Dycom Industries (DY) Operating Expenses (2011 - 2025)
Dycom Industries (DY) reported Operating Expenses of $1.3 billion for fiscal Q3 2026 (quarter ended Oct 25, 2025), up 11.2% from $1.17 billion a year earlier and up 5.1% from the prior quarter.
Dycom Industries (DY) Operating Expenses (2011 - 2025) Analysis & Trends
Over the twelve months ended Oct 25, 2025, Dycom Industries' Operating Expenses came in at $4.74 billion, up 11.9% year-over-year; for FY2025 (ended Jan 25, 2025), it was $4.36 billion, up 13.2% from FY2024.
- Operating Expenses has increased for three consecutive fiscal years, with a five-year compound annual growth rate of 6.2% (FY2020 to FY2025).
- By fiscal year, Operating Expenses came in at $3.85 billion in FY2024 (+7.1%), $3.6 billion in FY2023 (+18.0%), $3.05 billion in FY2022 (-2.6%) and $3.13 billion in FY2021 (-2.8%).
- The fiscal Q3 2026 figure ranks as the highest quarterly Operating Expenses in data going back to fiscal Q3 2019.
- Year over year, Operating Expenses has now increased in each of the last 17 quarters, with growth averaging 11.4% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was fiscal Q2 2023 (growth of 20.2%); the low point was fiscal Q1 2022 (a decline of 14.1%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $1.24 billion (Q2 2026), $1.17 billion (Q1 2026) and $1.03 billion (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Quanta Services | 101.70 Bn | 99.89 Bn | 1.55 Bn | 698.49 Mn |
| 2 | Ferrovial | 38.65 Bn | 19.25 Bn | - | - |
| 3 | Emcor | 34.80 Bn | 31.19 Bn | 1.02 Bn | 475.04 Mn |
| 4 | Mastec | 17.34 Bn | 16.24 Bn | 556.28 Mn | 292.57 Mn |
| 5 | Sterling Infrastructure | 16.37 Bn | 14.73 Bn | 289.96 Mn | 65.66 Mn |
| 6 | Jacobs Solutions | 16.17 Bn | 10.82 Bn | 810.70 Mn | 524.00 Mn |
| 7 | IES Holdings | 13.52 Bn | 12.39 Bn | 340.66 Mn | 162.17 Mn |
| 8 | Dycom Industries | 8.20 Bn | 7.33 Bn | - | - |
| 9 | Stantec | 7.70 Bn | 7.70 Bn | - | 972.05 Mn |
| 10 | Aecom | 7.68 Bn | 3.00 Bn | -34.04 Mn | 46.45 Mn |
Historic Data
| Date | Value |
|---|---|
| Oct 25, 2025 | 1.30 Bn |
| Jul 26, 2025 | 1.24 Bn |
| Apr 26, 2025 | 1.17 Bn |
| Jan 25, 2025 | 1.03 Bn |
| Oct 26, 2024 | 1.17 Bn |
| Jul 27, 2024 | 1.10 Bn |
| Apr 27, 2024 | 1.06 Bn |
| Jan 27, 2024 | 909.66 Mn |
| Oct 28, 2023 | 1.02 Bn |
| Jul 29, 2023 | 953.23 Mn |
| Apr 29, 2023 | 972.99 Mn |
| Jan 28, 2023 | 874.37 Mn |
| Oct 29, 2022 | 965.15 Mn |
| Jul 30, 2022 | 906.66 Mn |
| Apr 30, 2022 | 851.75 Mn |
| Jan 29, 2022 | 757.77 Mn |
| Oct 30, 2021 | 810.53 Mn |
| Jul 31, 2021 | 754.56 Mn |
| May 1, 2021 | 726.10 Mn |
| Jan 30, 2021 | 752.96 Mn |
Dycom Industries 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=DY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DY", "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=DY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();