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FLOWERS FOODS INC: selling, general and administrative expense

Selling, general and administrative expense for FLOWERS FOODS INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All FLOWERS FOODS INC financial histories

What this measure means

Selling and general administrative costs reported under this concept. It is an expense category, not a substitute for total operating expenses.

Exact concept: us-gaap:SellingGeneralAndAdministrativeExpense. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2007-12-30 to 2026-01-03. The SEC response was captured on 2026-09-20.

Selected filing history

Selling, general and administrative expense in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2024-12-292026-01-032,075,368,000USD2026-02-2510-K · 0001193125-26-071441
2023-12-312024-12-282,001,052,000USD2026-02-2510-K · 0001193125-26-071441
2023-01-012023-12-302,119,718,000USD2026-02-2510-K · 0001193125-26-071441
2022-01-022022-12-311,850,594,000USD2025-02-1810-K · 0000950170-25-022243
2021-01-032022-01-011,719,797,000USD2024-02-2110-K · 0000950170-24-017647
2019-12-292021-01-021,693,387,000USD2023-02-2210-K · 0000950170-23-003619
2018-12-302019-12-281,575,122,000USD2022-02-2310-K · 0001564590-22-006065
2017-12-312018-12-291,507,256,000USD2021-02-2410-K · 0001564590-21-007896
2017-01-012017-12-301,510,015,000USD2020-02-1910-K · 0001564590-20-005163
2016-01-032016-12-311,469,382,000USD2019-02-2010-K · 0001564590-19-003388
2015-01-042016-01-021,381,527,000USD2018-02-2110-K · 0001564590-18-002612
2013-12-292015-01-031,368,289,000USD2017-02-2310-K · 0001564590-17-002099
2012-12-302013-12-281,356,742,000USD2016-02-2410-K · 0001564590-16-013151
2012-01-012012-12-291,092,113,000USD2015-02-2510-K · 0001193125-15-061804
2011-01-022011-12-311,016,491,000USD2014-02-1910-K · 0001193125-14-058624
2010-01-032011-01-01935,999,000USD2012-02-2910-K · 0001193125-12-087463
2010-01-012011-01-01935,999,000USD2013-02-2010-K · 0001193125-13-067201
2009-01-042010-01-02926,418,000USD2012-02-2910-K · 0001193125-12-087463
2007-12-302009-01-03894,800,000USD2011-02-2310-K · 0000950123-11-017197

Related financial histories

Inspect the source

Entity
FLOWERS FOODS INC / CIK 0001128928
Captured
2026-09-20T07:40:47.183Z
SEC response SHA-256
c7f2fbdc039de17d69c63c297747bc3291833f1d8cf3dff7b022d2fd13c9d4ca

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001128928.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))