Douglas Dynamics (PLOW) Operating Expenses (2010 - 2026)
Douglas Dynamics' Operating Expenses was $29.83 million in Q2 2026, up 37.1% from $21.75 million a year earlier and up 13.2% from the prior quarter.
Douglas Dynamics (PLOW) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Douglas Dynamics' Operating Expenses was $105.93 million through Jun 30, 2026, up 15.2% year-over-year; for FY2025, it was $94.89 million, up 3.5% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 8.0% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $91.68 million in FY2024 (+16.3%), $78.84 million in FY2023 (-4.1%), $82.18 million in FY2022 (+4.2%) and $78.84 million in FY2021 (+22.0%).
- 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 three straight quarters, with growth averaging 19.9% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2024 (growth of 48.5%); the worst was Q4 2023 (a decline of 23.5%).
- Per Business Quant data, PLOW's Operating Expenses in the three quarters before Q2 2026 was $26.34 million (Q1 2026), $27.28 million (Q4 2025) and $22.47 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 376.87 Bn | 348.57 Bn | 7.76 Bn | 16.25 Bn |
| 2 | Amphenol | 208.65 Bn | 203.35 Bn | 3.55 Bn | 963.40 Mn |
| 3 | Deere | 185.97 Bn | 194.73 Bn | 4.66 Bn | 10.73 Bn |
| 4 | Eaton | 167.50 Bn | 164.73 Bn | 2.86 Bn | 1.46 Bn |
| 5 | Parker-Hannifin | 122.25 Bn | 120.39 Bn | 2.25 Bn | 874.00 Mn |
| 6 | Vertiv Holdings | 93.95 Bn | 84.57 Bn | 1.23 Bn | 490.50 Mn |
| 7 | Emerson Electric | 88.90 Bn | 81.65 Bn | 2.66 Bn | 1.34 Bn |
| 8 | 3M | 87.39 Bn | 68.85 Bn | 2.68 Bn | 5.52 Bn |
| 9 | Illinois Tool Works | 78.00 Bn | 74.56 Bn | 1.90 Bn | - |
| 10 | Douglas Dynamics | 914.70 Mn | 888.69 Mn | 66.80 Mn | 29.83 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 29.83 Mn |
| Mar 31, 2026 | 26.34 Mn |
| Dec 31, 2025 | 27.28 Mn |
| Sep 30, 2025 | 22.47 Mn |
| Jun 30, 2025 | 21.75 Mn |
| Mar 31, 2025 | 23.39 Mn |
| Dec 31, 2024 | 21.14 Mn |
| Sep 30, 2024 | 25.69 Mn |
| Jun 30, 2024 | 23.37 Mn |
| Mar 31, 2024 | 21.49 Mn |
| Dec 31, 2023 | 14.23 Mn |
| Sep 30, 2023 | 18.00 Mn |
| Jun 30, 2023 | 24.17 Mn |
| Mar 31, 2023 | 22.44 Mn |
| Dec 31, 2022 | 18.61 Mn |
| Sep 30, 2022 | 19.18 Mn |
| Jun 30, 2022 | 23.02 Mn |
| Mar 31, 2022 | 21.37 Mn |
| Dec 31, 2021 | 19.36 Mn |
| Sep 30, 2021 | 17.61 Mn |
Douglas Dynamics 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=PLOW&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PLOW", "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=PLOW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();