Mastech Digital (MHH) Operating Expenses (2010 - 2026)
Mastech Digital's Operating Expenses was $12.32 million in Q2 2026, down 10.7% from $13.79 million a year earlier but up 12.3% from the prior quarter.
Mastech Digital (MHH) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Mastech Digital's Operating Expenses was $47.82 million through Jun 30, 2026, down 13.9% year-over-year; for FY2025, it came in at $53.06 million, up 2.4% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 6.8% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $51.81 million in FY2024 (-0.2%), $51.91 million in FY2023 (+1.8%), $50.98 million in FY2022 (+14.0%) and $44.72 million in FY2021 (+17.3%).
- Quarterly Operating Expenses has moved between $9.87 million (Q4 2023) and $16.47 million (Q2 2023) over five years.
- Compared with a year earlier, Operating Expenses has declined for three straight quarters, with growth averaging 2.9% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2024 (growth of 48.4%); the worst was Q1 2026 (a decline of 25.6%).
- Per Business Quant data, MHH's Operating Expenses in the three quarters before Q2 2026 was $10.97 million (Q1 2026), $11.88 million (Q4 2025) and $12.64 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 43.52 Bn | 43.57 Bn | 1.60 Bn | 528.00 Mn |
| 2 | Cognizant Technology Solutions | 25.96 Bn | 19.13 Bn | 1.83 Bn | 812.00 Mn |
| 3 | Td Synnex | 20.53 Bn | 14.56 Bn | 1.34 Bn | 822.22 Mn |
| 4 | Cdw | 16.06 Bn | 14.05 Bn | 1.32 Bn | 891.20 Mn |
| 5 | Cgi | 15.14 Bn | 12.92 Bn | - | 12.44 Mn |
| 6 | Arrow Electronics | 11.55 Bn | 10.58 Bn | 1.13 Bn | 747.88 Mn |
| 7 | Avnet | 8.20 Bn | 7.38 Bn | 865.03 Mn | 634.01 Mn |
| 8 | Ingram Micro Holding | 6.32 Bn | 1.92 Bn | 958.68 Mn | 722.71 Mn |
| 9 | EPAM Systems | 5.59 Bn | 1.23 Bn | 429.57 Mn | 245.25 Mn |
| 10 | Mastech Digital | 86.25 Mn | -52.18 Mn | 12.00 Mn | 12.32 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 12.32 Mn |
| Mar 31, 2026 | 10.97 Mn |
| Dec 31, 2025 | 11.88 Mn |
| Sep 30, 2025 | 12.64 Mn |
| Jun 30, 2025 | 13.79 Mn |
| Mar 31, 2025 | 14.75 Mn |
| Dec 31, 2024 | 14.65 Mn |
| Sep 30, 2024 | 12.33 Mn |
| Jun 30, 2024 | 12.29 Mn |
| Mar 31, 2024 | 12.54 Mn |
| Dec 31, 2023 | 9.87 Mn |
| Sep 30, 2023 | 12.62 Mn |
| Jun 30, 2023 | 16.47 Mn |
| Mar 31, 2023 | 12.95 Mn |
| Dec 31, 2022 | 12.23 Mn |
| Sep 30, 2022 | 12.93 Mn |
| Jun 30, 2022 | 13.20 Mn |
| Mar 31, 2022 | 12.63 Mn |
| Dec 31, 2021 | 11.15 Mn |
| Sep 30, 2021 | 11.65 Mn |
Mastech Digital 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=MHH&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MHH", "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=MHH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();