Ranpak Holdings (PACK) Operating Expenses (2017 - 2026)
Ranpak Holdings (PACK) recorded Operating Expenses of $36.2 million in Q2 2026, down 6.0% from $38.5 million a year earlier and down 6.7% from the prior quarter.
Ranpak Holdings (PACK) Operating Expenses (2017 - 2026) Analysis & Trends
On a TTM basis, Ranpak Holdings' Operating Expenses came in at $152.2 million as of Jun 30, 2026, up 3.4% year-over-year; for FY2025, it came in at $152.4 million, up 2.8% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 7.0% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $148.2 million in FY2024 (+12.3%), $132 million in FY2023 (-9.4%), $145.7 million in FY2022 (+2.3%) and $142.4 million in FY2021 (+31.0%).
- The Q2 2026 figure is the lowest quarterly Operating Expenses since Q3 2024.
- On a year-over-year basis, Operating Expenses rose in five of the last eight quarters, with growth averaging 2.7%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 45.1% in Q3 2021, against a decline of 37.2% in Q2 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $38.8 million (Q1 2026), $37 million (Q4 2025) and $40.2 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Smurfit Westrock | 21.44 Bn | 18.34 Bn | 1.40 Bn | 1.09 Bn |
| 2 | Packaging Corp Of America | 20.96 Bn | 18.50 Bn | 512.50 Mn | 179.30 Mn |
| 3 | Amcor | 20.41 Bn | 15.82 Bn | 1.34 Bn | 646.00 Mn |
| 4 | International Paper | 17.90 Bn | 13.80 Bn | 1.66 Bn | 991.00 Mn |
| 5 | Ball | 17.00 Bn | 14.00 Bn | 697.00 Mn | 312.00 Mn |
| 6 | Crown Holdings | 12.59 Bn | 9.41 Bn | 748.00 Mn | 249.00 Mn |
| 7 | Sonoco Products | 4.96 Bn | 3.94 Bn | 392.38 Mn | 202.18 Mn |
| 8 | Silgan Holdings | 4.24 Bn | 1.98 Bn | 294.88 Mn | 144.94 Mn |
| 9 | Ardagh Metal Packaging | 2.76 Bn | -316,998.09 Bn | 238.00 Mn | 87.00 Mn |
| 10 | Ranpak Holdings | 292.18 Mn | 87.58 Mn | 34.50 Mn | 36.20 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 36.20 Mn |
| Mar 31, 2026 | 38.80 Mn |
| Dec 31, 2025 | 37.00 Mn |
| Sep 30, 2025 | 40.20 Mn |
| Jun 30, 2025 | 38.50 Mn |
| Mar 31, 2025 | 36.70 Mn |
| Dec 31, 2024 | 36.60 Mn |
| Sep 30, 2024 | 35.40 Mn |
| Jun 30, 2024 | 36.70 Mn |
| Mar 31, 2024 | 39.50 Mn |
| Dec 31, 2023 | 39.90 Mn |
| Sep 30, 2023 | 30.10 Mn |
| Jun 30, 2023 | 25.70 Mn |
| Mar 31, 2023 | 36.30 Mn |
| Dec 31, 2022 | 27.80 Mn |
| Sep 30, 2022 | 35.80 Mn |
| Jun 30, 2022 | 40.90 Mn |
| Mar 31, 2022 | 41.20 Mn |
| Dec 31, 2021 | 39.20 Mn |
| Sep 30, 2021 | 38.30 Mn |
Ranpak Holdings 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=PACK&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PACK", "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=PACK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();