Columbus Mckinnon (CMCO) Accumulated Expenses (2011 - 2026)
Columbus Mckinnon's Accumulated Expenses was $247.96 million in fiscal Q1 2027 (quarter ended Jun 30, 2026), up 103.6% from $121.77 million a year earlier but down 0.4% from the prior quarter.
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Analysis
Columbus Mckinnon (CMCO) Accumulated Expenses (2011 - 2026) Analysis & Trends
At the end of FY2026 (ended Mar 31, 2026), Accumulated Expenses at Columbus Mckinnon came in at $249.01 million, up 118.6% from FY2025.
- Accumulated Expenses shows a five-year compound annual growth rate of 17.6% (FY2021 to FY2026).
- In earlier fiscal years, Accumulated Expenses was $113.91 million in FY2025 (-11.0%), $127.97 million in FY2024 (+2.9%), $124.32 million in FY2023 (+5.2%) and $118.19 million in FY2022 (+6.7%).
- Quarterly Accumulated Expenses has moved between $93.6 million (fiscal Q3 2025) and $249.01 million (fiscal Q4 2026) over five years.
- Compared with a year earlier, Accumulated Expenses has increased for five straight quarters, with growth averaging 25.9% over the last eight quarters.
- The best year-over-year quarter for Accumulated Expenses over five years was fiscal Q4 2026 (growth of 118.6%); the worst was fiscal Q3 2025 (a decline of 34.3%).
- Per Business Quant data, CMCO's Accumulated Expenses in the three fiscal quarters before Q1 2027 was $249.01 million (Q4 2026), $121.48 million (Q3 2026) and $119.09 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Caterpillar | 372.79 Bn | 344.49 Bn | 7.76 Bn |
| 2 | Amphenol | 207.98 Bn | 202.68 Bn | 3.55 Bn |
| 3 | Deere | 181.02 Bn | 189.78 Bn | 4.66 Bn |
| 4 | Eaton | 166.86 Bn | 164.09 Bn | 2.86 Bn |
| 5 | Parker-Hannifin | 120.45 Bn | 118.58 Bn | 2.25 Bn |
| 6 | Vertiv Holdings | 92.94 Bn | 83.56 Bn | 1.23 Bn |
| 7 | Emerson Electric | 86.56 Bn | 79.32 Bn | 2.66 Bn |
| 8 | 3M | 84.72 Bn | 66.18 Bn | 2.68 Bn |
| 9 | Illinois Tool Works | 73.32 Bn | 69.88 Bn | 1.90 Bn |
| 10 | Columbus Mckinnon | 459.32 Mn | 200.43 Mn | 146.27 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 247.96 Mn |
| Mar 31, 2026 | 249.01 Mn |
| Dec 31, 2025 | 121.48 Mn |
| Sep 30, 2025 | 119.09 Mn |
| Jun 30, 2025 | 121.77 Mn |
| Mar 31, 2025 | 113.91 Mn |
| Dec 31, 2024 | 93.60 Mn |
| Sep 30, 2024 | 106.85 Mn |
| Jun 30, 2024 | 107.59 Mn |
| Mar 31, 2024 | 127.97 Mn |
| Dec 31, 2023 | 142.52 Mn |
| Sep 30, 2023 | 141.53 Mn |
| Jun 30, 2023 | 145.93 Mn |
| Mar 31, 2023 | 124.32 Mn |
| Dec 31, 2022 | 104.23 Mn |
| Sep 30, 2022 | 104.84 Mn |
| Jun 30, 2022 | 104.82 Mn |
| Mar 31, 2022 | 118.19 Mn |
| Dec 31, 2021 | 116.41 Mn |
| Sep 30, 2021 | 104.92 Mn |
API Access
Columbus Mckinnon Accumulated 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=accumulated-expenses&ticker=CMCO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "CMCO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=CMCO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();