Powell Industries (POWL) Change in Accured Expenses (2010 - 2026)
Powell Industries' Change in Accured Expenses was $15.48 million in fiscal Q3 2026 (quarter ended Jun 30, 2026), up 34.6% from $11.5 million a year earlier and up 95.7% from the prior quarter.
Powell Industries (POWL) Change in Accured Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Powell Industries' Change in Accured Expenses was $11.18 million through Jun 30, 2026, up 56.8% year-over-year; for FY2025 (ended Sep 30, 2025), it was $9.73 million, up 94.2% from FY2024.
- Change in Accured Expenses shows a five-year compound annual growth rate of 83.7% (FY2020 to FY2025).
- In earlier fiscal years, Change in Accured Expenses was $5.01 million in FY2024 (-57.3%), $11.73 million in FY2023 (+31.7%), $8.91 million in FY2022 and -$3.15 million in FY2021.
- The fiscal Q3 2026 figure marks the highest quarterly Change in Accured Expenses in data going back to fiscal Q4 2010.
- The best year-over-year quarter for Change in Accured Expenses over five years was fiscal Q2 2022 (growth of 444.8%); the worst was fiscal Q2 2024 (a decline of 47.6%).
- Per Business Quant data, POWL's Change in Accured Expenses in the three fiscal quarters before Q3 2026 was $7.91 million (Q2 2026), -$24.16 million (Q1 2026) and $11.95 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 388.70 Bn | 360.40 Bn | 7.76 Bn | 715.00 Mn |
| 2 | Amphenol | 214.42 Bn | 209.12 Bn | 3.55 Bn | - |
| 3 | Deere | 185.30 Bn | 194.07 Bn | 4.66 Bn | 67.00 Mn |
| 4 | Eaton | 169.35 Bn | 166.59 Bn | 2.86 Bn | - |
| 5 | Parker-Hannifin | 122.64 Bn | 120.77 Bn | 2.25 Bn | - |
| 6 | Vertiv Holdings | 97.12 Bn | 87.74 Bn | 1.23 Bn | 117.60 Mn |
| 7 | Emerson Electric | 90.13 Bn | 82.89 Bn | 2.66 Bn | 191.00 Mn |
| 8 | 3M | 83.49 Bn | 64.94 Bn | 2.68 Bn | - |
| 9 | Illinois Tool Works | 74.89 Bn | 71.45 Bn | 1.90 Bn | 57.00 Mn |
| 10 | Powell Industries | 7.14 Bn | 4.99 Bn | 95.30 Mn | 15.48 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 15.48 Mn |
| Mar 31, 2026 | 7.91 Mn |
| Dec 31, 2025 | -24.16 Mn |
| Sep 30, 2025 | 11.95 Mn |
| Jun 30, 2025 | 11.50 Mn |
| Mar 31, 2025 | 7.08 Mn |
| Dec 31, 2024 | -20.80 Mn |
| Sep 30, 2024 | 9.35 Mn |
| Jun 30, 2024 | 7.12 Mn |
| Mar 31, 2024 | 4.93 Mn |
| Dec 31, 2023 | -16.39 Mn |
| Sep 30, 2023 | 8.20 Mn |
| Jun 30, 2023 | 6.86 Mn |
| Mar 31, 2023 | 9.41 Mn |
| Dec 31, 2022 | -12.74 Mn |
| Sep 30, 2022 | 9.58 Mn |
| Jun 30, 2022 | 5.09 Mn |
| Mar 31, 2022 | 5.27 Mn |
| Dec 31, 2021 | -11.04 Mn |
| Sep 30, 2021 | 3.98 Mn |
Powell Industries Change in Accured 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=change-in-accured-expenses&ticker=POWL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "POWL", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=POWL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();