IES Holdings (IESC) Operating Expenses (2010 - 2026)
IES Holdings (IESC) reported Operating Expenses of $162.17 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), up 27.0% from $127.67 million a year earlier and up 13.7% from the prior quarter.
IES Holdings (IESC) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, IES Holdings' Operating Expenses came in at $555.37 million, up 21.0% year-over-year; for FY2025 (ended Sep 30, 2025), it was $476.12 million, up 19.8% from FY2024.
- Operating Expenses has increased for 13 consecutive fiscal years, with a five-year compound annual growth rate of 22.7% (FY2020 to FY2025).
- By fiscal year, Operating Expenses came in at $397.4 million in FY2024 (+33.0%), $298.9 million in FY2023 (+13.7%), $262.99 million in FY2022 (+29.9%) and $202.46 million in FY2021 (+18.5%).
- The fiscal Q3 2026 figure ranks as the highest quarterly Operating Expenses in data going back to fiscal Q3 2010.
- Year over year, Operating Expenses has now increased in each of the last 33 quarters, with growth averaging 21.9% over the last eight quarters.
- Across the past five years, year-over-year growth in Operating Expenses ran from 9.3% in fiscal Q2 2023 to 40.8% in fiscal Q3 2024.
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $142.57 million (Q2 2026), $121.94 million (Q1 2026) and $128.69 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Quanta Services | 82.97 Bn | 81.16 Bn | 1.55 Bn | 698.49 Mn |
| 2 | Ferrovial | 35.82 Bn | 16.13 Bn | - | - |
| 3 | Emcor | 29.22 Bn | 25.61 Bn | 1.02 Bn | 475.04 Mn |
| 4 | Jacobs Solutions | 17.13 Bn | 11.78 Bn | 810.70 Mn | 524.00 Mn |
| 5 | Mastec | 13.77 Bn | 12.68 Bn | 556.28 Mn | 292.57 Mn |
| 6 | Sterling Infrastructure | 11.44 Bn | 9.80 Bn | 289.96 Mn | 65.66 Mn |
| 7 | IES Holdings | 8.80 Bn | 7.66 Bn | 340.66 Mn | 162.17 Mn |
| 8 | Stantec | 8.31 Bn | 7.24 Bn | 1.36 Bn | 972.05 Mn |
| 9 | Aecom | 7.83 Bn | 3.16 Bn | -34.04 Mn | 46.45 Mn |
| 10 | Dycom Industries | 6.74 Bn | 5.88 Bn | - | - |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 162.17 Mn |
| Mar 31, 2026 | 142.57 Mn |
| Dec 31, 2025 | 121.94 Mn |
| Sep 30, 2025 | 128.69 Mn |
| Jun 30, 2025 | 127.67 Mn |
| Mar 31, 2025 | 116.38 Mn |
| Dec 31, 2024 | 103.38 Mn |
| Sep 30, 2024 | 111.50 Mn |
| Jun 30, 2024 | 104.74 Mn |
| Mar 31, 2024 | 95.27 Mn |
| Dec 31, 2023 | 85.89 Mn |
| Sep 30, 2023 | 87.28 Mn |
| Jun 30, 2023 | 74.37 Mn |
| Mar 31, 2023 | 69.42 Mn |
| Dec 31, 2022 | 67.84 Mn |
| Sep 30, 2022 | 72.86 Mn |
| Jun 30, 2022 | 67.16 Mn |
| Mar 31, 2022 | 63.50 Mn |
| Dec 31, 2021 | 59.47 Mn |
| Sep 30, 2021 | 61.54 Mn |
IES Holdings 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=IESC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "IESC", "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=IESC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();