Dycom Industries (DY) Operating Expenses (2009 - 2026)
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.
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Analysis
Dycom Industries (DY) Operating Expenses (2009 - 2026) 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 Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Quanta Services | 87.86 Bn | 84.32 Bn | 2.01 Bn | 783.29 Mn |
| 2 | Ferrovial | 43.95 Bn | 24.55 Bn | - | - |
| 3 | Emcor | 28.40 Bn | 24.67 Bn | 1.11 Bn | 528.43 Mn |
| 4 | Jacobs Solutions | 18.40 Bn | 13.04 Bn | 810.70 Mn | 524.00 Mn |
| 5 | Mastec | 14.54 Bn | 13.22 Bn | 660.86 Mn | 322.35 Mn |
| 6 | Aecom | 9.09 Bn | 4.41 Bn | -34.04 Mn | 46.45 Mn |
| 7 | Sterling Infrastructure | 8.86 Bn | 7.32 Bn | 377.28 Mn | 63.50 Mn |
| 8 | Stantec | 8.64 Bn | 7.57 Bn | 1.36 Bn | 972.05 Mn |
| 9 | IES Holdings | 6.87 Bn | 5.74 Bn | 340.66 Mn | 162.30 Mn |
| 10 | Dycom Industries | 6.60 Bn | 4.90 Bn | 440.55 Mn | 1.81 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 1.81 Bn |
| May 2, 2026 | 1.82 Bn |
| Jan 31, 2026 | 127.67 Mn |
| 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 |
API Access
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_KEYimport 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();