Napco Security Technologies (NSSC) Operating Expenses (2010 - 2026)
Napco Security Technologies' Operating Expenses was $15.79 million in fiscal Q4 2026 (quarter ended Jun 30, 2026), up 7.3% from $14.71 million a year earlier but down 48.5% from the prior quarter.
Napco Security Technologies (NSSC) Operating Expenses (2010 - 2026) Analysis & Trends
For FY2026 (ended Jun 30, 2026), Operating Expenses at Napco Security Technologies came in at $74.15 million, up 35.4% from FY2025.
- Operating Expenses has now increased for eight consecutive fiscal years, with a five-year compound annual growth rate of 17.7% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $54.77 million in FY2025 (+14.3%), $47.94 million in FY2024 (+11.7%), $42.91 million in FY2023 (+4.8%) and $40.93 million in FY2022 (+24.7%).
- Quarterly Operating Expenses has moved between $9.28 million (fiscal Q1 2022) and $30.68 million (fiscal Q3 2026) over five years.
- Compared with a year earlier, Operating Expenses has increased for 11 straight quarters, with growth averaging 24.8% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q3 2026 (growth of 119.4%); the worst was fiscal Q2 2023 (a decline of 1.4%).
- Per Business Quant data, NSSC's Operating Expenses in the three fiscal quarters before Q4 2026 was $30.68 million (Q3 2026), $13.49 million (Q2 2026) and $14.2 million (Q1 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 146.43 Bn | 105.71 Bn | 6.13 Bn | 15.54 Bn |
| 2 | Cintas | 86.79 Bn | 85.87 Bn | 1.55 Bn | 841.66 Mn |
| 3 | Iron Mountain | 33.63 Bn | 32.82 Bn | 1.07 Bn | 1.66 Bn |
| 4 | APi | 17.31 Bn | 14.35 Bn | 703.00 Mn | 528.00 Mn |
| 5 | Rollins | 16.03 Bn | 15.57 Bn | 569.95 Mn | 877.22 Mn |
| 6 | UL Solutions | 14.80 Bn | 13.55 Bn | 417.00 Mn | 267.00 Mn |
| 7 | Aramark | 14.78 Bn | 12.73 Bn | 430.34 Mn | 4.84 Bn |
| 8 | Gartner | 14.60 Bn | 8.29 Bn | 1.19 Bn | 1.30 Bn |
| 9 | Rentokil Initial | 10.70 Bn | 4.21 Bn | - | - |
| 10 | Napco Security Technologies | 1.30 Bn | 814.75 Mn | 34.22 Mn | 15.79 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 15.79 Mn |
| Mar 31, 2026 | 30.68 Mn |
| Dec 31, 2025 | 13.49 Mn |
| Sep 30, 2025 | 14.20 Mn |
| Jun 30, 2025 | 14.71 Mn |
| Mar 31, 2025 | 13.98 Mn |
| Dec 31, 2024 | 13.32 Mn |
| Sep 30, 2024 | 12.76 Mn |
| Jun 30, 2024 | 13.88 Mn |
| Mar 31, 2024 | 11.99 Mn |
| Dec 31, 2023 | 11.21 Mn |
| Sep 30, 2023 | 10.86 Mn |
| Jun 30, 2023 | 11.23 Mn |
| Mar 31, 2023 | 10.74 Mn |
| Dec 31, 2022 | 10.03 Mn |
| Sep 30, 2022 | 10.92 Mn |
| Jun 30, 2022 | 11.03 Mn |
| Mar 31, 2022 | 10.45 Mn |
| Dec 31, 2021 | 10.17 Mn |
| Sep 30, 2021 | 9.28 Mn |
Napco Security Technologies 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=NSSC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "NSSC", "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=NSSC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();