Everforth (EFOR) Operating Expenses (2010 - 2026)
Everforth (EFOR) reported Operating Expenses of $226.2 million for Q2 2026, up 4.3% from $216.8 million a year earlier and up 0.8% from the prior quarter.
Powered by 
Analysis
Everforth (EFOR) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Everforth's Operating Expenses came in at $873.3 million, up 4.4% year-over-year; for FY2025, it came in at $854 million, up 4.0% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 6.8% (FY2020 to FY2025).
- By year, Operating Expenses came in at $821.2 million in FY2024 (-2.7%), $844.2 million in FY2023 (-5.7%), $895 million in FY2022 (+21.6%) and $735.8 million in FY2021 (+19.6%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses since Q4 2022.
- Year over year, Operating Expenses has now increased in each of the last six quarters, with growth averaging 2.9% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q4 2021 (growth of 32.3%); the low point was Q4 2023 (a decline of 11.4%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $224.4 million (Q1 2026), $210.5 million (Q4 2025) and $212.2 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 42.66 Bn | 42.72 Bn | 1.60 Bn | 528.00 Mn |
| 2 | Cognizant Technology Solutions | 25.65 Bn | 18.82 Bn | 1.83 Bn | 812.00 Mn |
| 3 | Td Synnex | 20.51 Bn | 14.54 Bn | 1.34 Bn | 822.22 Mn |
| 4 | Cdw | 16.33 Bn | 14.32 Bn | 1.32 Bn | 891.20 Mn |
| 5 | Cgi | 15.07 Bn | 12.85 Bn | - | 12.44 Mn |
| 6 | Arrow Electronics | 11.72 Bn | 10.75 Bn | 1.13 Bn | 747.88 Mn |
| 7 | Avnet | 8.33 Bn | 7.51 Bn | 865.03 Mn | 634.01 Mn |
| 8 | Ingram Micro Holding | 6.23 Bn | 1.84 Bn | 958.68 Mn | 722.71 Mn |
| 9 | EPAM Systems | 5.55 Bn | 1.19 Bn | 429.57 Mn | 245.25 Mn |
| 10 | Everforth | 1.34 Bn | 758.55 Mn | 284.60 Mn | 226.20 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 226.20 Mn |
| Mar 31, 2026 | 224.40 Mn |
| Dec 31, 2025 | 210.50 Mn |
| Sep 30, 2025 | 212.20 Mn |
| Jun 30, 2025 | 216.80 Mn |
| Mar 31, 2025 | 214.50 Mn |
| Dec 31, 2024 | 197.90 Mn |
| Sep 30, 2024 | 207.50 Mn |
| Jun 30, 2024 | 205.60 Mn |
| Mar 31, 2024 | 210.20 Mn |
| Dec 31, 2023 | 203.60 Mn |
| Sep 30, 2023 | 206.00 Mn |
| Jun 30, 2023 | 210.50 Mn |
| Mar 31, 2023 | 224.10 Mn |
| Dec 31, 2022 | 229.90 Mn |
| Sep 30, 2022 | 232.60 Mn |
| Jun 30, 2022 | 220.40 Mn |
| Mar 31, 2022 | 212.10 Mn |
| Dec 31, 2021 | 202.40 Mn |
| Sep 30, 2021 | 192.70 Mn |
API Access
Everforth 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=EFOR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "EFOR", "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=EFOR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();