Everpure (P) Operating Expenses (2014 - 2026)
Everpure's Operating Expenses was $748.23 million in fiscal Q2 2027 (quarter ended Aug 2, 2026), up 24.8% from $599.47 million a year earlier and up 6.4% from the prior quarter.
Everpure (P) Operating Expenses (2014 - 2026) Analysis & Trends
On a trailing twelve-month basis, Everpure's Operating Expenses was $2.75 billion through Aug 2, 2026, up 22.6% year-over-year; for FY2026 (ended Feb 1, 2026), it came in at $2.46 billion, up 15.8% from FY2025.
- Operating Expenses has now increased for 12 consecutive fiscal years, with a five-year compound annual growth rate of 11.8% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $2.13 billion in FY2025 (+8.1%), $1.97 billion in FY2024 (+8.5%), $1.81 billion in FY2023 (+15.5%) and $1.57 billion in FY2022 (+11.4%).
- The fiscal Q2 2027 figure marks the highest quarterly Operating Expenses in data going back to fiscal Q3 2015.
- Compared with a year earlier, Operating Expenses has increased for 44 straight quarters, with growth averaging 16.2% over the last eight quarters.
- The year-over-year growth in Operating Expenses has ranged between 2.9% (fiscal Q4 2024) and 24.8% (fiscal Q2 2027) over the last five years.
- Per Business Quant data, P's Operating Expenses in the three fiscal quarters before Q2 2027 was $703.39 million (Q1 2027), $652.89 million (Q4 2026) and $643.46 million (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Apple | 5,059.58 Bn | 4,807.07 Bn | 54.77 Bn | 19.08 Bn |
| 2 | Cisco Systems | 451.20 Bn | 387.12 Bn | 11.06 Bn | 6.80 Bn |
| 3 | Dell Technologies | 365.27 Bn | 321.03 Bn | 9.83 Bn | 4.45 Bn |
| 4 | Arista Networks | 251.01 Bn | 204.46 Bn | 1.91 Bn | 532.30 Mn |
| 5 | Sandisk | 211.16 Bn | 199.69 Bn | 7.58 Bn | 545.00 Mn |
| 6 | Seagate Technology Holdings | 159.53 Bn | 154.52 Bn | 1.90 Bn | 2.07 Bn |
| 7 | Sony | 145.60 Bn | 82.87 Bn | 6.53 Bn | 14.83 Bn |
| 8 | Western Digital | 128.87 Bn | 117.00 Bn | 2.03 Bn | 465.00 Mn |
| 9 | Hewlett Packard Enterprise | 91.88 Bn | 69.75 Bn | 4.93 Bn | 10.82 Bn |
| 10 | Everpure | 50.56 Bn | 44.97 Bn | 811.39 Mn | 748.23 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 2, 2026 | 748.23 Mn |
| May 3, 2026 | 703.39 Mn |
| Feb 1, 2026 | 652.89 Mn |
| Nov 2, 2025 | 643.46 Mn |
| Aug 3, 2025 | 599.47 Mn |
| May 4, 2025 | 567.32 Mn |
| Feb 2, 2025 | 551.53 Mn |
| Nov 3, 2024 | 523.24 Mn |
| Aug 4, 2024 | 515.20 Mn |
| May 5, 2024 | 537.48 Mn |
| Feb 4, 2024 | 511.12 Mn |
| Nov 5, 2023 | 478.54 Mn |
| Aug 6, 2023 | 492.82 Mn |
| May 7, 2023 | 485.16 Mn |
| Feb 5, 2023 | 496.73 Mn |
| Nov 6, 2022 | 457.20 Mn |
| Aug 7, 2022 | 429.21 Mn |
| May 8, 2022 | 430.99 Mn |
| Feb 6, 2022 | 446.07 Mn |
| Oct 31, 2021 | 392.87 Mn |
Everpure 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=P&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "P", "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=P&period=max&api_key=YOUR_API_KEY");
const data = await res.json();