Flowers Foods (FLO) Buildings (2010 - 2026)
Flowers Foods' Buildings was $626.44 million in FY2026.
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Analysis
Flowers Foods (FLO) Buildings (2010 - 2026) Analysis & Trends
From FY2010 onward, Flowers Foods has reported Buildings for 14 years.
- Buildings shows a five-year compound annual growth rate of 2.6% (FY2021 to FY2026).
- The FY2026 figure marks the highest annual Buildings in data going back to FY2010.
- Per Business Quant data, Buildings in earlier years was $624.34 million in FY2024 (+1.4%), $615.9 million in FY2023 (+11.3%) and $553.61 million in FY2022 (+0.5%).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Unilever | 133.59 Bn | 108.95 Bn | - |
| 2 | Mondelez International | 75.71 Bn | 69.03 Bn | 3.99 Bn |
| 3 | Hershey | 32.64 Bn | 28.88 Bn | 1.26 Bn |
| 4 | Kraft Heinz | 27.82 Bn | 14.35 Bn | 2.03 Bn |
| 5 | General Mills | 18.09 Bn | 15.75 Bn | 1.49 Bn |
| 6 | Mccormick | 13.03 Bn | 12.90 Bn | 778.20 Mn |
| 7 | J M Smucker | 12.89 Bn | 12.68 Bn | 979.60 Mn |
| 8 | Hormel Foods | 10.92 Bn | 7.61 Bn | 471.52 Mn |
| 9 | Chewy | 7.33 Bn | 4.62 Bn | 1.01 Bn |
| 10 | Flowers Foods | 1.21 Bn | 1.11 Bn | 577.93 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jan 3, 2026 | 626.44 Mn |
| Dec 28, 2024 | 624.34 Mn |
| Dec 30, 2023 | 615.90 Mn |
| Dec 31, 2022 | 553.61 Mn |
| Jan 1, 2022 | 550.95 Mn |
| Jan 2, 2021 | 484.81 Mn |
| Dec 28, 2019 | 488.52 Mn |
| Dec 29, 2018 | 483.86 Mn |
| Dec 30, 2017 | 462.66 Mn |
| Dec 31, 2016 | 458.20 Mn |
| Jan 2, 2016 | 455.63 Mn |
| Jan 3, 2015 | 441.44 Mn |
| Dec 28, 2013 | 444.36 Mn |
| Dec 29, 2012 | 378.26 Mn |
| Dec 31, 2011 | 360.96 Mn |
| Jan 1, 2011 | 329.65 Mn |
| Jan 2, 2010 | 323.86 Mn |
API Access
Flowers Foods Buildings 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=buildings&ticker=FLO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "buildings", "ticker": "FLO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=buildings&ticker=FLO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();