Flowers Foods (FLO) Restructuring Costs (2017 - 2025)
Flowers Foods' Restructuring Costs came in at $6.08 million for FY2026.
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Analysis
Flowers Foods (FLO) Restructuring Costs (2017 - 2025) Analysis & Trends
Going back to FY2017, Flowers Foods' Restructuring Costs data covers 7 years.
- Restructuring Costs carries a five-year compound annual growth rate of -29.7% (FY2021 to FY2026).
- The FY2026 figure represents the lowest annual Restructuring Costs in data going back to FY2017.
- Per Business Quant, earlier years put Restructuring Costs at $7.4 million in FY2024 (+4.3%) and $7.1 million in FY2023.
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 |
|---|---|
| Oct 4, 2025 | 5.51 Mn |
| Apr 19, 2025 | 573,000.00 |
| Jul 13, 2024 | 6.81 Mn |
| Apr 20, 2024 | 598,000.00 |
| Dec 30, 2023 | 226,000.00 |
| Oct 7, 2023 | 179,000.00 |
| Jul 15, 2023 | 2.50 Mn |
| Apr 22, 2023 | 4.20 Mn |
| Jan 2, 2021 | 4.85 Mn |
| Oct 3, 2020 | 20.10 Mn |
| Jul 11, 2020 | 10.54 Mn |
| Dec 28, 2019 | 17.48 Mn |
| Oct 5, 2019 | 3.28 Mn |
| Jul 13, 2019 | 2.05 Mn |
| Apr 20, 2019 | 718,000.00 |
| Dec 29, 2018 | 7.21 Mn |
| Oct 6, 2018 | 497,000.00 |
| Jul 14, 2018 | 801,000.00 |
| Apr 21, 2018 | 1.26 Mn |
| Dec 30, 2017 | 3.58 Mn |
API Access
Flowers Foods Restructuring Costs 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=restructuring-costs&ticker=FLO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "restructuring-costs", "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=restructuring-costs&ticker=FLO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();