Dominos Pizza (DPZ) Operating Expenses (2010 - 2026)
Dominos Pizza (DPZ) recorded Operating Expenses of $115.37 million in Q2 2026, up 7.2% from $107.61 million a year earlier and up 3.6% from the prior quarter.
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Analysis
Dominos Pizza (DPZ) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Dominos Pizza's Operating Expenses came in at $474.21 million as of Jun 14, 2026, up 3.3% year-over-year; for FY2025, it came in at $464.12 million, up 1.0% from FY2024.
- Annual Operating Expenses has a four-year compound annual growth rate of 3.4% (FY2021 to FY2025).
- Across earlier years, Operating Expenses came in at $459.49 million in FY2024 (+5.7%), $434.55 million in FY2023, $428.33 million in FY2022 (+5.3%) and $406.61 million in FY2021.
- Quarterly Operating Expenses has ranged from $91.21 million in Q3 2022 to $144.37 million in Q4 2023 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for four consecutive quarters, with growth averaging 2.1% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 18.6% in Q2 2024, against a decline of 7.2% in Q2 2025 at the low end.
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 | Dominos Pizza | 10.07 Bn | 9.40 Bn | 478.23 Mn | 115.37 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 14, 2026 | 115.37 Mn |
| Mar 22, 2026 | 111.41 Mn |
| Dec 28, 2025 | 142.34 Mn |
| Sep 7, 2025 | 105.09 Mn |
| Jun 15, 2025 | 107.61 Mn |
| Mar 23, 2025 | 109.08 Mn |
| Dec 29, 2024 | 138.53 Mn |
| Sep 8, 2024 | 103.99 Mn |
| Jun 16, 2024 | 115.95 Mn |
| Mar 24, 2024 | 101.02 Mn |
| Dec 31, 2023 | 144.37 Mn |
| Sep 10, 2023 | 97.20 Mn |
| Jun 18, 2023 | 97.79 Mn |
| Mar 26, 2023 | 95.19 Mn |
| Jan 1, 2023 | 130.76 Mn |
| Sep 11, 2022 | 91.21 Mn |
| Jun 19, 2022 | 97.07 Mn |
| Mar 27, 2022 | 97.49 Mn |
| Sep 12, 2021 | 96.34 Mn |
| Jun 20, 2021 | 100.45 Mn |
API Access
Dominos Pizza 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=DPZ&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DPZ", "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=DPZ&period=max&api_key=YOUR_API_KEY");
const data = await res.json();