Cdw (CDW) Operating Expenses (2010 - 2026)
Cdw's Operating Expenses was $891.2 million in Q2 2026, up 8.6% from $821 million a year earlier and up 9.5% from the prior quarter.
Powered by 
Analysis
Cdw (CDW) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Cdw's Operating Expenses was $3.34 billion through Jun 30, 2026, up 9.6% year-over-year; for FY2025, it came in at $3.22 billion, up 9.0% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 9.6% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $2.95 billion in FY2024 (-0.7%), $2.97 billion in FY2023 (+0.7%), $2.95 billion in FY2022 (+37.3%) and $2.15 billion in FY2021 (+5.8%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2010.
- Compared with a year earlier, Operating Expenses has increased for seven straight quarters, with growth averaging 6.4% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q1 2022 (growth of 52.0%); the worst was Q3 2024 (a decline of 4.0%).
- Per Business Quant data, CDW's Operating Expenses in the three quarters before Q2 2026 was $814 million (Q1 2026), $823.7 million (Q4 2025) and $812.2 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 52.03 Bn | 38.53 Bn | 1.60 Bn | 528.00 Mn |
| 2 | Cognizant Technology Solutions | 31.75 Bn | 24.91 Bn | 1.83 Bn | 812.00 Mn |
| 3 | Wipro | 21.48 Bn | 16.18 Bn | 738.00 Mn | 2.23 Bn |
| 4 | Cdw | 19.70 Bn | 17.69 Bn | 1.32 Bn | 891.20 Mn |
| 5 | Td Synnex | 19.65 Bn | 13.81 Bn | 1.43 Bn | 784.64 Mn |
| 6 | Cgi | 17.59 Bn | 15.39 Bn | - | - |
| 7 | Arrow Electronics | 11.05 Bn | 10.00 Bn | 1.13 Bn | 747.88 Mn |
| 8 | Avnet | 7.49 Bn | 6.67 Bn | 865.03 Mn | 634.01 Mn |
| 9 | EPAM Systems | 6.82 Bn | 2.46 Bn | 429.57 Mn | 245.25 Mn |
| 10 | Ingram Micro Holding | 6.25 Bn | 1.85 Bn | 958.68 Mn | 722.71 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 891.20 Mn |
| Mar 31, 2026 | 814.00 Mn |
| Dec 31, 2025 | 823.70 Mn |
| Sep 30, 2025 | 812.20 Mn |
| Jun 30, 2025 | 821.00 Mn |
| Mar 31, 2025 | 760.90 Mn |
| Dec 31, 2024 | 746.70 Mn |
| Sep 30, 2024 | 719.10 Mn |
| Jun 30, 2024 | 750.00 Mn |
| Mar 31, 2024 | 735.30 Mn |
| Dec 31, 2023 | 718.80 Mn |
| Sep 30, 2023 | 749.30 Mn |
| Jun 30, 2023 | 769.30 Mn |
| Mar 31, 2023 | 734.10 Mn |
| Dec 31, 2022 | 734.50 Mn |
| Sep 30, 2022 | 766.80 Mn |
| Jun 30, 2022 | 732.90 Mn |
| Mar 31, 2022 | 717.20 Mn |
| Dec 31, 2021 | 636.30 Mn |
| Sep 30, 2021 | 528.50 Mn |
API Access
Cdw 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=CDW&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CDW", "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=CDW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();