Enpro (NPO) Operating Expenses (2010 - 2026)
Enpro (NPO) reported Operating Expenses of $91.3 million for Q2 2026, up 15.4% from $79.1 million a year earlier and up 5.5% from the prior quarter.
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Analysis
Enpro (NPO) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Enpro's Operating Expenses came in at $348.2 million, up 12.8% year-over-year; for FY2025, it came in at $325.9 million, up 7.7% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 4.9% (FY2020 to FY2025).
- By year, Operating Expenses came in at $302.5 million in FY2024 (-13.6%), $350 million in FY2023 (-0.3%), $351.1 million in FY2022 (+33.7%) and $262.7 million in FY2021 (+2.5%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses since Q2 2023.
- Year over year, Operating Expenses has now increased in each of the last five quarters, with growth averaging 9.3% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q2 2023 (growth of 95.9%); the low point was Q4 2023 (a decline of 47.3%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $86.5 million (Q1 2026), $91.1 million (Q4 2025) and $79.3 million (Q3 2025).
Peer Set
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 | Enpro | 6.48 Bn | 6.08 Bn | 149.00 Mn | 91.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 91.30 Mn |
| Mar 31, 2026 | 86.50 Mn |
| Dec 31, 2025 | 91.10 Mn |
| Sep 30, 2025 | 79.30 Mn |
| Jun 30, 2025 | 79.10 Mn |
| Mar 31, 2025 | 76.40 Mn |
| Dec 31, 2024 | 77.10 Mn |
| Sep 30, 2024 | 76.20 Mn |
| Jun 30, 2024 | 71.00 Mn |
| Mar 31, 2024 | 78.20 Mn |
| Dec 31, 2023 | 75.80 Mn |
| Sep 30, 2023 | 67.70 Mn |
| Jun 30, 2023 | 134.20 Mn |
| Mar 31, 2023 | 72.30 Mn |
| Dec 31, 2022 | 143.70 Mn |
| Sep 30, 2022 | 65.90 Mn |
| Jun 30, 2022 | 68.50 Mn |
| Mar 31, 2022 | 73.00 Mn |
| Dec 31, 2021 | 78.30 Mn |
| Sep 30, 2021 | 60.10 Mn |
API Access
Enpro 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=NPO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "NPO", "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=NPO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();