Jones Lang Lasalle (JLL) Return on Sales [ROS] (2009 - 2026)
Jones Lang Lasalle's Return on Sales [ROS] came in at 4.20% for Q2 2026, up 1.04 percentage points from 3.16% a year earlier and up 1.00 percentage points from the prior quarter.
Jones Lang Lasalle (JLL) Return on Sales [ROS] (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Jones Lang Lasalle reported Return on Sales [ROS] of 4.65%, up 0.93 percentage points year-over-year.
- Return on Sales [ROS] carries a five-year change of +0.83 percentage points (FY2020 to FY2025).
- Going back by year, Return on Sales [ROS] was 3.70% in FY2024 (+0.93 pp), 2.78% in FY2023 (-1.38 pp), 4.16% in FY2022 (-1.23 pp) and 5.39% in FY2021 (+2.02 pp).
- The five-year range for quarterly Return on Sales [ROS] is 0.38% (Q1 2023) to 7.49% (Q4 2021).
- Year-over-year, Return on Sales [ROS] has increased for five consecutive quarters, with an average year-over-year change of +0.76 percentage points over the last eight quarters.
- The fastest year-over-year change in Return on Sales [ROS] over five years came in Q3 2021 (a gain of 2.10 percentage points), and the weakest in Q1 2023 (a drop of 3.28 percentage points).
- Business Quant data shows JLL's Return on Sales [ROS] at 3.20% (Q1 2026), 6.66% (Q4 2025) and 4.20% (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Cbre | 37.56 Bn | 31.32 Bn | 2.09 Bn | 3.25% |
| 2 | KE Holdings | 36.95 Bn | 17.65 Bn | 1.03 Bn | 12.33% |
| 3 | Jones Lang Lasalle | 14.12 Bn | 12.33 Bn | - | 4.20% |
| 4 | Compass | 6.95 Bn | 5.41 Bn | - | 2.88% |
| 5 | Colliers International | 4.59 Bn | 3.66 Bn | 635.11 Mn | 0.05% |
| 6 | Cushman & Wakefield | 2.80 Bn | 278.27 Mn | 512.00 Mn | 4.86% |
| 7 | Newmark | 2.01 Bn | 1.39 Bn | - | 4.55% |
| 8 | Marcus & Millichap | 1.08 Bn | 178.91 Mn | - | 1.09% |
| 9 | Agnt | 609.98 Mn | 139.66 Mn | 98.80 Mn | 0.11% |
| 10 | Rmr | 568.78 Mn | 493.24 Mn | - | -6.04% |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 4.20% |
| Mar 31, 2026 | 3.20% |
| Dec 31, 2025 | 6.66% |
| Sep 30, 2025 | 4.20% |
| Jun 30, 2025 | 3.16% |
| Mar 31, 2025 | 2.09% |
| Dec 31, 2024 | 5.48% |
| Sep 30, 2024 | 3.89% |
| Jun 30, 2024 | 2.71% |
| Mar 31, 2024 | 2.23% |
| Dec 31, 2023 | 4.94% |
| Sep 30, 2023 | 2.33% |
| Jun 30, 2023 | 2.95% |
| Mar 31, 2023 | 0.38% |
| Dec 31, 2022 | 4.54% |
| Sep 30, 2022 | 3.91% |
| Jun 30, 2022 | 4.45% |
| Mar 31, 2022 | 3.66% |
| Dec 31, 2021 | 7.49% |
| Sep 30, 2021 | 5.99% |
Jones Lang Lasalle 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=JLL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "JLL", "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=JLL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();