Worthington Steel (WS) Total Non-Current Liabilities (2023 - 2026)
Worthington Steel's Total Non-Current Liabilities came in at $4.3 billion for fiscal Q1 2027 (quarter ended Aug 31, 2026), up 347.5% from $961.3 million a year earlier and up 328.8% from the prior quarter.
Worthington Steel (WS) Total Non-Current Liabilities (2023 - 2026) Analysis & Trends
At the end of FY2026 (ended May 31, 2026), Worthington Steel's Total Non-Current Liabilities was $1 billion, up 37.2% from FY2025.
- Total Non-Current Liabilities has increased in each of the last three fiscal years, with a three-year compound annual growth rate of 20.3% (FY2023 to FY2026).
- Going back by fiscal year, Total Non-Current Liabilities was $731.1 million in FY2025 (+2.3%), $714.6 million in FY2024 (+24.0%) and $576.2 million in FY2023.
- The fiscal Q1 2027 figure represents the highest quarterly Total Non-Current Liabilities in data going back to fiscal Q4 2023.
- Year-over-year, Total Non-Current Liabilities has increased for six consecutive quarters, with growth averaging 64.0% over the last eight quarters.
- The fastest year-over-year change in Total Non-Current Liabilities over five years came in fiscal Q1 2027 (growth of 347.5%), and the weakest in fiscal Q2 2025 (a decline of 19.2%).
- Business Quant data shows WS's Total Non-Current Liabilities at $1 billion (Q4 2026), $997.6 million (Q3 2026) and $849.6 million (Q2 2026) in the three fiscal quarters before Q1 2027.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 267.46 Bn | 238.77 Bn | 7.35 Bn | 76.44 Bn |
| 2 | Amphenol | 197.37 Bn | 192.21 Bn | 4.02 Bn | 28.76 Bn |
| 3 | Deere | 185.36 Bn | 194.13 Bn | 4.66 Bn | - |
| 4 | Eaton | 137.64 Bn | 134.62 Bn | 3.11 Bn | 23.44 Bn |
| 5 | Parker-Hannifin | 121.80 Bn | 119.79 Bn | 2.26 Bn | 25.05 Bn |
| 6 | 3M | 97.84 Bn | 80.25 Bn | 2.78 Bn | 26.86 Bn |
| 7 | Emerson Electric | 93.37 Bn | 85.86 Bn | 2.74 Bn | 17.63 Bn |
| 8 | Illinois Tool Works | 81.86 Bn | 78.53 Bn | 1.91 Bn | 8.26 Bn |
| 9 | Vertiv Holdings | 74.77 Bn | 63.62 Bn | 1.64 Bn | 12.22 Bn |
| 10 | Worthington Steel | 1.97 Bn | 1.84 Bn | 261.20 Mn | 4.30 Bn |
Historic Data
| Date | Value |
|---|---|
| Aug 31, 2026 | 4.30 Bn |
| May 31, 2026 | 1.00 Bn |
| Feb 28, 2026 | 997.60 Mn |
| Nov 30, 2025 | 849.60 Mn |
| Aug 31, 2025 | 961.30 Mn |
| May 31, 2025 | 731.10 Mn |
| Feb 28, 2025 | 620.80 Mn |
| Nov 30, 2024 | 558.90 Mn |
| Aug 31, 2024 | 651.40 Mn |
| May 31, 2024 | 714.60 Mn |
| Feb 29, 2024 | 740.50 Mn |
| Nov 30, 2023 | 691.30 Mn |
| May 31, 2023 | 576.20 Mn |
Worthington Steel Total Non-Current Liabilities 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=total-non-current-liabilities&ticker=WS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "WS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-non-current-liabilities&ticker=WS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();