Iron Mountain (IRM) Change in Accured Expenses (2009 - 2026)
Iron Mountain's Change in Accured Expenses came in at $183.83 million for Q2 2026, up 29.7% from $141.7 million a year earlier.
Iron Mountain (IRM) Change in Accured Expenses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Iron Mountain reported Change in Accured Expenses of $224.69 million, up 88.3% year-over-year; for FY2025, it was $202.12 million.
- Change in Accured Expenses carries a five-year compound annual growth rate of 6.2% (FY2020 to FY2025).
- Going back by year, Change in Accured Expenses was $5.88 million in FY2024 (-80.2%), $29.69 million in FY2023, -$27.8 million in FY2022 and $42.54 million in FY2021 (-71.6%).
- The five-year range for quarterly Change in Accured Expenses is -$148.65 million (Q3 2021) to $229.76 million (Q4 2023).
- Year-over-year, Change in Accured Expenses increased in three of the last four quarters, with growth averaging 13.0%.
- The fastest year-over-year change in Change in Accured Expenses over five years came in Q2 2024 (growth of 497.1%), and the weakest in Q2 2023 (a decline of 75.8%).
- Business Quant data shows IRM's Change in Accured Expenses at -$69.55 million (Q1 2026), $205.13 million (Q4 2025) and -$94.71 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 132.79 Bn | 93.20 Bn | 6.13 Bn | 967.46 Mn |
| 2 | Cintas | 77.24 Bn | 76.43 Bn | 1.48 Bn | 60.14 Mn |
| 3 | Iron Mountain | 33.76 Bn | 33.28 Bn | 1.07 Bn | 183.83 Mn |
| 4 | APi | 17.50 Bn | 14.54 Bn | 703.00 Mn | - |
| 5 | Aramark | 14.64 Bn | 12.66 Bn | 430.34 Mn | -6.96 Mn |
| 6 | Rollins | 14.51 Bn | 14.06 Bn | 569.95 Mn | 81.49 Mn |
| 7 | UL Solutions | 13.33 Bn | 12.11 Bn | 417.00 Mn | 83.00 Mn |
| 8 | Gartner | 11.67 Bn | 5.36 Bn | 1.19 Bn | 53.59 Mn |
| 9 | Rentokil Initial | 10.08 Bn | 3.42 Bn | - | - |
| 10 | Tetra Tech | 8.48 Bn | 7.59 Bn | 243.21 Mn | 70.88 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 183.83 Mn |
| Mar 31, 2026 | -69.55 Mn |
| Dec 31, 2025 | 205.13 Mn |
| Sep 30, 2025 | -94.71 Mn |
| Jun 30, 2025 | 141.70 Mn |
| Mar 31, 2025 | -49.99 Mn |
| Dec 31, 2024 | 140.98 Mn |
| Sep 30, 2024 | -113.37 Mn |
| Jun 30, 2024 | 122.96 Mn |
| Mar 31, 2024 | -144.69 Mn |
| Dec 31, 2023 | 229.76 Mn |
| Sep 30, 2023 | -91.21 Mn |
| Jun 30, 2023 | 20.59 Mn |
| Mar 31, 2023 | -129.45 Mn |
| Dec 31, 2022 | 111.34 Mn |
| Sep 30, 2022 | -88.63 Mn |
| Jun 30, 2022 | 85.19 Mn |
| Mar 31, 2022 | -135.69 Mn |
| Dec 31, 2021 | 138.96 Mn |
| Sep 30, 2021 | -148.65 Mn |
Iron Mountain 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=IRM&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "IRM", "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=IRM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();