Open Text (OTEX) Operating Expenses (2009 - 2026)
Open Text (OTEX) reported Operating Expenses of $691.79 million for fiscal Q4 2026 (quarter ended Jun 30, 2026), down 9.7% from $766.14 million a year earlier and down 6.0% from the prior quarter.
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Analysis
Open Text (OTEX) Operating Expenses (2009 - 2026) Analysis & Trends
For FY2026 (ended Jun 30, 2026), Open Text posted Operating Expenses of $2.79 billion, down 2.0% from FY2025.
- Operating Expenses has a five-year compound annual growth rate of 11.6% (FY2021 to FY2026).
- By fiscal year, Operating Expenses came in at $2.84 billion in FY2025 (-14.0%), $3.3 billion in FY2024 (+24.6%), $2.65 billion in FY2023 (+48.4%) and $1.79 billion in FY2022 (+10.9%).
- Five-year quarterly Operating Expenses spans a low of $391.5 million in fiscal Q1 2022 and a high of $942.73 million in fiscal Q4 2023.
- Year over year, Operating Expenses gained in two of the last eight quarters, with an average decline of 7.7%.
- The high point for year-over-year Operating Expenses in five years was fiscal Q2 2024 (growth of 94.0%); the low point was fiscal Q2 2025 (a decline of 22.1%).
- Per Business Quant data, the three fiscal quarters before Q4 2026 came in at $736.06 million (Q3 2026), $690.45 million (Q2 2026) and $667.57 million (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Adobe | 90.32 Bn | 65.57 Bn | 6.00 Bn | 3.64 Bn |
| 2 | Atlassian | 46.45 Bn | 39.73 Bn | 1.53 Bn | 1.32 Bn |
| 3 | Twilio | 44.08 Bn | 34.07 Bn | 725.87 Mn | 641.32 Mn |
| 4 | Autodesk | 43.30 Bn | 31.34 Bn | 1.87 Bn | 1.27 Bn |
| 5 | Zoom Communications | 25.52 Bn | -5.27 Bn | 985.50 Mn | 671.18 Mn |
| 6 | Figma | 10.74 Bn | 4.24 Bn | 309.61 Mn | 426.90 Mn |
| 7 | Dropbox | 7.01 Bn | 2.65 Bn | 506.50 Mn | 341.70 Mn |
| 8 | Nice | 6.59 Bn | 5.06 Bn | 995.81 Mn | 765.06 Mn |
| 9 | RingCentral | 6.37 Bn | 5.87 Bn | 472.31 Mn | 422.02 Mn |
| 10 | Open Text | 5.38 Bn | 813.39 Mn | 1.01 Bn | 691.79 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 691.79 Mn |
| Mar 31, 2026 | 736.06 Mn |
| Dec 31, 2025 | 690.45 Mn |
| Sep 30, 2025 | 667.57 Mn |
| Jun 30, 2025 | 766.14 Mn |
| Mar 31, 2025 | 689.16 Mn |
| Dec 31, 2024 | 682.18 Mn |
| Sep 30, 2024 | 704.12 Mn |
| Jun 30, 2024 | 794.46 Mn |
| Mar 31, 2024 | 828.71 Mn |
| Dec 31, 2023 | 875.25 Mn |
| Sep 30, 2023 | 805.53 Mn |
| Jun 30, 2023 | 942.73 Mn |
| Mar 31, 2023 | 810.96 Mn |
| Dec 31, 2022 | 451.08 Mn |
| Sep 30, 2022 | 447.34 Mn |
| Jun 30, 2022 | 496.20 Mn |
| Mar 31, 2022 | 476.44 Mn |
| Dec 31, 2021 | 422.73 Mn |
| Sep 30, 2021 | 391.50 Mn |
API Access
Open Text 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=OTEX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "OTEX", "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=OTEX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();