Geo (GEO) Other Operating Expenses (2010 - 2026)
Geo (GEO) posted Other Operating Expenses of $465.23 million for Q2 2026, up 11.0% from $418.97 million a year earlier and up 0.9% from the prior quarter.
Geo (GEO) Other Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Other Operating Expenses at Geo was $1.84 billion, up 15.4% year-over-year; for FY2025, it was $1.61 billion, up 11.5% from FY2024.
- Annual Other Operating Expenses has increased for four consecutive years, with a five-year compound annual growth rate of 2.0% (FY2020 to FY2025).
- In prior years, Geo's Other Operating Expenses was $1.45 billion in FY2024 (+0.4%), $1.44 billion in FY2023 (+6.5%), $1.35 billion in FY2022 (+3.0%) and $1.32 billion in FY2021 (-10.3%).
- Quarterly Other Operating Expenses has run from a low of $336.6 million in Q1 2022 to a high of $470.08 million in Q4 2025 over five years.
- On a year-over-year basis, Other Operating Expenses has increased in each of the last six quarters, with growth averaging 8.8% over the last eight quarters.
- The strongest year-over-year quarter for Other Operating Expenses in the past five years was Q4 2025, with growth of 21.6%; the weakest was Q1 2022, with a decline of 11.3%.
- According to Business Quant data, Other Operating Expenses for the three prior quarters was $460.93 million (Q1 2026), $470.08 million (Q4 2025) and $446.76 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Accenture | 122.50 Bn | 82.91 Bn | 6.13 Bn |
| 2 | Cintas | 78.05 Bn | 77.24 Bn | 1.48 Bn |
| 3 | Iron Mountain | 33.02 Bn | 32.53 Bn | 1.07 Bn |
| 4 | APi | 16.68 Bn | 13.72 Bn | 703.00 Mn |
| 5 | Rollins | 14.49 Bn | 14.04 Bn | 569.95 Mn |
| 6 | Aramark | 14.11 Bn | 12.13 Bn | 430.34 Mn |
| 7 | UL Solutions | 13.27 Bn | 12.05 Bn | 417.00 Mn |
| 8 | Gartner | 11.78 Bn | 5.47 Bn | 1.19 Bn |
| 9 | Rentokil Initial | 9.98 Bn | 3.32 Bn | - |
| 10 | Geo | 4.03 Bn | 3.64 Bn | - |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 465.23 Mn |
| Mar 31, 2026 | 460.93 Mn |
| Dec 31, 2025 | 470.08 Mn |
| Sep 30, 2025 | 446.76 Mn |
| Jun 30, 2025 | 418.97 Mn |
| Mar 31, 2025 | 396.03 Mn |
| Dec 31, 2024 | 386.68 Mn |
| Sep 30, 2024 | 394.84 Mn |
| Jun 30, 2024 | 391.33 Mn |
| Mar 31, 2024 | 388.61 Mn |
| Dec 31, 2023 | 390.36 Mn |
| Sep 30, 2023 | 393.31 Mn |
| Jun 30, 2023 | 386.44 Mn |
| Mar 31, 2023 | 383.36 Mn |
| Dec 31, 2022 | 380.63 Mn |
| Sep 30, 2022 | 386.19 Mn |
| Jun 30, 2022 | 362.50 Mn |
| Mar 31, 2022 | 336.60 Mn |
| Dec 31, 2021 | 345.32 Mn |
| Sep 30, 2021 | 349.43 Mn |
Geo Other 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=other-operating-expenses&ticker=GEO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "ticker": "GEO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=other-operating-expenses&ticker=GEO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();