Latham (SWIM) Inventory (2020 - 2026)
Latham's Inventory was $79.61 million in Q2 2026, up 1.2% from $78.65 million a year earlier but down 9.1% from the prior quarter.
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Analysis
Latham (SWIM) Inventory (2020 - 2026) Analysis & Trends
At the end of FY2025, Inventory at Latham came in at $74.93 million, down 2.8% from FY2024.
- Inventory has now declined for three consecutive years, though with a five-year compound annual growth rate of 2.9% (FY2020 to FY2025).
- In earlier years, Inventory was $77.1 million in FY2024 (-20.6%), $97.14 million in FY2023 (-41.2%), $165.22 million in FY2022 (+50.8%) and $109.56 million in FY2021 (+69.0%).
- Quarterly Inventory has moved between $70.32 million (Q3 2025) and $166.43 million (Q3 2022) over five years.
- Compared with a year earlier, Inventory was higher in two of the last eight quarters, with an average decline of 8.7%.
- The best year-over-year quarter for Inventory over five years was Q2 2022 (growth of 117.4%); the worst was Q4 2023 (a decline of 41.2%).
- Per Business Quant data, SWIM's Inventory in the three quarters before Q2 2026 was $87.61 million (Q1 2026), $74.93 million (Q4 2025) and $70.32 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Inventory (Qtr) |
|---|---|---|---|---|---|
| 1 | Trane Technologies | 101.77 Bn | 96.49 Bn | 2.26 Bn | 2.62 Bn |
| 2 | Johnson Controls International | 89.79 Bn | 87.52 Bn | 2.47 Bn | 1.96 Bn |
| 3 | Comfort Systems Usa | 49.37 Bn | 44.62 Bn | 844.23 Mn | 104.80 Mn |
| 4 | Carrier Global | 46.49 Bn | 40.80 Bn | 1.94 Bn | 2.76 Bn |
| 5 | Otis Worldwide | 27.54 Bn | 23.96 Bn | 1.14 Bn | 686.00 Mn |
| 6 | James Hardie Industries | 15.37 Bn | 14.44 Bn | 548.70 Mn | 612.10 Mn |
| 7 | Masco | 14.88 Bn | 12.74 Bn | 868.00 Mn | 1.06 Bn |
| 8 | Carlisle Companies | 13.65 Bn | 9.99 Bn | 568.40 Mn | 492.70 Mn |
| 9 | Allegion | 13.45 Bn | 12.16 Bn | 517.50 Mn | 541.90 Mn |
| 10 | Latham | 741.86 Mn | 741.86 Mn | 70.08 Mn | 79.61 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 79.61 Mn |
| Mar 28, 2026 | 87.61 Mn |
| Dec 31, 2025 | 74.93 Mn |
| Sep 27, 2025 | 70.32 Mn |
| Jun 28, 2025 | 78.65 Mn |
| Mar 29, 2025 | 86.86 Mn |
| Dec 31, 2024 | 77.10 Mn |
| Sep 28, 2024 | 74.94 Mn |
| Jun 29, 2024 | 83.67 Mn |
| Mar 30, 2024 | 95.15 Mn |
| Dec 31, 2023 | 97.14 Mn |
| Sep 30, 2023 | 103.22 Mn |
| Jul 1, 2023 | 126.52 Mn |
| Apr 1, 2023 | 149.56 Mn |
| Dec 31, 2022 | 165.22 Mn |
| Oct 1, 2022 | 166.43 Mn |
| Jul 2, 2022 | 161.92 Mn |
| Apr 2, 2022 | 140.07 Mn |
| Dec 31, 2021 | 109.56 Mn |
| Oct 2, 2021 | 80.71 Mn |
API Access
Latham Inventory 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=inventory&ticker=SWIM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "inventory", "ticker": "SWIM", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=inventory&ticker=SWIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();