Sysco (SYY) Operating Expenses (2009 - 2026)
Sysco's Operating Expenses was $3.15 billion in fiscal Q4 2026 (quarter ended Jun 27, 2026), up 1.7% from $3.1 billion a year earlier but down 1.3% from the prior quarter.
Sysco (SYY) Operating Expenses (2009 - 2026) Analysis & Trends
For FY2026 (ended Jun 27, 2026), Operating Expenses at Sysco came in at $12.54 billion, up 5.6% from FY2025.
- Operating Expenses has now increased for five consecutive fiscal years, with a five-year compound annual growth rate of 9.7% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $11.88 billion in FY2025 (+4.2%), $11.41 billion in FY2024 (+4.5%), $10.92 billion in FY2023 (+9.4%) and $9.97 billion in FY2022 (+26.1%).
- Quarterly Operating Expenses has moved between $2.34 billion (fiscal Q1 2022) and $3.19 billion (fiscal Q3 2026) over five years.
- Compared with a year earlier, Operating Expenses has increased for 21 straight quarters, with growth averaging 4.9% over the last eight quarters.
- The year-over-year growth in Operating Expenses has ranged between 0.5% (fiscal Q3 2025) and 33.4% (fiscal Q3 2022) over the last five years.
- Per Business Quant data, SYY's Operating Expenses in the three fiscal quarters before Q4 2026 was $3.19 billion (Q3 2026), $3.1 billion (Q2 2026) and $3.1 billion (Q1 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 847.32 Bn | 810.03 Bn | 49.13 Bn | 39.75 Bn |
| 2 | Costco Wholesale | 410.07 Bn | 339.37 Bn | 9.01 Bn | 6.19 Bn |
| 3 | Sysco | 37.60 Bn | 31.85 Bn | 4.13 Bn | 3.15 Bn |
| 4 | Kroger | 35.90 Bn | 22.05 Bn | 7.86 Bn | 198.00 Mn |
| 5 | Dollar General | 27.06 Bn | 21.73 Bn | 3.68 Bn | 2.91 Bn |
| 6 | Caseys General Stores | 22.17 Bn | 20.17 Bn | 1.24 Bn | 754.11 Mn |
| 7 | Dollar Tree | 21.26 Bn | 17.89 Bn | 2.10 Bn | 1.43 Bn |
| 8 | US Foods Holding | 20.27 Bn | 20.07 Bn | 1.92 Bn | 1.48 Bn |
| 9 | Tractor Supply | 16.44 Bn | 15.61 Bn | 1.68 Bn | 1.02 Bn |
| 10 | Performance Food | 14.36 Bn | 14.14 Bn | 2.17 Bn | 1.85 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 3.15 Bn |
| Mar 28, 2026 | 3.19 Bn |
| Dec 27, 2025 | 3.10 Bn |
| Sep 27, 2025 | 3.10 Bn |
| Jun 28, 2025 | 3.10 Bn |
| Mar 29, 2025 | 2.90 Bn |
| Dec 28, 2024 | 2.94 Bn |
| Sep 28, 2024 | 2.95 Bn |
| Jun 29, 2024 | 2.86 Bn |
| Mar 30, 2024 | 2.89 Bn |
| Dec 30, 2023 | 2.81 Bn |
| Sep 30, 2023 | 2.84 Bn |
| Jul 1, 2023 | 2.72 Bn |
| Apr 1, 2023 | 2.74 Bn |
| Dec 31, 2022 | 2.71 Bn |
| Oct 1, 2022 | 2.75 Bn |
| Jul 2, 2022 | 2.68 Bn |
| Apr 2, 2022 | 2.52 Bn |
| Jan 2, 2022 | 2.45 Bn |
| Oct 2, 2021 | 2.34 Bn |
Sysco Operating 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=operating-expenses&ticker=SYY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SYY", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=SYY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();