Ingersoll Rand (IR) Operating Expenses (2016 - 2026)
Ingersoll Rand's Operating Expenses was $400.8 million in Q2 2026, up 8.0% from $371.2 million a year earlier and up 8.1% from the prior quarter.
Ingersoll Rand (IR) Operating Expenses (2016 - 2026) Analysis & Trends
On a trailing twelve-month basis, Ingersoll Rand's Operating Expenses was $1.49 billion through Jun 30, 2026, up 7.4% year-over-year; for FY2025, it came in at $1.44 billion, up 7.1% from FY2024.
- Operating Expenses has now increased for five consecutive years, with a five-year compound annual growth rate of 12.8% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $1.34 billion in FY2024 (+5.6%), $1.27 billion in FY2023 (+16.1%), $1.1 billion in FY2022 (+6.6%) and $1.03 billion in FY2021 (+30.2%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2016.
- Compared with a year earlier, Operating Expenses has increased for 26 straight quarters, with growth averaging 6.1% over the last eight quarters.
- The year-over-year growth in Operating Expenses has ranged between 0.3% (Q4 2024) and 19.9% (Q4 2023) over the last five years.
- Per Business Quant data, IR's Operating Expenses in the three quarters before Q2 2026 was $370.7 million (Q1 2026), $357.1 million (Q4 2025) and $361 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 372.79 Bn | 344.49 Bn | 7.76 Bn | 16.25 Bn |
| 2 | Amphenol | 207.98 Bn | 202.68 Bn | 3.55 Bn | 963.40 Mn |
| 3 | Deere | 181.02 Bn | 189.78 Bn | 4.66 Bn | 10.73 Bn |
| 4 | Eaton | 166.86 Bn | 164.09 Bn | 2.86 Bn | 1.46 Bn |
| 5 | Parker-Hannifin | 120.45 Bn | 118.58 Bn | 2.25 Bn | 874.00 Mn |
| 6 | Vertiv Holdings | 92.94 Bn | 83.56 Bn | 1.23 Bn | 490.50 Mn |
| 7 | Emerson Electric | 86.56 Bn | 79.32 Bn | 2.66 Bn | 1.34 Bn |
| 8 | 3M | 84.72 Bn | 66.18 Bn | 2.68 Bn | 5.52 Bn |
| 9 | Illinois Tool Works | 73.32 Bn | 69.88 Bn | 1.90 Bn | - |
| 10 | Ingersoll Rand | 29.15 Bn | 24.35 Bn | 862.60 Mn | 400.80 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 400.80 Mn |
| Mar 31, 2026 | 370.70 Mn |
| Dec 31, 2025 | 357.10 Mn |
| Sep 30, 2025 | 361.00 Mn |
| Jun 30, 2025 | 371.20 Mn |
| Mar 31, 2025 | 350.00 Mn |
| Dec 31, 2024 | 331.70 Mn |
| Sep 30, 2024 | 334.30 Mn |
| Jun 30, 2024 | 342.10 Mn |
| Mar 31, 2024 | 336.30 Mn |
| Dec 31, 2023 | 330.80 Mn |
| Sep 30, 2023 | 315.20 Mn |
| Jun 30, 2023 | 315.60 Mn |
| Mar 31, 2023 | 311.10 Mn |
| Dec 31, 2022 | 276.00 Mn |
| Sep 30, 2022 | 278.70 Mn |
| Jun 30, 2022 | 275.60 Mn |
| Mar 31, 2022 | 265.50 Mn |
| Dec 31, 2021 | 255.90 Mn |
| Sep 30, 2021 | 252.60 Mn |
Ingersoll Rand 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=IR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "IR", "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=IR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();