GXO Logistics (GXO) Restructuring Costs (2020 - 2026)
GXO Logistics (GXO) posted Restructuring Costs of $5.0 million for Q2 2026, up 66.67% on a QoQ basis from $3.0 million in Q1 2026, and up 150.0% year-over-year from $2.0 million in Q2 2025.
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Analysis
GXO Logistics (GXO) Restructuring Costs (2020 - 2026) Analysis & Trends
GXO Logistics has reported Restructuring Costs for 7 years, with the latest figure at $5.0 million in Q2 2026.
- On a quarterly basis, Restructuring Costs rose 150.0% year-over-year to $5.0 million in Q2 2026; TTM through Jun 2026 was $16.0 million, a 40.74% decrease from a year earlier, with the FY2025 full-year figure at $27.0 million, up 8.0% from the prior year.
- Restructuring Costs was $5.0 million for Q2 2026 at GXO Logistics, up from $3.0 million in the prior quarter.
- The five-year high for Restructuring Costs was $21.0 million in Q1 2023, with the low at -$6.0 million in Q4 2023.
- Average Restructuring Costs over 5 years is $6.9 million, with a median of $5.0 million recorded in 2025.
- The sharpest annual moves came in 2022 and 2023: Restructuring Costs surged 1900.0% in 2022, then slumped 133.33% in 2023.
- Over 5 years, Restructuring Costs stood at $18.0 million in 2022, then sank by 133.33% to -$6.0 million in 2023, then jumped by 83.33% to -$1.0 million in 2024, then jumped by 600.0% to $5.0 million in 2025, then changed by 0.0% to $5.0 million in 2026.
- The last three Restructuring Costs figures came in at $5.0 million (Q2 2026), $3.0 million (Q1 2026), and $5.0 million (Q4 2025), per Business Quant data.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Copart | 27.11 Bn | 23.77 Bn | 732.88 Mn |
| 2 | Expeditors International Of Washington | 24.83 Bn | 23.80 Bn | 1.09 Bn |
| 3 | C. H. Robinson Worldwide | 17.92 Bn | 17.76 Bn | 1.11 Bn |
| 4 | Rb Global | 15.40 Bn | 14.87 Bn | 935.50 Mn |
| 5 | Ryder System | 9.14 Bn | 9.14 Bn | 1.45 Bn |
| 6 | Landstar System | 5.78 Bn | 5.43 Bn | 308.86 Mn |
| 7 | GXO Logistics | 5.27 Bn | 4.53 Bn | 508.00 Mn |
| 8 | Rxo | 3.34 Bn | 3.32 Bn | 302.00 Mn |
| 9 | Hub | 1.98 Bn | 1.89 Bn | 250.84 Mn |
| 10 | Cryoport | 862.04 Mn | 465.34 Mn | 22.82 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.00 Mn |
| Mar 31, 2026 | 3.00 Mn |
| Dec 31, 2025 | 5.00 Mn |
| Sep 30, 2025 | 3.00 Mn |
| Jun 30, 2025 | 2.00 Mn |
| Mar 31, 2025 | 17.00 Mn |
| Dec 31, 2024 | -1.00 Mn |
| Sep 30, 2024 | 9.00 Mn |
| Jun 30, 2024 | 1.00 Mn |
| Mar 31, 2024 | 16.00 Mn |
| Dec 31, 2023 | -6.00 Mn |
| Sep 30, 2023 | 7.00 Mn |
| Jun 30, 2023 | 3.00 Mn |
| Mar 31, 2023 | 21.00 Mn |
| Dec 31, 2022 | 18.00 Mn |
| Jun 30, 2022 | 1.00 Mn |
| Mar 31, 2022 | 13.00 Mn |
| Dec 31, 2021 | -1.00 Mn |
| Sep 30, 2021 | 2.00 Mn |
| Jun 30, 2021 | -1.00 Mn |
API Access
GXO Logistics Restructuring Costs 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=restructuring-costs&ticker=GXO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "restructuring-costs", "ticker": "GXO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=restructuring-costs&ticker=GXO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();