Shake Shack (SHAK) Operating Expenses (2014 - 2026)
Shake Shack (SHAK) recorded Operating Expenses of $396.87 million in Q2 2026, up 18.8% from $334.09 million a year earlier and up 7.4% from the prior quarter.
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Analysis
Shake Shack (SHAK) Operating Expenses (2014 - 2026) Analysis & Trends
On a TTM basis, Shake Shack's Operating Expenses came in at $1.5 billion as of Jul 1, 2026, up 14.7% year-over-year; for FY2025, it was $1.38 billion, up 10.7% from FY2024.
- Annual Operating Expenses has increased for five straight years, with a five-year compound annual growth rate of 19.5% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $1.25 billion in FY2024 (+15.5%), $1.08 billion in FY2023 (+16.6%), $927.38 million in FY2022 (+22.7%) and $755.75 million in FY2021 (+33.3%).
- The Q2 2026 figure is the highest quarterly Operating Expenses in data going back to Q1 2014.
- On a year-over-year basis, Operating Expenses has increased for 23 consecutive quarters, with growth averaging 14.0% over the last eight quarters.
- The year-over-year growth in Operating Expenses has ranged between 4.2% (Q3 2025) and 43.3% (Q3 2021) over the last five years.
- Per Business Quant, the preceding three quarters came in at $369.37 million (Q1 2026), $381.79 million (Q4 2025) and $348.86 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 171.96 Bn | 166.78 Bn | 6.42 Bn | 3.76 Bn |
| 2 | Starbucks | 110.34 Bn | 97.96 Bn | - | 8.42 Bn |
| 3 | Yum Brands | 41.48 Bn | 38.36 Bn | 1.47 Bn | 1.51 Bn |
| 4 | Chipotle Mexican Grill | 39.00 Bn | 34.98 Bn | - | 2.82 Bn |
| 5 | Restaurant Brands International | 25.80 Bn | 21.35 Bn | 1.38 Bn | 1.80 Bn |
| 6 | Darden Restaurants | 24.38 Bn | 23.48 Bn | 1.68 Bn | 2.88 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 1.80 Bn |
| 8 | Yum China Holdings | 15.57 Bn | 9.23 Bn | 537.00 Mn | 2.79 Bn |
| 9 | Texas Roadhouse | 11.21 Bn | 10.55 Bn | - | 1.54 Bn |
| 10 | Shake Shack | 2.84 Bn | 1.50 Bn | - | 396.87 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 1, 2026 | 396.87 Mn |
| Apr 1, 2026 | 369.37 Mn |
| Dec 31, 2025 | 381.79 Mn |
| Sep 24, 2025 | 348.86 Mn |
| Jun 25, 2025 | 334.09 Mn |
| Mar 26, 2025 | 318.06 Mn |
| Dec 25, 2024 | 318.47 Mn |
| Sep 25, 2024 | 334.91 Mn |
| Jun 26, 2024 | 305.71 Mn |
| Mar 27, 2024 | 290.47 Mn |
| Dec 27, 2023 | 287.54 Mn |
| Sep 27, 2023 | 270.55 Mn |
| Jun 28, 2023 | 267.06 Mn |
| Mar 29, 2023 | 256.47 Mn |
| Dec 28, 2022 | 244.84 Mn |
| Sep 28, 2022 | 232.64 Mn |
| Jun 29, 2022 | 231.57 Mn |
| Mar 30, 2022 | 218.33 Mn |
| Dec 29, 2021 | 209.75 Mn |
| Sep 29, 2021 | 196.54 Mn |
API Access
Shake Shack 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=SHAK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SHAK", "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=SHAK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();