DXC Technology (DXC) Operating Expenses (2016 - 2026)
DXC Technology (DXC) posted Operating Expenses of $2.76 billion for fiscal Q1 2027 (quarter ended Jun 30, 2026), down 10.8% from $3.09 billion a year earlier and down 13.3% from the prior quarter.
DXC Technology (DXC) Operating Expenses (2016 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at DXC Technology was $11.99 billion, down 1.4% year-over-year; for FY2026 (ended Mar 31, 2026), it came in at $12.33 billion, up 0.7% from FY2025.
- Annual Operating Expenses shows a five-year compound annual growth rate of -6.3% (FY2021 to FY2026).
- In prior fiscal years, DXC Technology's Operating Expenses was $12.24 billion in FY2025 (-9.7%), $13.56 billion in FY2024 (-11.5%), $15.32 billion in FY2023 (+1.3%) and $15.12 billion in FY2022 (-11.4%).
- The fiscal Q1 2027 figure stands as the lowest quarterly Operating Expenses since fiscal Q3 2021.
- On a year-over-year basis, Operating Expenses increased in 1 of the last eight quarters, with an average decline of 4.8%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was fiscal Q3 2022, with growth of 69.8%; the weakest was fiscal Q4 2022, with a decline of 38.0%.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $3.18 billion (Q4 2026), $3.02 billion (Q3 2026) and $3.03 billion (Q2 2026).
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 | DXC Technology | 2.38 Bn | -4.98 Bn | 611.00 Mn | 2.76 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.76 Bn |
| Mar 31, 2026 | 3.18 Bn |
| Dec 31, 2025 | 3.02 Bn |
| Sep 30, 2025 | 3.03 Bn |
| Jun 30, 2025 | 3.09 Bn |
| Mar 31, 2025 | 2.83 Bn |
| Dec 31, 2024 | 3.09 Bn |
| Sep 30, 2024 | 3.15 Bn |
| Jun 30, 2024 | 3.17 Bn |
| Mar 31, 2024 | 3.70 Bn |
| Dec 31, 2023 | 3.19 Bn |
| Sep 30, 2023 | 3.31 Bn |
| Jun 30, 2023 | 3.37 Bn |
| Mar 31, 2023 | 4.75 Bn |
| Dec 31, 2022 | 3.46 Bn |
| Sep 30, 2022 | 3.51 Bn |
| Jun 30, 2022 | 3.59 Bn |
| Mar 31, 2022 | 3.21 Bn |
| Dec 31, 2021 | 3.92 Bn |
| Sep 30, 2021 | 4.28 Bn |
DXC Technology 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=DXC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DXC", "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=DXC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();