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SYSCO CORP: operating income or loss

Operating income or loss for SYSCO CORP. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All SYSCO CORP financial histories

What this measure means

Operating revenue less operating expenses for the reporting period. It excludes items outside the reported operating result and is not free cash flow.

Exact concept: us-gaap:OperatingIncomeLoss. 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 2007-07-01 to 2026-06-27. The SEC response was captured on 2026-09-19.

Selected filing history

Operating income or loss in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-06-292026-06-273,095,000,000USD2026-08-2110-K · 0000096021-26-000033
2024-06-302025-06-283,088,000,000USD2026-08-2110-K · 0000096021-26-000033
2023-07-022024-06-293,202,000,000USD2026-08-2110-K · 0000096021-26-000033
2022-07-032023-07-013,039,000,000USD2025-08-2210-K · 0000096021-25-000099
2021-07-042022-07-022,346,000,000USD2024-08-2810-K · 0000096021-24-000128
2020-06-282021-07-031,447,188,000USD2023-08-2510-K · 0000096021-23-000117
2019-06-302020-06-27749,505,000USD2022-08-2610-K · 0000096021-22-000151
2018-07-012019-06-292,330,150,000USD2021-08-3010-K · 0000096021-21-000093
2017-07-022018-06-302,314,056,000USD2020-08-2610-K · 0000096021-20-000100
2016-07-032017-07-012,054,616,000USD2019-08-2610-K · 0000096021-19-000093
2015-06-282016-07-021,850,500,000USD2018-08-2710-K · 0000096021-18-000126
2014-06-292015-06-271,229,362,000USD2017-08-3010-K · 0000096021-17-000120
2013-06-302014-06-281,587,122,000USD2016-08-3010-K · 0000096021-16-000275
2012-07-012013-06-291,658,478,000USD2015-08-2510-K · 0000096021-15-000057
2011-07-032012-06-301,890,632,000USD2014-08-2610-K · 0000096021-14-000040
2010-07-042011-07-021,931,502,000USD2013-08-2710-K · 0000096021-13-000073
2009-06-282010-07-031,975,868,000USD2012-08-2810-K · 0000096021-12-000062
2008-06-292009-06-271,872,211,000USD2011-08-3010-K · 0000950123-11-081150
2007-07-012008-06-281,879,949,000USD2010-08-3110-K · 0000950123-10-082514

Related financial histories

Inspect the source

Entity
SYSCO CORP / CIK 0000096021
Captured
2026-09-19T14:53:07.509Z
SEC response SHA-256
7358a5dbcdd4e5fb99b84e4ce7221b2e96c698b58560a4b9a676b1fc7933d824

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/0000096021.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"])))