Telephone & Data Systems (TDS) Operating Expenses (2009 - 2026)
Telephone & Data Systems' Operating Expenses came in at -$63.93 million for Q2 2026, compared with $310.85 million a year earlier.
Telephone & Data Systems (TDS) Operating Expenses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Telephone & Data Systems reported Operating Expenses of $792.08 million, down 43.1% year-over-year; for FY2025, it came in at $1.33 billion, down 10.9% from FY2024.
- Operating Expenses has declined in each of the last three years, with a five-year compound annual growth rate of -23.2% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $1.49 billion in FY2024 (-27.0%), $2.04 billion in FY2023 (-61.5%), $5.29 billion in FY2022 (+4.4%) and $5.07 billion in FY2021 (+2.1%).
- The Q2 2026 figure represents the lowest quarterly Operating Expenses since Q4 2023.
- Year-over-year, Operating Expenses increased in 1 of the last six quarters, with an average decline of 44.2%.
- The fastest year-over-year change in Operating Expenses over five years came in Q4 2025 (growth of 12.7%), and the weakest in Q2 2025 (a decline of 74.1%).
- Business Quant data shows TDS's Operating Expenses at $165.63 million (Q1 2026), $313.88 million (Q4 2025) and $376.5 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Verizon Communications | 193.94 Bn | 158.35 Bn | 27.03 Bn | 27.07 Bn |
| 2 | T-Mobile US | 178.90 Bn | 163.65 Bn | 14.76 Bn | 17.30 Bn |
| 3 | At&T | 170.76 Bn | 118.71 Bn | 25.82 Bn | 24.52 Bn |
| 4 | Grupo Televisa, S.A.B | 146.22 Bn | 134.85 Bn | 318.12 Mn | -117.85 Mn |
| 5 | Comcast | 77.07 Bn | 41.32 Bn | - | 24.78 Bn |
| 6 | Chunghwa Telecom | 35.67 Bn | 31.52 Bn | 728.80 Mn | 309.31 Mn |
| 7 | EchoStar | 25.89 Bn | 17.02 Bn | 1.65 Bn | 3.06 Bn |
| 8 | AST SpaceMobile | 23.74 Bn | 24.24 Bn | 7.95 Mn | 329.10 Mn |
| 9 | Bce | 19.19 Bn | 17.52 Bn | - | -2.51 Bn |
| 10 | Telephone & Data Systems | 4.00 Bn | -1.03 Bn | 179.96 Mn | -63.93 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -63.93 Mn |
| Mar 31, 2026 | 165.63 Mn |
| Dec 31, 2025 | 313.88 Mn |
| Sep 30, 2025 | 376.50 Mn |
| Jun 30, 2025 | 310.85 Mn |
| Mar 31, 2025 | 324.37 Mn |
| Dec 31, 2024 | 278.47 Mn |
| Sep 30, 2024 | 477.23 Mn |
| Jun 30, 2024 | 1.20 Bn |
| Mar 31, 2024 | 1.20 Bn |
| Dec 31, 2023 | -1.70 Bn |
| Sep 30, 2023 | 1.23 Bn |
| Jun 30, 2023 | 1.23 Bn |
| Mar 31, 2023 | 1.27 Bn |
| Dec 31, 2022 | 1.38 Bn |
| Sep 30, 2022 | 1.40 Bn |
| Jun 30, 2022 | 1.29 Bn |
| Mar 31, 2022 | 1.22 Bn |
| Dec 31, 2021 | 1.35 Bn |
| Sep 30, 2021 | 1.26 Bn |
Telephone & Data Systems 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=TDS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "TDS", "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=TDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();