Dirtt Environmental Solutions (DRTTF) Operating Expenses (2018 - 2026)
Dirtt Environmental Solutions (DRTTF) posted Operating Expenses of $12.68 million for Q2 2026, down 16.3% from $15.16 million a year earlier and down 22.0% from the prior quarter.
Dirtt Environmental Solutions (DRTTF) Operating Expenses (2018 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Dirtt Environmental Solutions was $65.68 million, up 7.8% year-over-year; for FY2025, it was $66.75 million, up 11.0% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of -2.2% (FY2020 to FY2025).
- In prior years, Dirtt Environmental Solutions' Operating Expenses was $60.15 million in FY2024 (-21.0%), $76.1 million in FY2023 (-12.7%), $87.2 million in FY2022 (+2.1%) and $85.4 million in FY2021 (+14.5%).
- The Q2 2026 figure stands as the lowest quarterly Operating Expenses in data going back to Q3 2018.
- On a year-over-year basis, Operating Expenses increased in four of the last eight quarters, with an average decline of 0.9%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2025, with growth of 40.9%; the weakest was Q4 2022, with a decline of 35.2%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $16.27 million (Q1 2026), $21.57 million (Q4 2025) and $15.17 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Trane Technologies | 101.77 Bn | 96.49 Bn | 2.26 Bn | 1.04 Bn |
| 2 | Johnson Controls International | 89.79 Bn | 87.52 Bn | 2.47 Bn | 1.49 Bn |
| 3 | Comfort Systems Usa | 49.37 Bn | 44.62 Bn | 844.23 Mn | 287.05 Mn |
| 4 | Carrier Global | 46.49 Bn | 40.80 Bn | 1.94 Bn | 5.58 Bn |
| 5 | Otis Worldwide | 27.54 Bn | 23.96 Bn | 1.14 Bn | 3.28 Bn |
| 6 | James Hardie Industries | 15.37 Bn | 14.44 Bn | 548.70 Mn | 327.40 Mn |
| 7 | Masco | 14.88 Bn | 12.74 Bn | 868.00 Mn | 397.00 Mn |
| 8 | Carlisle Companies | 13.65 Bn | 9.99 Bn | 568.40 Mn | 210.70 Mn |
| 9 | Allegion | 13.45 Bn | 12.16 Bn | 517.50 Mn | 262.80 Mn |
| 10 | Dirtt Environmental Solutions | 108.52 Mn | 32.24 Mn | 13.98 Mn | 12.68 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 12.68 Mn |
| Mar 31, 2026 | 16.27 Mn |
| Dec 31, 2025 | 21.57 Mn |
| Sep 30, 2025 | 15.17 Mn |
| Jun 30, 2025 | 15.16 Mn |
| Mar 31, 2025 | 14.86 Mn |
| Dec 31, 2024 | 15.30 Mn |
| Sep 30, 2024 | 15.63 Mn |
| Jun 30, 2024 | 14.36 Mn |
| Mar 31, 2024 | 14.86 Mn |
| Dec 31, 2023 | 17.30 Mn |
| Sep 30, 2023 | 23.16 Mn |
| Jun 30, 2023 | 16.84 Mn |
| Mar 31, 2023 | 18.80 Mn |
| Dec 31, 2022 | 15.81 Mn |
| Sep 30, 2022 | 20.99 Mn |
| Jun 30, 2022 | 25.55 Mn |
| Mar 31, 2022 | 24.85 Mn |
| Dec 31, 2021 | 24.38 Mn |
| Sep 30, 2021 | 20.44 Mn |
Dirtt Environmental Solutions 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=DRTTF&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DRTTF", "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=DRTTF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();