Distribution Solutions (DSGR) Operating Expenses (2010 - 2026)
Distribution Solutions' Operating Expenses was $152.27 million in Q2 2026, up 6.3% from $143.26 million a year earlier and up 1.7% from the prior quarter.
Distribution Solutions (DSGR) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Distribution Solutions' Operating Expenses was $598.61 million through Jun 30, 2026, up 5.6% year-over-year; for FY2025, it was $583.78 million, up 4.7% from FY2024.
- Operating Expenses has now increased for five consecutive years, with a five-year compound annual growth rate of 28.6% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $557.82 million in FY2024 (+9.6%), $508.88 million in FY2023 (+45.8%), $349.11 million in FY2022 (+68.5%) and $207.25 million in FY2021 (+24.9%).
- 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 17 straight quarters, with growth averaging 4.5% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q1 2023 (growth of 139.9%); the worst was Q1 2022 (a decline of 2.7%).
- Per Business Quant data, DSGR's Operating Expenses in the three quarters before Q2 2026 was $149.71 million (Q1 2026), $149.93 million (Q4 2025) and $146.71 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | W.W. Grainger | 59.11 Bn | 57.09 Bn | 1.98 Bn | 1.18 Bn |
| 2 | Fastenal | 57.94 Bn | 56.86 Bn | 1.06 Bn | 561.80 Mn |
| 3 | Ferguson Enterprises | 44.13 Bn | 41.35 Bn | 2.32 Bn | 1.61 Bn |
| 4 | Sunbelt Rentals Holdings | 30.69 Bn | 30.57 Bn | 1.25 Bn | 989.00 Mn |
| 5 | Reliance | 20.00 Bn | 19.04 Bn | 1.30 Bn | 4.19 Bn |
| 6 | Wesco International | 17.78 Bn | 15.09 Bn | 1.46 Bn | 1.02 Bn |
| 7 | Applied Industrial Technologies | 12.42 Bn | 12.29 Bn | 411.22 Mn | 251.91 Mn |
| 8 | Watsco | 11.14 Bn | 9.30 Bn | 578.93 Mn | 348.99 Mn |
| 9 | Avantor | 10.34 Bn | 9.14 Bn | 537.00 Mn | 415.20 Mn |
| 10 | Distribution Solutions | 1.62 Bn | 1.37 Bn | 180.14 Mn | 152.27 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 152.27 Mn |
| Mar 31, 2026 | 149.71 Mn |
| Dec 31, 2025 | 149.93 Mn |
| Sep 30, 2025 | 146.71 Mn |
| Jun 30, 2025 | 143.26 Mn |
| Mar 31, 2025 | 143.88 Mn |
| Dec 31, 2024 | 139.92 Mn |
| Sep 30, 2024 | 139.90 Mn |
| Jun 30, 2024 | 137.37 Mn |
| Mar 31, 2024 | 140.63 Mn |
| Dec 31, 2023 | 137.97 Mn |
| Sep 30, 2023 | 132.51 Mn |
| Jun 30, 2023 | 122.25 Mn |
| Mar 31, 2023 | 116.15 Mn |
| Dec 31, 2022 | 103.63 Mn |
| Sep 30, 2022 | 97.14 Mn |
| Jun 30, 2022 | 110.44 Mn |
| Mar 31, 2022 | 48.42 Mn |
| Dec 31, 2021 | 54.83 Mn |
| Sep 30, 2021 | 51.43 Mn |
Distribution 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=DSGR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DSGR", "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=DSGR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();