Wd 40 (WDFC) Total Non-Current Liabilities (2011 - 2026)
Wd 40 (WDFC) posted Total Non-Current Liabilities of $219.28 million for fiscal Q3 2026 (quarter ended May 31, 2026), up 11.1% from $197.44 million a year earlier and up 7.8% from the prior quarter.
Wd 40 (WDFC) Total Non-Current Liabilities (2011 - 2026) Analysis & Trends
At the end of FY2025 (ended Aug 31, 2025), Wd 40's Total Non-Current Liabilities came in at $206.25 million, up 0.9% from FY2024.
- Annual Total Non-Current Liabilities shows a five-year compound annual growth rate of 1.5% (FY2020 to FY2025).
- In prior fiscal years, Wd 40's Total Non-Current Liabilities was $204.45 million in FY2024 (-4.8%), $214.72 million in FY2023 (-8.4%), $234.49 million in FY2022 (+7.4%) and $218.34 million in FY2021 (+14.3%).
- The fiscal Q3 2026 figure stands as the highest quarterly Total Non-Current Liabilities since fiscal Q3 2023.
- On a year-over-year basis, Total Non-Current Liabilities increased in four of the last eight quarters, with an average decline of 0.7%.
- The strongest year-over-year quarter for Total Non-Current Liabilities in the past five years was fiscal Q4 2021, with growth of 14.3%; the weakest was fiscal Q1 2024, with a decline of 15.6%.
- According to Business Quant data, Total Non-Current Liabilities for the three prior fiscal quarters was $203.33 million (Q2 2026), $194.17 million (Q1 2026) and $206.25 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Procter & Gamble | 367.14 Bn | 322.89 Bn | 10.28 Bn | 67.30 Bn |
| 2 | Colgate Palmolive | 74.80 Bn | 69.53 Bn | 3.30 Bn | 14.17 Bn |
| 3 | Estee Lauder Companies | 37.60 Bn | 25.67 Bn | 2.74 Bn | 9.73 Bn |
| 4 | Kenvue | 36.63 Bn | 32.25 Bn | 2.30 Bn | 15.61 Bn |
| 5 | Kimberly Clark | 35.53 Bn | 32.72 Bn | 1.60 Bn | 16.06 Bn |
| 6 | Church & Dwight | 24.88 Bn | 23.41 Bn | 693.90 Mn | 4.43 Bn |
| 7 | Clorox | 10.33 Bn | 8.61 Bn | 804.00 Mn | 7.14 Bn |
| 8 | e.l.f. Beauty | 6.73 Bn | 5.71 Bn | 398.84 Mn | 1.24 Bn |
| 9 | Reynolds Consumer Products | 4.77 Bn | 4.44 Bn | 245.00 Mn | 2.66 Bn |
| 10 | Wd 40 | 2.60 Bn | 2.38 Bn | 110.42 Mn | 219.28 Mn |
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 219.28 Mn |
| Feb 28, 2026 | 203.33 Mn |
| Nov 30, 2025 | 194.17 Mn |
| Aug 31, 2025 | 206.25 Mn |
| May 31, 2025 | 197.44 Mn |
| Feb 28, 2025 | 214.73 Mn |
| Nov 30, 2024 | 206.58 Mn |
| Aug 31, 2024 | 204.45 Mn |
| May 31, 2024 | 207.63 Mn |
| Feb 29, 2024 | 212.82 Mn |
| Nov 30, 2023 | 201.71 Mn |
| Aug 31, 2023 | 214.72 Mn |
| May 31, 2023 | 220.93 Mn |
| Feb 28, 2023 | 241.73 Mn |
| Nov 30, 2022 | 238.89 Mn |
| Aug 31, 2022 | 234.49 Mn |
| May 31, 2022 | 222.75 Mn |
| Feb 28, 2022 | 213.27 Mn |
| Nov 30, 2021 | 211.58 Mn |
| Aug 31, 2021 | 218.34 Mn |
Wd 40 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=WDFC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "WDFC", "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=WDFC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();