Designer Brands (DBI) Operating Expenses (2010 - 2026)
Designer Brands (DBI) recorded Operating Expenses of $313.41 million in fiscal Q2 2027 (quarter ended Aug 1, 2026), up 5.4% from $297.46 million a year earlier and up 4.7% from the prior quarter.
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Analysis
Designer Brands (DBI) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Designer Brands' Operating Expenses came in at $1.23 billion as of Aug 1, 2026, up 2.0% year-over-year; for FY2026 (ended Jan 31, 2026), it came in at $175.17 million, down 43.9% from FY2025.
- Annual Operating Expenses has a five-year compound annual growth rate of -25.3% (FY2021 to FY2026).
- Across earlier fiscal years, Operating Expenses came in at $311.98 million in FY2025 (-4.5%), $326.84 million in FY2024 (+86.6%), $175.13 million in FY2023 (-79.9%) and $870.68 million in FY2022 (+15.6%).
- Quarterly Operating Expenses has ranged from $211.91 million in fiscal Q3 2022 to $597.51 million in fiscal Q4 2023 over the past five years.
- On a year-over-year basis, Operating Expenses rose in three of the last eight quarters, with an average decline of 1.9%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 155.8% in fiscal Q4 2023, against a decline of 45.3% in fiscal Q4 2024 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $299.21 million (Q1 2027), $319.85 million (Q4 2026) and $300.06 million (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,654.24 Bn | 2,170.93 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 289.19 Bn | 282.43 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 143.39 Bn | 120.94 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 105.29 Bn | 98.25 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 75.79 Bn | 58.72 Bn | 2.12 Bn | 1.02 Bn |
| 6 | Target | 72.00 Bn | 66.59 Bn | 8.94 Bn | 5.73 Bn |
| 7 | O Reilly Automotive | 70.61 Bn | 69.69 Bn | 2.52 Bn | 1.53 Bn |
| 8 | Carvana | 66.52 Bn | 58.12 Bn | 1.38 Bn | 704.00 Mn |
| 9 | Autozone | 47.57 Bn | 46.47 Bn | 2.52 Bn | 1.60 Bn |
| 10 | Designer Brands | 272.49 Mn | 68.58 Mn | 365.36 Mn | 313.41 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 313.41 Mn |
| May 2, 2026 | 299.21 Mn |
| Jan 31, 2026 | 319.85 Mn |
| Nov 1, 2025 | 300.06 Mn |
| Aug 2, 2025 | 297.46 Mn |
| May 3, 2025 | 301.86 Mn |
| Feb 1, 2025 | 311.98 Mn |
| Nov 2, 2024 | 296.83 Mn |
| Aug 3, 2024 | 313.53 Mn |
| May 4, 2024 | 323.49 Mn |
| Feb 3, 2024 | 326.84 Mn |
| Oct 28, 2023 | 320.12 Mn |
| Jul 29, 2023 | 302.91 Mn |
| Apr 29, 2023 | 306.29 Mn |
| Jan 28, 2023 | 597.51 Mn |
| Oct 29, 2022 | 222.23 Mn |
| Jul 30, 2022 | 228.69 Mn |
| Apr 30, 2022 | 223.43 Mn |
| Jan 29, 2022 | 233.57 Mn |
| Oct 30, 2021 | 211.91 Mn |
API Access
Designer Brands Operating Expenses 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=operating-expenses&ticker=DBI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DBI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=DBI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();