Xylem (XYL) Operating Expenses (2010 - 2026)
Xylem's Operating Expenses was $573 million in Q2 2026, down 2.4% from $587 million a year earlier but up 2.5% from the prior quarter.
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Analysis
Xylem (XYL) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Xylem's Operating Expenses was $2.26 billion through Jun 30, 2026, up 1.9% year-over-year; for FY2025, it was $2.25 billion, up 2.2% from FY2024.
- Operating Expenses has now increased for four consecutive years, with a five-year compound annual growth rate of 9.9% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $2.2 billion in FY2024 (+6.7%), $2.07 billion in FY2023 (+41.2%), $1.46 billion in FY2022 (+5.2%) and $1.39 billion in FY2021 (-1.1%).
- Quarterly Operating Expenses has moved between $320 million (Q3 2021) and $590 million (Q4 2024) over five years.
- Compared with a year earlier, Operating Expenses was higher in four of the last eight quarters, with growth averaging 0.9%.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2023 (growth of 61.0%); the worst was Q3 2024 (a decline of 12.0%).
- Per Business Quant data, XYL's Operating Expenses in the three quarters before Q2 2026 was $559 million (Q1 2026), $579 million (Q4 2025) and $549 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Ecolab | 78.59 Bn | 70.36 Bn | 1.95 Bn | 1.14 Bn |
| 2 | Xylem | 23.57 Bn | 19.05 Bn | 963.00 Mn | 573.00 Mn |
| 3 | Veralto | 23.49 Bn | 16.14 Bn | 902.00 Mn | 587.00 Mn |
| 4 | Badger Meter | 3.66 Bn | 2.93 Bn | 90.77 Mn | 51.40 Mn |
| 5 | Ceco Environmental | 3.13 Bn | 2.96 Bn | 86.47 Mn | 109.35 Mn |
| 6 | NWPX Infrastructure | 993.98 Mn | 955.45 Mn | 34.36 Mn | 13.21 Mn |
| 7 | Energy Recovery | 343.89 Mn | 19.06 Mn | 8.96 Mn | 14.84 Mn |
| 8 | Cadiz | 301.30 Mn | 269.74 Mn | -24,000.00 | 9.81 Mn |
| 9 | AirJoule Technologies | 296.32 Mn | 175.95 Mn | - | 5.04 Mn |
| 10 | LanzaTech Global | 77.75 Mn | -37.39 Mn | 1.91 Mn | 18.89 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 573.00 Mn |
| Mar 31, 2026 | 559.00 Mn |
| Dec 31, 2025 | 579.00 Mn |
| Sep 30, 2025 | 549.00 Mn |
| Jun 30, 2025 | 587.00 Mn |
| Mar 31, 2025 | 537.00 Mn |
| Dec 31, 2024 | 590.00 Mn |
| Sep 30, 2024 | 504.00 Mn |
| Jun 30, 2024 | 566.00 Mn |
| Mar 31, 2024 | 543.00 Mn |
| Dec 31, 2023 | 545.00 Mn |
| Sep 30, 2023 | 573.00 Mn |
| Jun 30, 2023 | 532.00 Mn |
| Mar 31, 2023 | 415.00 Mn |
| Dec 31, 2022 | 376.00 Mn |
| Sep 30, 2022 | 356.00 Mn |
| Jun 30, 2022 | 374.00 Mn |
| Mar 31, 2022 | 356.00 Mn |
| Dec 31, 2021 | 353.00 Mn |
| Sep 30, 2021 | 320.00 Mn |
API Access
Xylem 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=XYL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "XYL", "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=XYL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();