TE Connectivity (TEL) Operating Expenses (2009 - 2026)
TE Connectivity (TEL) posted Operating Expenses of $845 million for fiscal Q3 2026 (quarter ended Jun 26, 2026), up 18.7% from $712 million a year earlier and up 8.9% from the prior quarter.
TE Connectivity (TEL) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 26, 2026, Operating Expenses at TE Connectivity was $3.13 billion, up 12.4% year-over-year; for FY2025 (ended Sep 26, 2025), it came in at $2.81 billion, up 7.3% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 4.4% (FY2020 to FY2025).
- In prior fiscal years, TE Connectivity's Operating Expenses was $2.62 billion in FY2024 (-0.8%), $2.64 billion in FY2023 (+8.2%), $2.44 billion in FY2022 (+1.8%) and $2.4 billion in FY2021 (+6.0%).
- The fiscal Q3 2026 figure stands as the highest quarterly Operating Expenses in data going back to fiscal Q2 2009.
- On a year-over-year basis, Operating Expenses has increased in each of the last eight quarters, with growth averaging 11.1% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was fiscal Q1 2023, with growth of 19.7%; the weakest was fiscal Q1 2022, with a decline of 16.8%.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $776 million (Q2 2026), $773 million (Q1 2026) and $737 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 376.87 Bn | 348.57 Bn | 7.76 Bn | 16.25 Bn |
| 2 | Amphenol | 208.65 Bn | 203.35 Bn | 3.55 Bn | 963.40 Mn |
| 3 | Deere | 185.97 Bn | 194.73 Bn | 4.66 Bn | 10.73 Bn |
| 4 | Eaton | 167.50 Bn | 164.73 Bn | 2.86 Bn | 1.46 Bn |
| 5 | Parker-Hannifin | 122.25 Bn | 120.39 Bn | 2.25 Bn | 874.00 Mn |
| 6 | Vertiv Holdings | 93.95 Bn | 84.57 Bn | 1.23 Bn | 490.50 Mn |
| 7 | Emerson Electric | 88.90 Bn | 81.65 Bn | 2.66 Bn | 1.34 Bn |
| 8 | 3M | 87.39 Bn | 68.85 Bn | 2.68 Bn | 5.52 Bn |
| 9 | Illinois Tool Works | 78.00 Bn | 74.56 Bn | 1.90 Bn | - |
| 10 | TE Connectivity | 62.17 Bn | 57.46 Bn | 1.84 Bn | 845.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 26, 2026 | 845.00 Mn |
| Mar 27, 2026 | 776.00 Mn |
| Dec 26, 2025 | 773.00 Mn |
| Sep 26, 2025 | 737.00 Mn |
| Jun 27, 2025 | 712.00 Mn |
| Mar 28, 2025 | 701.00 Mn |
| Dec 27, 2024 | 658.00 Mn |
| Sep 27, 2024 | 715.00 Mn |
| Jun 28, 2024 | 636.00 Mn |
| Mar 29, 2024 | 660.00 Mn |
| Dec 29, 2023 | 606.00 Mn |
| Sep 29, 2023 | 638.00 Mn |
| Jun 30, 2023 | 649.00 Mn |
| Mar 31, 2023 | 682.00 Mn |
| Dec 30, 2022 | 669.00 Mn |
| Sep 30, 2022 | 659.00 Mn |
| Jun 24, 2022 | 598.00 Mn |
| Mar 25, 2022 | 623.00 Mn |
| Dec 24, 2021 | 559.00 Mn |
| Sep 24, 2021 | 595.00 Mn |
TE Connectivity 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=TEL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "TEL", "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=TEL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();