Flowers Foods (FLO) Accumulated Expenses (2009 - 2026)
Flowers Foods (FLO) reported Accumulated Expenses of $65.03 million for Q2 2027, down 0.6% from $65.43 million a year earlier.
Powered by 
Analysis
Flowers Foods (FLO) Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2026, Flowers Foods posted Accumulated Expenses of $59.03 million.
- Accumulated Expenses has a five-year compound annual growth rate of 9.8% (FY2021 to FY2026).
- By year, Accumulated Expenses came in at $41.74 million in FY2024 (-8.3%), $45.52 million in FY2023 (+20.7%) and $37.73 million in FY2022 (+1.9%).
- Five-year quarterly Accumulated Expenses spans a low of $31.73 million in Q3 2022 and a high of $65.43 million in Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Unilever | 144.95 Bn | 98.82 Bn | - |
| 2 | Mondelez International | 84.23 Bn | 77.29 Bn | 3.92 Bn |
| 3 | Hershey | 34.99 Bn | 31.72 Bn | 1.51 Bn |
| 4 | Kraft Heinz | 28.72 Bn | 16.47 Bn | 1.99 Bn |
| 5 | General Mills | 18.50 Bn | 16.16 Bn | 1.49 Bn |
| 6 | J M Smucker | 14.27 Bn | 14.05 Bn | 979.60 Mn |
| 7 | Mccormick | 12.58 Bn | 12.23 Bn | 794.90 Mn |
| 8 | Hormel Foods | 12.22 Bn | 8.90 Bn | 471.52 Mn |
| 9 | Chewy | 9.17 Bn | 6.46 Bn | 1.01 Bn |
| 10 | Flowers Foods | 1.37 Bn | 1.28 Bn | 577.93 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 18, 2026 | 65.03 Mn |
| Oct 4, 2025 | 42.24 Mn |
| Jul 12, 2025 | 65.43 Mn |
| Apr 19, 2025 | 45.60 Mn |
| Dec 28, 2024 | 41.74 Mn |
| Oct 5, 2024 | 36.62 Mn |
| Jul 13, 2024 | 43.34 Mn |
| Apr 20, 2024 | 36.32 Mn |
| Dec 30, 2023 | 45.52 Mn |
| Oct 7, 2023 | 35.96 Mn |
| Jul 15, 2023 | 45.89 Mn |
| Apr 22, 2023 | 33.04 Mn |
| Dec 31, 2022 | 37.73 Mn |
| Oct 8, 2022 | 30.17 Mn |
| Jul 16, 2022 | 38.68 Mn |
| Apr 23, 2022 | 35.10 Mn |
| Oct 9, 2021 | 31.73 Mn |
| Jul 17, 2021 | 38.83 Mn |
| Apr 24, 2021 | 34.24 Mn |
| Oct 3, 2020 | 29.81 Mn |
API Access
Flowers Foods Accumulated 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=accumulated-expenses&ticker=FLO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "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=accumulated-expenses&ticker=FLO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();