Dine Brands Global (DIN) Property, Plant & Equipment (Net) (2010 - 2026)
Dine Brands Global (DIN) posted Property, Plant & Equipment (Net) of $173.4 million for Q2 2026, up 4.9% from the prior quarter.
Dine Brands Global (DIN) Property, Plant & Equipment (Net) (2010 - 2026) Analysis & Trends
At the end of FY2025, Dine Brands Global's Property, Plant & Equipment (Net) came in at $160.5 million, up 2.8% from FY2024.
- Annual Property, Plant & Equipment (Net) shows a five-year compound annual growth rate of -3.1% (FY2020 to FY2025).
- In prior years, Dine Brands Global's Property, Plant & Equipment (Net) was $156.1 million in FY2024 (-3.6%), $161.9 million in FY2023 (+11.4%), $145.3 million in FY2022 (-19.0%) and $179.41 million in FY2021 (-4.6%).
- The Q2 2026 figure stands as the highest quarterly Property, Plant & Equipment (Net) since Q2 2022.
- On a year-over-year basis, Property, Plant & Equipment (Net) increased in two of the last four quarters, with an average decline of 1.3%.
- The strongest year-over-year quarter for Property, Plant & Equipment (Net) in the past five years was Q3 2023, with growth of 19.7%; the weakest was Q3 2022, with a decline of 22.8%.
- According to Business Quant data, Property, Plant & Equipment (Net) for the three prior quarters was $165.3 million (Q1 2026), $160.5 million (Q4 2025) and $155.17 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | PP&E (Net) (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 164.13 Bn | 158.95 Bn | 6.42 Bn | 28.48 Bn |
| 2 | Starbucks | 107.97 Bn | 95.60 Bn | - | 6.99 Bn |
| 3 | Chipotle Mexican Grill | 41.04 Bn | 37.02 Bn | - | 2.87 Bn |
| 4 | Yum Brands | 37.16 Bn | 34.04 Bn | 1.47 Bn | 1.61 Bn |
| 5 | Restaurant Brands International | 24.42 Bn | 21.52 Bn | 1.38 Bn | 2.23 Bn |
| 6 | Darden Restaurants | 22.67 Bn | 21.77 Bn | 1.68 Bn | 5.12 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 2.23 Bn |
| 8 | Yum China Holdings | 13.79 Bn | 8.16 Bn | 537.00 Mn | 2.62 Bn |
| 9 | Texas Roadhouse | 10.24 Bn | 9.60 Bn | - | 1.89 Bn |
| 10 | Dine Brands Global | 379.50 Mn | -118.40 Mn | 91.20 Mn | 173.40 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 173.40 Mn |
| Mar 29, 2026 | 165.30 Mn |
| Dec 28, 2025 | 160.50 Mn |
| Sep 30, 2025 | 155.17 Mn |
| Dec 29, 2024 | 156.10 Mn |
| Sep 30, 2024 | 154.93 Mn |
| Jun 30, 2024 | 158.10 Mn |
| Mar 31, 2024 | 159.71 Mn |
| Dec 31, 2023 | 161.90 Mn |
| Sep 30, 2023 | 162.06 Mn |
| Jun 30, 2023 | 157.51 Mn |
| Mar 31, 2023 | 158.72 Mn |
| Dec 31, 2022 | 145.30 Mn |
| Sep 30, 2022 | 135.37 Mn |
| Jun 30, 2022 | 175.27 Mn |
| Mar 31, 2022 | 175.52 Mn |
| Dec 31, 2021 | 179.41 Mn |
| Sep 30, 2021 | 175.32 Mn |
| Jun 30, 2021 | 178.57 Mn |
| Mar 31, 2021 | 182.66 Mn |
Dine Brands Global Property, Plant & Equipment (Net) 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=property-plant-and-equipment-net&ticker=DIN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "property-plant-and-equipment-net", "ticker": "DIN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=property-plant-and-equipment-net&ticker=DIN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();