General Mills (GIS) Operating Expenses (2009 - 2026)
General Mills (GIS) recorded Operating Expenses of $853.6 million in fiscal Q1 2027 (quarter ended Aug 30, 2026), down 0.9% from $861.4 million a year earlier and down 76.9% from the prior quarter.
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Analysis
General Mills (GIS) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, General Mills' Operating Expenses came in at $6.35 billion as of Aug 30, 2026, up 80.0% year-over-year; for FY2026 (ended May 31, 2026), it came in at $6.36 billion, up 80.5% from FY2025.
- Annual Operating Expenses has a five-year compound annual growth rate of 14.4% (FY2021 to FY2026).
- Across earlier fiscal years, Operating Expenses came in at $3.52 billion in FY2025 (+0.7%), $3.5 billion in FY2024 (-1.6%), $3.56 billion in FY2023 (+14.0%) and $3.12 billion in FY2022 (-4.0%).
- Quarterly Operating Expenses has ranged from $758.5 million in fiscal Q3 2022 to $3.7 billion in fiscal Q4 2026 over the past five years.
- On a year-over-year basis, Operating Expenses rose in five of the last eight quarters, with growth averaging 36.9%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 281.0% in fiscal Q4 2026, against a decline of 20.8% in fiscal Q4 2022 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $3.7 billion (Q4 2026), $837.3 million (Q3 2026) and $964.5 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Unilever | 133.59 Bn | 108.95 Bn | - | - |
| 2 | Mondelez International | 75.71 Bn | 69.03 Bn | 3.99 Bn | 2.01 Bn |
| 3 | Hershey | 32.64 Bn | 28.88 Bn | 1.26 Bn | 628.91 Mn |
| 4 | Kraft Heinz | 27.82 Bn | 14.35 Bn | 2.03 Bn | 8.46 Bn |
| 5 | General Mills | 18.09 Bn | 15.75 Bn | 1.49 Bn | 853.60 Mn |
| 6 | Mccormick | 13.03 Bn | 12.90 Bn | 778.20 Mn | 441.80 Mn |
| 7 | J M Smucker | 12.89 Bn | 12.68 Bn | 979.60 Mn | 411.10 Mn |
| 8 | Hormel Foods | 10.92 Bn | 7.61 Bn | 471.52 Mn | 323.50 Mn |
| 9 | Chewy | 7.33 Bn | 4.62 Bn | 1.01 Bn | 919.20 Mn |
| 10 | Conagra Brands | 6.75 Bn | 5.73 Bn | 704.10 Mn | 401.10 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 30, 2026 | 853.60 Mn |
| May 31, 2026 | 3.70 Bn |
| Feb 22, 2026 | 837.30 Mn |
| Nov 23, 2025 | 964.50 Mn |
| Aug 24, 2025 | 861.40 Mn |
| May 25, 2025 | 970.00 Mn |
| Feb 23, 2025 | 843.60 Mn |
| Nov 24, 2024 | 853.20 Mn |
| Aug 25, 2024 | 857.30 Mn |
| May 26, 2024 | 909.10 Mn |
| Feb 25, 2024 | 796.70 Mn |
| Nov 26, 2023 | 954.10 Mn |
| Aug 27, 2023 | 840.50 Mn |
| May 28, 2023 | 910.00 Mn |
| Feb 26, 2023 | 948.30 Mn |
| Nov 27, 2022 | 905.30 Mn |
| Aug 28, 2022 | 793.00 Mn |
| May 29, 2022 | 777.80 Mn |
| Feb 27, 2022 | 758.50 Mn |
| Nov 28, 2021 | 831.10 Mn |
API Access
General Mills 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=GIS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GIS", "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=GIS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();