in the three quarters before Q2 2026 was $620.73 million (Q1 2026), $593.94 million (Q4 2025) and $572.95 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Quanta Services | 102.72 Bn | 100.91 Bn | 1.55 Bn | 698.49 Mn |
| 2 | Ferrovial | 37.36 Bn | 17.95 Bn | - | - |
| 3 | Emcor | 34.45 Bn | 30.84 Bn | 1.02 Bn | 475.04 Mn |
| 4 | Mastec | 17.62 Bn | 16.52 Bn | 556.28 Mn | 292.57 Mn |
| 5 | Jacobs Solutions | 16.24 Bn | 10.89 Bn | 810.70 Mn | 524.00 Mn |
| 6 | Sterling Infrastructure | 16.06 Bn | 14.42 Bn | 289.96 Mn | 65.66 Mn |
| 7 | IES Holdings | 13.53 Bn | 12.40 Bn | 340.66 Mn | 162.17 Mn |
| 8 | Dycom Industries | 8.22 Bn | 7.36 Bn | - | - |
| 9 | Aecom | 7.69 Bn | 3.02 Bn | -34.04 Mn | 46.45 Mn |
| 10 | Stantec | 7.62 Bn | 7.62 Bn | - | 972.05 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 698.49 Mn |
| Mar 31, 2026 | 620.73 Mn |
| Dec 31, 2025 | 593.94 Mn |
| Sep 30, 2025 | 572.95 Mn |
| Jun 30, 2025 | 528.36 Mn |
| Mar 31, 2025 | 493.97 Mn |
| Dec 31, 2024 | 506.18 Mn |
| Sep 30, 2024 | 483.88 Mn |
| Jun 30, 2024 | 432.36 Mn |
| Mar 31, 2024 | 402.34 Mn |
| Dec 31, 2023 | 399.88 Mn |
| Sep 30, 2023 | 386.54 Mn |
| Jun 30, 2023 | 384.17 Mn |
| Mar 31, 2023 | 384.55 Mn |
| Dec 31, 2022 | 341.13 Mn |
| Sep 30, 2022 | 347.45 Mn |
| Jun 30, 2022 | 323.25 Mn |
| Mar 31, 2022 | 324.89 Mn |
| Dec 31, 2021 | 367.65 Mn |
| Sep 30, 2021 | 274.85 Mn |
Quanta Services Operating Expenses 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=operating-expenses&ticker=PWR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PWR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=PWR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();