Armstrong World Industries (AWI) Operating Expenses (2010 - 2026)
Armstrong World Industries' Operating Expenses came in at $93.7 million for Q2 2026, up 11.0% from $84.4 million a year earlier and up 6.0% from the prior quarter.
Armstrong World Industries (AWI) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Armstrong World Industries reported Operating Expenses of $359.6 million, up 10.5% year-over-year; for FY2025, it was $339.5 million, up 10.0% from FY2024.
- Operating Expenses has increased in each of the last three years, with a five-year compound annual growth rate of 15.8% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $308.5 million in FY2024 (+17.5%), $262.5 million in FY2023 (+10.8%), $237 million in FY2022 (-0.2%) and $237.4 million in FY2021 (+45.5%).
- The Q2 2026 figure represents the highest quarterly Operating Expenses since Q1 2015.
- Year-over-year, Operating Expenses has increased for 14 consecutive quarters, with growth averaging 12.9% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q3 2021 (growth of 52.0%), and the weakest in Q3 2022 (a decline of 4.8%).
- Business Quant data shows AWI's Operating Expenses at $88.4 million (Q1 2026), $87.4 million (Q4 2025) and $90.1 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Trane Technologies | 100.25 Bn | 94.99 Bn | 2.26 Bn | 1.04 Bn |
| 2 | Johnson Controls International | 90.55 Bn | 88.31 Bn | 2.47 Bn | 1.49 Bn |
| 3 | Comfort Systems Usa | 58.58 Bn | 53.83 Bn | 844.23 Mn | 287.05 Mn |
| 4 | Carrier Global | 45.65 Bn | 40.28 Bn | 1.94 Bn | 5.58 Bn |
| 5 | Otis Worldwide | 24.99 Bn | 21.59 Bn | 1.14 Bn | 3.28 Bn |
| 6 | James Hardie Industries | 14.56 Bn | 13.29 Bn | 548.70 Mn | 327.40 Mn |
| 7 | Masco | 13.48 Bn | 11.59 Bn | 868.00 Mn | 397.00 Mn |
| 8 | Allegion | 13.22 Bn | 11.93 Bn | 517.50 Mn | 262.80 Mn |
| 9 | Carlisle Companies | 12.96 Bn | 9.31 Bn | 568.40 Mn | 210.70 Mn |
| 10 | Armstrong World Industries | 6.91 Bn | 6.55 Bn | 195.00 Mn | 93.70 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 93.70 Mn |
| Mar 31, 2026 | 88.40 Mn |
| Dec 31, 2025 | 87.40 Mn |
| Sep 30, 2025 | 90.10 Mn |
| Jun 30, 2025 | 84.40 Mn |
| Mar 31, 2025 | 78.00 Mn |
| Dec 31, 2024 | 85.40 Mn |
| Sep 30, 2024 | 77.60 Mn |
| Jun 30, 2024 | 80.60 Mn |
| Mar 31, 2024 | 65.40 Mn |
| Dec 31, 2023 | 73.30 Mn |
| Sep 30, 2023 | 64.60 Mn |
| Jun 30, 2023 | 61.90 Mn |
| Mar 31, 2023 | 62.70 Mn |
| Dec 31, 2022 | 59.10 Mn |
| Sep 30, 2022 | 59.30 Mn |
| Jun 30, 2022 | 61.50 Mn |
| Mar 31, 2022 | 57.10 Mn |
| Dec 31, 2021 | 60.90 Mn |
| Sep 30, 2021 | 62.30 Mn |
Armstrong World 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=AWI&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AWI", "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=AWI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();