Wolverine World Wide (WWW) Asset Utilization Ratio (2010 - 2026)
Wolverine World Wide's (WWW) Asset Utilization Ratio came in at 1.15 for Q2 2027, up 10.7% from 1.04 a year earlier.
Powered by 
Analysis
Wolverine World Wide (WWW) Asset Utilization Ratio (2010 - 2026) Analysis & Trends
For FY2026, Wolverine World Wide's Asset Utilization Ratio stood at 1.11.
- In prior years, Wolverine World Wide's Asset Utilization Ratio was 0.94 in FY2024 (-4.6%), 0.98 in FY2023 (-6.9%) and 1.06 in FY2022 (+3.4%).
- The Q2 2027 figure stands as the highest quarterly Asset Utilization Ratio since Q3 2011.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Asset Util. (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 52.47 Bn | 18.46 Bn | 5.39 Bn | 1.23 |
| 2 | Tapestry | 23.05 Bn | 19.01 Bn | 1.56 Bn | 1.22 |
| 3 | Ralph Lauren | 21.35 Bn | 13.45 Bn | 1.44 Bn | 1.09 |
| 4 | Deckers Outdoor | 11.12 Bn | 3.99 Bn | - | - |
| 5 | Lululemon Athletica | 10.25 Bn | 4.50 Bn | 1.46 Bn | 1.30 |
| 6 | Levi Strauss | 7.60 Bn | 4.25 Bn | 979.10 Mn | 1.00 |
| 7 | Gildan Activewear | 6.52 Bn | 5.51 Bn | 459.76 Mn | 0.46 |
| 8 | Birkenstock Holding | 5.97 Bn | 4.27 Bn | 493.89 Mn | 0.42 |
| 9 | Crocs | 5.64 Bn | 5.06 Bn | 700.71 Mn | 0.93 |
| 10 | Wolverine World Wide | 1.57 Bn | 946.97 Mn | 235.30 Mn | 1.15 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 4, 2026 | 1.15 |
| Jan 3, 2026 | 1.10 |
| Sep 27, 2025 | 1.05 |
| Jun 28, 2025 | 1.04 |
| Mar 29, 2025 | 1.06 |
| Dec 28, 2024 | 1.02 |
| Sep 28, 2024 | 1.00 |
| Jun 29, 2024 | 1.03 |
| Mar 30, 2024 | 1.04 |
| Dec 30, 2023 | 1.04 |
| Sep 30, 2023 | 1.04 |
| Jul 1, 2023 | 1.07 |
| Apr 1, 2023 | 1.09 |
| Dec 31, 2022 | 0.95 |
| Oct 1, 2022 | 0.87 |
| Jul 2, 2022 | 0.91 |
| Apr 2, 2022 | 0.90 |
| Oct 2, 2021 | 0.92 |
| Jul 3, 2021 | 0.94 |
| Apr 3, 2021 | 0.85 |
API Access
Wolverine World Wide Asset Utilization Ratio 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=asset-utilization-ratio&ticker=WWW&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "asset-utilization-ratio", "ticker": "WWW", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=asset-utilization-ratio&ticker=WWW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();