Motorola Solutions (MSI) Operating Expenses (2009 - 2026)
Motorola Solutions (MSI) recorded Operating Expenses of $756 million in Q2 2026, up 11.0% from $681 million a year earlier and up 9.4% from the prior quarter.
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Analysis
Motorola Solutions (MSI) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Motorola Solutions' Operating Expenses came in at $2.94 billion as of Jul 4, 2026, up 6.6% year-over-year; for FY2025, it was $2.84 billion, up 6.4% from FY2024.
- Annual Operating Expenses has increased for five straight years, with a five-year compound annual growth rate of 7.5% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $2.67 billion in FY2024 (+10.3%), $2.42 billion in FY2023 (+8.5%), $2.23 billion in FY2022 (+6.8%) and $2.09 billion in FY2021 (+5.5%).
- Quarterly Operating Expenses has ranged from $526 million in Q1 2022 to $769 million in Q4 2025 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for 21 consecutive quarters, with growth averaging 8.4% over the last eight quarters.
- Over the past five years, the year-over-year growth in Operating Expenses ranged from 3.3% (Q1 2026) to 14.4% (Q4 2024).
- Per Business Quant, the preceding three quarters came in at $691 million (Q1 2026), $769 million (Q4 2025) and $722 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 339.47 Bn | 293.47 Bn | 4.68 Bn | 10.86 Bn |
| 2 | Rtx | 255.27 Bn | 228.48 Bn | 5.13 Bn | 21.96 Bn |
| 3 | Boeing | 156.48 Bn | 63.18 Bn | 2.41 Bn | 2.35 Bn |
| 4 | Lockheed Martin | 119.91 Bn | 106.64 Bn | 2.45 Bn | - |
| 5 | Howmet Aerospace | 92.95 Bn | 88.55 Bn | 951.00 Mn | 156.00 Mn |
| 6 | General Dynamics | 91.08 Bn | 78.19 Bn | 2.18 Bn | 12.63 Bn |
| 7 | Motorola Solutions | 75.61 Bn | 71.97 Bn | 1.68 Bn | 756.00 Mn |
| 8 | Northrop Grumman | 72.52 Bn | 61.76 Bn | 2.12 Bn | 9.78 Bn |
| 9 | Honeywell International | 67.37 Bn | 19.81 Bn | 3.65 Bn | 1.87 Bn |
| 10 | TransDigm | 61.72 Bn | 49.81 Bn | 1.63 Bn | 332.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 4, 2026 | 756.00 Mn |
| Apr 4, 2026 | 691.00 Mn |
| Dec 31, 2025 | 769.00 Mn |
| Sep 27, 2025 | 722.00 Mn |
| Jun 28, 2025 | 681.00 Mn |
| Mar 29, 2025 | 669.00 Mn |
| Dec 31, 2024 | 733.00 Mn |
| Sep 28, 2024 | 673.00 Mn |
| Jun 29, 2024 | 650.00 Mn |
| Mar 30, 2024 | 615.00 Mn |
| Dec 31, 2023 | 641.00 Mn |
| Sep 30, 2023 | 595.00 Mn |
| Jul 1, 2023 | 605.00 Mn |
| Apr 1, 2023 | 578.00 Mn |
| Dec 31, 2022 | 583.00 Mn |
| Oct 1, 2022 | 575.00 Mn |
| Jul 2, 2022 | 547.00 Mn |
| Apr 2, 2022 | 526.00 Mn |
| Dec 31, 2021 | 557.00 Mn |
| Oct 2, 2021 | 534.00 Mn |
API Access
Motorola Solutions 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=MSI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MSI", "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=MSI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();