Global Industrial (GIC) Return on Sales [ROS] (2010 - 2026)
Global Industrial (GIC) posted Return on Sales [ROS] of 8.40% for Q3 2026, up 0.96 percentage points from 7.44% a year earlier but down 4.36 percentage points from the prior quarter.
Global Industrial (GIC) Return on Sales [ROS] (2010 - 2026) Analysis & Trends
For the trailing twelve months through Sep 30, 2026, Return on Sales [ROS] at Global Industrial was 8.30%, up 1.38 percentage points year-over-year; for FY2025, it was 7.08%, up 0.96 percentage points from FY2024.
- Annual Return on Sales [ROS] shows a five-year change of -1.10 percentage points (FY2020 to FY2025).
- In prior years, Global Industrial's Return on Sales [ROS] was 6.12% in FY2024 (-1.46 pp), 7.57% in FY2023 (-1.45 pp), 9.02% in FY2022 (+0.74 pp) and 8.28% in FY2021 (+0.10 pp).
- Quarterly Return on Sales [ROS] has run from a low of 4.80% in Q4 2024 to a high of 12.75% in Q2 2026 over five years.
- On a year-over-year basis, Return on Sales [ROS] has increased in each of the last seven quarters, with an average year-over-year change of +0.82 percentage points over the last eight quarters.
- The strongest year-over-year quarter for Return on Sales [ROS] in the past five years was Q1 2022, with a gain of 7.59 percentage points; the weakest was Q1 2023, with a drop of 3.72 percentage points.
- According to Business Quant data, Return on Sales [ROS] for the three prior quarters was 12.75% (Q2 2026), 5.88% (Q1 2026) and 5.67% (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | United Rentals | 70.32 Bn | 69.44 Bn | 2.05 Bn | 28.80% |
| 2 | W.W. Grainger | 68.06 Bn | 65.42 Bn | 2.01 Bn | 15.98% |
| 3 | Fastenal | 62.73 Bn | 61.73 Bn | 1.10 Bn | 21.55% |
| 4 | Ferguson Enterprises | 50.77 Bn | 47.99 Bn | 2.32 Bn | 8.19% |
| 5 | Sunbelt Rentals Holdings | 33.62 Bn | 33.50 Bn | 1.25 Bn | 22.18% |
| 6 | Reliance | 21.51 Bn | 20.57 Bn | 1.45 Bn | 10.59% |
| 7 | Wesco International | 15.41 Bn | 12.46 Bn | 1.57 Bn | 6.24% |
| 8 | Watsco | 12.14 Bn | 9.83 Bn | 578.93 Mn | 11.32% |
| 9 | Applied Industrial Technologies | 10.93 Bn | 10.82 Bn | 392.21 Mn | 11.12% |
| 10 | Global Industrial | 1.77 Bn | 1.44 Bn | 138.90 Mn | 8.40% |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 8.40% |
| Jun 30, 2026 | 12.75% |
| Mar 31, 2026 | 5.88% |
| Dec 31, 2025 | 5.67% |
| Sep 30, 2025 | 7.44% |
| Jun 30, 2025 | 9.33% |
| Mar 31, 2025 | 5.67% |
| Dec 31, 2024 | 4.80% |
| Sep 30, 2024 | 6.48% |
| Jun 30, 2024 | 7.59% |
| Mar 31, 2024 | 5.38% |
| Dec 31, 2023 | 6.69% |
| Sep 30, 2023 | 7.95% |
| Jun 30, 2023 | 8.93% |
| Mar 31, 2023 | 6.50% |
| Dec 31, 2022 | 6.79% |
| Sep 30, 2022 | 9.21% |
| Jun 30, 2022 | 9.58% |
| Mar 31, 2022 | 10.22% |
| Dec 31, 2021 | 9.96% |
Global Industrial Return on Sales [ROS] 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=return-on-sales-%5Bros%5D&ticker=GIC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "GIC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=return-on-sales-%5Bros%5D&ticker=GIC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();