Organogenesis Holdings (ORGO) Operating Expenses (2016 - 2026)
Organogenesis Holdings (ORGO) recorded Operating Expenses of $94.75 million in Q2 2026, down 16.6% from $113.58 million a year earlier and down 10.7% from the prior quarter.
Organogenesis Holdings (ORGO) Operating Expenses (2016 - 2026) Analysis & Trends
On a TTM basis, Organogenesis Holdings' Operating Expenses came in at $493.32 million as of Jun 30, 2026, up 9.0% year-over-year; for FY2025, it was $519.48 million, up 7.5% from FY2024.
- Annual Operating Expenses has increased for nine straight years, with a five-year compound annual growth rate of 18.3% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $483.33 million in FY2024 (+14.9%), $420.62 million in FY2023 (+30.0%), $323.57 million in FY2022 (+15.2%) and $280.94 million in FY2021 (+25.3%).
- The Q2 2026 figure is the lowest quarterly Operating Expenses since Q1 2024.
- On a year-over-year basis, Operating Expenses rose in four of the last eight quarters, with growth averaging 7.3%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 125.4% in Q4 2023, against a decline of 35.2% in Q4 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $106.12 million (Q1 2026), $162.32 million (Q4 2025) and $130.14 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 250.84 Bn | 229.99 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 174.73 Bn | 145.82 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 159.85 Bn | 143.67 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 146.79 Bn | 126.35 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 114.54 Bn | 80.41 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 105.67 Bn | 91.79 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 63.93 Bn | 58.94 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Becton Dickinson | 50.12 Bn | 47.27 Bn | 2.32 Bn | 4.32 Bn |
| 9 | Edwards Lifesciences | 50.06 Bn | 34.17 Bn | 1.35 Bn | 840.10 Mn |
| 10 | Organogenesis Holdings | 177.57 Mn | -117.33 Mn | 20.08 Mn | 94.75 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 94.75 Mn |
| Mar 31, 2026 | 106.12 Mn |
| Dec 31, 2025 | 162.32 Mn |
| Sep 30, 2025 | 130.14 Mn |
| Jun 30, 2025 | 113.58 Mn |
| Mar 31, 2025 | 113.44 Mn |
| Dec 31, 2024 | 116.44 Mn |
| Sep 30, 2024 | 108.94 Mn |
| Jun 30, 2024 | 144.13 Mn |
| Mar 31, 2024 | 85.13 Mn |
| Dec 31, 2023 | 179.63 Mn |
| Sep 30, 2023 | 74.69 Mn |
| Jun 30, 2023 | 81.26 Mn |
| Mar 31, 2023 | 85.04 Mn |
| Dec 31, 2022 | 79.69 Mn |
| Sep 30, 2022 | 88.90 Mn |
| Jun 30, 2022 | 82.81 Mn |
| Mar 31, 2022 | 72.17 Mn |
| Dec 31, 2021 | 75.51 Mn |
| Sep 30, 2021 | 71.32 Mn |
Organogenesis Holdings 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=ORGO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ORGO", "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=ORGO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();