1 800 Flowers Com (FLWS) Operating Leases (2019 - 2026)
1 800 Flowers Com's Operating Leases was $95.47 million in fiscal Q4 2026 (quarter ended Jun 28, 2026), down 4.2% from $99.64 million a year earlier but up 2.2% from the prior quarter.
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Analysis
1 800 Flowers Com (FLWS) Operating Leases (2019 - 2026) Analysis & Trends
From fiscal Q1 2020 onward, 1 800 Flowers Com has reported Operating Leases for 23 quarters.
- Operating Leases has now declined for four consecutive fiscal years, though with a five-year compound annual growth rate of 3.8% (FY2021 to FY2026).
- In earlier fiscal years, Operating Leases was $99.64 million in FY2025 (-5.9%), $105.87 million in FY2024 (-9.8%), $117.33 million in FY2023 (-5.1%) and $123.66 million in FY2022 (+55.8%).
- Quarterly Operating Leases has moved between $93.37 million (fiscal Q3 2026) and $128.62 million (fiscal Q1 2022) over five years.
- Compared with a year earlier, Operating Leases has declined for 11 straight quarters, with an average decline of 7.0% over the last eight quarters.
- The best year-over-year quarter for Operating Leases over five years was fiscal Q4 2022 (growth of 55.8%); the worst was fiscal Q3 2024 (a decline of 11.2%).
- Per Business Quant data, FLWS's Operating Leases in the three fiscal quarters before Q4 2026 was $93.37 million (Q3 2026), $93.55 million (Q2 2026) and $96.4 million (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Amazon Com | 2,659.84 Bn | 2,176.54 Bn | 104.83 Bn |
| 2 | Home Depot | 287.59 Bn | 280.83 Bn | 16.12 Bn |
| 3 | Tjx Companies | 147.38 Bn | 124.93 Bn | 5.07 Bn |
| 4 | Lowes Companies | 105.03 Bn | 97.99 Bn | 8.58 Bn |
| 5 | Ross Stores | 74.93 Bn | 57.86 Bn | 2.12 Bn |
| 6 | Target | 71.05 Bn | 65.64 Bn | 8.94 Bn |
| 7 | O Reilly Automotive | 70.25 Bn | 69.33 Bn | 2.52 Bn |
| 8 | Carvana | 69.96 Bn | 61.56 Bn | 1.38 Bn |
| 9 | Autozone | 46.92 Bn | 45.82 Bn | 2.52 Bn |
| 10 | 1 800 Flowers Com | 166.17 Mn | -96.98 Mn | 101.81 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 95.47 Mn |
| Mar 29, 2026 | 93.37 Mn |
| Dec 28, 2025 | 93.55 Mn |
| Sep 28, 2025 | 96.40 Mn |
| Jun 29, 2025 | 99.64 Mn |
| Mar 30, 2025 | 103.74 Mn |
| Dec 29, 2024 | 102.04 Mn |
| Sep 29, 2024 | 104.40 Mn |
| Jun 30, 2024 | 105.87 Mn |
| Mar 31, 2024 | 107.92 Mn |
| Dec 31, 2023 | 110.74 Mn |
| Oct 1, 2023 | 113.28 Mn |
| Jul 2, 2023 | 117.33 Mn |
| Apr 2, 2023 | 121.57 Mn |
| Jan 1, 2023 | 124.73 Mn |
| Oct 2, 2022 | 128.52 Mn |
| Jul 3, 2022 | 123.66 Mn |
| Mar 27, 2022 | 125.83 Mn |
| Dec 26, 2021 | 128.62 Mn |
| Sep 26, 2021 | 107.53 Mn |
API Access
1 800 Flowers Com Operating Leases 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-leases&ticker=FLWS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-leases", "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=operating-leases&ticker=FLWS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();