e.l.f. Beauty (ELF) Operating Leases (2019 - 2026)
e.l.f. Beauty's Operating Leases came in at $89.66 million for fiscal Q1 2027 (quarter ended Jun 30, 2026), up 78.1% from $50.35 million a year earlier and up 28.2% from the prior quarter.
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Analysis
e.l.f. Beauty (ELF) Operating Leases (2019 - 2026) Analysis & Trends
At the end of FY2026 (ended Mar 31, 2026), e.l.f. Beauty's Operating Leases was $69.93 million, up 43.5% from FY2025.
- Operating Leases has increased in each of the last three fiscal years, with a five-year compound annual growth rate of 28.3% (FY2021 to FY2026).
- Going back by fiscal year, Operating Leases was $48.72 million in FY2025 (+127.0%), $21.46 million in FY2024 (+91.6%), $11.2 million in FY2023 (-28.9%) and $15.74 million in FY2022 (-21.6%).
- The fiscal Q1 2027 figure represents the highest quarterly Operating Leases in data going back to fiscal Q4 2019.
- Year-over-year, Operating Leases has increased for 12 consecutive quarters, with growth averaging 82.8% over the last eight quarters.
- The fastest year-over-year change in Operating Leases over five years came in fiscal Q1 2025 (growth of 231.8%), and the weakest in fiscal Q1 2024 (a decline of 30.7%).
- Business Quant data shows ELF's Operating Leases at $69.93 million (Q4 2026), $67.48 million (Q3 2026) and $55.63 million (Q2 2026) in the three fiscal quarters before Q1 2027.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Procter & Gamble | 346.43 Bn | 302.42 Bn | 10.28 Bn |
| 2 | Colgate Palmolive | 69.04 Bn | 64.10 Bn | 3.30 Bn |
| 3 | Estee Lauder Companies | 34.63 Bn | 22.70 Bn | 2.74 Bn |
| 4 | Kenvue | 34.35 Bn | 29.97 Bn | 2.30 Bn |
| 5 | Kimberly Clark | 32.85 Bn | 30.17 Bn | 1.60 Bn |
| 6 | Church & Dwight | 22.69 Bn | 21.21 Bn | 693.90 Mn |
| 7 | Clorox | 9.84 Bn | 8.28 Bn | 804.00 Mn |
| 8 | e.l.f. Beauty | 6.00 Bn | 4.97 Bn | 398.84 Mn |
| 9 | Reynolds Consumer Products | 4.65 Bn | 4.32 Bn | 245.00 Mn |
| 10 | Interparfums | 3.78 Bn | 3.58 Bn | 223.53 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 89.66 Mn |
| Mar 31, 2026 | 69.93 Mn |
| Dec 31, 2025 | 67.48 Mn |
| Sep 30, 2025 | 55.63 Mn |
| Jun 30, 2025 | 50.35 Mn |
| Mar 31, 2025 | 48.72 Mn |
| Dec 31, 2024 | 48.12 Mn |
| Sep 30, 2024 | 36.18 Mn |
| Jun 30, 2024 | 33.64 Mn |
| Mar 31, 2024 | 21.46 Mn |
| Dec 31, 2023 | 21.72 Mn |
| Sep 30, 2023 | 14.56 Mn |
| Jun 30, 2023 | 10.14 Mn |
| Mar 31, 2023 | 11.20 Mn |
| Dec 31, 2022 | 12.33 Mn |
| Sep 30, 2022 | 13.44 Mn |
| Jun 30, 2022 | 14.64 Mn |
| Mar 31, 2022 | 15.74 Mn |
| Dec 31, 2021 | 16.66 Mn |
| Sep 30, 2021 | 17.92 Mn |
API Access
e.l.f. Beauty Operating Leases 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-leases&ticker=ELF&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-leases", "ticker": "ELF", "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-leases&ticker=ELF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();