1 800 Flowers Com (FLWS) Other Operating Expenses (2010 - 2026)
1 800 Flowers Com (FLWS) recorded Other Operating Expenses of $14.57 million in fiscal Q4 2026 (quarter ended Jun 28, 2026), down 8.6% from $15.94 million a year earlier and down 0.9% from the prior quarter.
1 800 Flowers Com (FLWS) Other Operating Expenses (2010 - 2026) Analysis & Trends
For FY2026 (ended Jun 28, 2026), 1 800 Flowers Com reported Other Operating Expenses of $57.86 million, down 7.1% from FY2025.
- Annual Other Operating Expenses has a five-year compound annual growth rate of 1.2% (FY2021 to FY2026).
- Across earlier fiscal years, Other Operating Expenses came in at $62.28 million in FY2025 (+3.4%), $60.24 million in FY2024 (-0.8%), $60.69 million in FY2023 (+7.3%) and $56.56 million in FY2022 (+3.9%).
- Quarterly Other Operating Expenses has ranged from $14.15 million in fiscal Q1 2026 to $41.37 million in fiscal Q2 2022 over the past five years.
- On a year-over-year basis, Other Operating Expenses has declined for four consecutive quarters, with an average decline of 1.8% over the last eight quarters.
- Peak year-over-year performance for Other Operating Expenses in the last five years was growth of 7.8% in fiscal Q2 2025, against a decline of 9.6% in fiscal Q2 2026 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $14.7 million (Q3 2026), $14.44 million (Q2 2026) and $14.15 million (Q1 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Amazon Com | 2,686.58 Bn | 2,203.28 Bn | 104.83 Bn |
| 2 | Home Depot | 283.87 Bn | 277.11 Bn | 16.12 Bn |
| 3 | Tjx Companies | 145.82 Bn | 123.36 Bn | 5.07 Bn |
| 4 | Lowes Companies | 103.43 Bn | 96.39 Bn | 8.58 Bn |
| 5 | Ross Stores | 74.61 Bn | 57.54 Bn | 2.12 Bn |
| 6 | Target | 71.16 Bn | 65.74 Bn | 8.94 Bn |
| 7 | O Reilly Automotive | 69.71 Bn | 68.80 Bn | 2.52 Bn |
| 8 | Carvana | 68.78 Bn | 60.38 Bn | 1.38 Bn |
| 9 | Autozone | 46.23 Bn | 45.13 Bn | 2.52 Bn |
| 10 | 1 800 Flowers Com | 159.78 Mn | -103.37 Mn | 101.81 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 14.57 Mn |
| Mar 29, 2026 | 14.70 Mn |
| Dec 28, 2025 | 14.44 Mn |
| Sep 28, 2025 | 14.15 Mn |
| Jun 29, 2025 | 15.94 Mn |
| Mar 30, 2025 | 14.73 Mn |
| Dec 29, 2024 | 15.97 Mn |
| Sep 29, 2024 | 15.64 Mn |
| Jun 30, 2024 | 14.82 Mn |
| Mar 31, 2024 | 15.29 Mn |
| Dec 31, 2023 | 14.82 Mn |
| Oct 1, 2023 | 15.30 Mn |
| Jul 2, 2023 | 16.16 Mn |
| Apr 2, 2023 | 14.84 Mn |
| Jan 1, 2023 | 14.95 Mn |
| Oct 2, 2022 | 14.74 Mn |
| Mar 27, 2022 | 14.46 Mn |
| Dec 26, 2021 | 13.49 Mn |
| Sep 26, 2021 | 13.42 Mn |
| Mar 28, 2021 | 14.28 Mn |
1 800 Flowers Com Other 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=other-operating-expenses&ticker=FLWS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "ticker": "FLWS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=other-operating-expenses&ticker=FLWS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();